xarray_test.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "import os\n",
    "from glob import glob\n",
    "\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import numpy.ma as ma\n",
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import plotly.graph_objs as go\n",
    "import plotly.io as pio\n",
    "import xarray as xr\n",
    "\n",
    "from dask.distributed import Client\n",
    "from IPython.display import Image, HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from icenet.data.sic.mask import Masks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load data from numpy files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "root = \"../pipeline\"\n",
    "name = \"sipn_test_0_south_forecast\"\n",
    "dates = [dt.date(*[2022, 12, 1])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_prediction_data_nb(root: object, name: object, date: object) -> tuple:\n",
    "    \"\"\"\n",
    "    Based on IceNet library v0.2.7.\n",
    "    \n",
    "    Ref:\n",
    "    https://github.com/icenet-ai/icenet/blob/cb1cb785808ba1138c0ed0f8f88208a144daa6ff/icenet/process/predict.py#L63-L89\n",
    "    \"\"\"\n",
    "    glob_str = os.path.join(root, \"results\", \"predict\", name, \"*\",\n",
    "                            date.strftime(\"%Y_%m_%d.npy\"))\n",
    "\n",
    "    np_files = glob(glob_str)\n",
    "    if not len(np_files):\n",
    "        logging.warning(\"No files found\")\n",
    "        return None\n",
    "\n",
    "    data = [np.load(f) for f in np_files]\n",
    "    data = np.array(data)\n",
    "    ens_members = data.shape[0]\n",
    "\n",
    "    logging.debug(\"Data read from disk: {} from: {}\".format(\n",
    "        data.shape, np_files))\n",
    "\n",
    "    return np.stack([data.mean(axis=0), data.std(axis=0)],\n",
    "                    axis=-1).squeeze(), data, ens_members"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of ensemble members: 10\n"
     ]
    }
   ],
   "source": [
    "arr, data, ens_members = get_prediction_data_nb(root, name, dates[0])\n",
    "\n",
    "# Make sure we're only working with the 90 days needed for the SIPN South submission.\n",
    "data = data[..., :90]\n",
    "\n",
    "print(\"Number of ensemble members:\", ens_members)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load ensemble mean + stddev data from final netcdf output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_dataset(\"../pipeline/results/predict/sipn_test_0_south_forecast.nc\")\n",
    "land_mask = Masks(south=True, north=False).get_land_mask()\n",
    "\n",
    "# Dimensions for all data being inserted into xarray\n",
    "data_dims_list = [\"time\", \"yc\", \"xc\", \"leadtime\"]\n",
    "\n",
    "# Dict to store all ensemble results (for creating an xarray)\n",
    "sic_data = {}\n",
    "\n",
    "# Apply np.nan to land mask regions (emulating icenet output)\n",
    "land_mask_nan = land_mask.astype(float)\n",
    "land_mask_nan[land_mask] = np.nan\n",
    "land_mask_nan[~land_mask] = 1.0\n",
    "\n",
    "for ensemble in range(ens_members):\n",
    "    sic_data[f\"sic_{ensemble}\"] = (data_dims_list, data[ensemble]*land_mask_nan[np.newaxis, :, :, np.newaxis])\n",
    "\n",
    "\n",
    "data_vars=dict(\n",
    "    Lambert_Azimuthal_Grid=ds.Lambert_Azimuthal_Grid.data,\n",
    "    # Extract just the first date (incase more have been predicted)\n",
    "    # and up to 90 forecast days.\n",
    "    sic_mean=(data_dims_list, ds.sic_mean[:1, ..., :90].data),\n",
    "    sic_stddev=(data_dims_list, ds.sic_stddev[:1, ..., :90].data),\n",
    "    ensemble_members=([\"time\"], [ens_members]),\n",
    ")\n",
    "\n",
    "data_vars.update(sic_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert all ensemble prediction data to Xarray dataset, using ensemble mean netCDF file as template"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                 (time: 1, yc: 432, xc: 432, leadtime: 90,\n",
       "                             forecast_date: 90)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2022-12-01\n",
       "  * leadtime                (leadtime) int64 1 2 3 4 5 6 7 ... 85 86 87 88 89 90\n",
       "  * forecast_date           (forecast_date) datetime64[ns] 2022-12-02 ... 202...\n",
       "  * xc                      (xc) float64 -5.388e+03 -5.362e+03 ... 5.388e+03\n",
       "  * yc                      (yc) float64 5.388e+03 5.362e+03 ... -5.388e+03\n",
       "    lat                     (yc, xc) float32 -16.62 -16.82 ... -16.82 -16.62\n",
       "    lon                     (yc, xc) float32 315.0 315.1 315.3 ... 135.1 135.0\n",
       "Data variables: (12/14)\n",
       "    Lambert_Azimuthal_Grid  int32 -2147483647\n",
       "    sic_mean                (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    sic_stddev              (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    ensemble_members        (time) int64 10\n",
       "    sic_0                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_1                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    ...                      ...\n",
       "    sic_4                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_5                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_6                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_7                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_8                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_9                   (time, yc, xc, leadtime) float64 nan nan ... nan nan</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-dbafd874-0dfc-4978-b85e-64046ab448e1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dbafd874-0dfc-4978-b85e-64046ab448e1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>yc</span>: 432</li><li><span class='xr-has-index'>xc</span>: 432</li><li><span class='xr-has-index'>leadtime</span>: 90</li><li><span class='xr-has-index'>forecast_date</span>: 90</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-52768378-6e71-443f-8119-2373ab5552ee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-52768378-6e71-443f-8119-2373ab5552ee' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-12-01</div><input id='attrs-2b4c3073-192d-42ba-be88-c1bf1b8fcf5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b4c3073-192d-42ba-be88-c1bf1b8fcf5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8da8ba7-8639-47ed-8fb6-36deb1ee6d8a' class='xr-var-data-in' type='checkbox'><label for='data-b8da8ba7-8639-47ed-8fb6-36deb1ee6d8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-12-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>leadtime</span></div><div class='xr-var-dims'>(leadtime)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 85 86 87 88 89 90</div><input id='attrs-31c98ae8-d527-4817-9cd8-489de102216b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-31c98ae8-d527-4817-9cd8-489de102216b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb8e72e6-ff7b-400b-894d-40df13dbb12b' class='xr-var-data-in' type='checkbox'><label for='data-fb8e72e6-ff7b-400b-894d-40df13dbb12b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,\n",
       "       55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,\n",
       "       73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>forecast_date</span></div><div class='xr-var-dims'>(forecast_date)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-12-02 ... 2023-03-01</div><input id='attrs-bb16c1aa-a66e-47d4-a707-9aeacbfce6a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb16c1aa-a66e-47d4-a707-9aeacbfce6a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78b1647c-851c-4d0d-8ed6-3d422c6948b1' class='xr-var-data-in' type='checkbox'><label for='data-78b1647c-851c-4d0d-8ed6-3d422c6948b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-12-02T00:00:00.000000000&#x27;, &#x27;2022-12-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-04T00:00:00.000000000&#x27;, &#x27;2022-12-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-06T00:00:00.000000000&#x27;, &#x27;2022-12-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-08T00:00:00.000000000&#x27;, &#x27;2022-12-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-10T00:00:00.000000000&#x27;, &#x27;2022-12-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-12T00:00:00.000000000&#x27;, &#x27;2022-12-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-14T00:00:00.000000000&#x27;, &#x27;2022-12-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-16T00:00:00.000000000&#x27;, &#x27;2022-12-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-18T00:00:00.000000000&#x27;, &#x27;2022-12-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-20T00:00:00.000000000&#x27;, &#x27;2022-12-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-22T00:00:00.000000000&#x27;, &#x27;2022-12-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-24T00:00:00.000000000&#x27;, &#x27;2022-12-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-26T00:00:00.000000000&#x27;, &#x27;2022-12-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-28T00:00:00.000000000&#x27;, &#x27;2022-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-30T00:00:00.000000000&#x27;, &#x27;2022-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-01T00:00:00.000000000&#x27;, &#x27;2023-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-03T00:00:00.000000000&#x27;, &#x27;2023-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-05T00:00:00.000000000&#x27;, &#x27;2023-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-07T00:00:00.000000000&#x27;, &#x27;2023-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-09T00:00:00.000000000&#x27;, &#x27;2023-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-11T00:00:00.000000000&#x27;, &#x27;2023-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-13T00:00:00.000000000&#x27;, &#x27;2023-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-15T00:00:00.000000000&#x27;, &#x27;2023-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-17T00:00:00.000000000&#x27;, &#x27;2023-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-19T00:00:00.000000000&#x27;, &#x27;2023-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-21T00:00:00.000000000&#x27;, &#x27;2023-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-23T00:00:00.000000000&#x27;, &#x27;2023-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-25T00:00:00.000000000&#x27;, &#x27;2023-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-27T00:00:00.000000000&#x27;, &#x27;2023-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-29T00:00:00.000000000&#x27;, &#x27;2023-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-31T00:00:00.000000000&#x27;, &#x27;2023-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-02T00:00:00.000000000&#x27;, &#x27;2023-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-04T00:00:00.000000000&#x27;, &#x27;2023-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-06T00:00:00.000000000&#x27;, &#x27;2023-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-08T00:00:00.000000000&#x27;, &#x27;2023-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-10T00:00:00.000000000&#x27;, &#x27;2023-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-12T00:00:00.000000000&#x27;, &#x27;2023-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-14T00:00:00.000000000&#x27;, &#x27;2023-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-16T00:00:00.000000000&#x27;, &#x27;2023-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-18T00:00:00.000000000&#x27;, &#x27;2023-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-20T00:00:00.000000000&#x27;, &#x27;2023-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-22T00:00:00.000000000&#x27;, &#x27;2023-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-24T00:00:00.000000000&#x27;, &#x27;2023-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-26T00:00:00.000000000&#x27;, &#x27;2023-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-28T00:00:00.000000000&#x27;, &#x27;2023-03-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xc</span></div><div class='xr-var-dims'>(xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.388e+03 -5.362e+03 ... 5.388e+03</div><input id='attrs-884e3de7-0fc6-4b23-abac-5276e216ee8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-884e3de7-0fc6-4b23-abac-5276e216ee8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c02e5bcd-5355-4581-919e-2ab6f74441d9' class='xr-var-data-in' type='checkbox'><label for='data-c02e5bcd-5355-4581-919e-2ab6f74441d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-5387.5, -5362.5, -5337.5, ...,  5337.5,  5362.5,  5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yc</span></div><div class='xr-var-dims'>(yc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.388e+03 5.362e+03 ... -5.388e+03</div><input id='attrs-610bf4d6-b238-4b0b-9eb0-5d42eea031f2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-610bf4d6-b238-4b0b-9eb0-5d42eea031f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8e2cbdb-ae87-4bd7-abbd-42b8fe27e0c6' class='xr-var-data-in' type='checkbox'><label for='data-f8e2cbdb-ae87-4bd7-abbd-42b8fe27e0c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 5387.5,  5362.5,  5337.5, ..., -5337.5, -5362.5, -5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-16.62 -16.82 ... -16.82 -16.62</div><input id='attrs-3ecb26c2-29dd-4c9f-8bfd-9affab1f136d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ecb26c2-29dd-4c9f-8bfd-9affab1f136d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1431d4e-89ee-4b28-9fd9-92832cc300c6' class='xr-var-data-in' type='checkbox'><label for='data-f1431d4e-89ee-4b28-9fd9-92832cc300c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-16.623926, -16.822655, -17.020658, ..., -17.020658, -16.822655,\n",
       "        -16.623926],\n",
       "       [-16.822655, -17.021584, -17.219795, ..., -17.219795, -17.021584,\n",
       "        -16.822655],\n",
       "       [-17.020658, -17.219795, -17.418213, ..., -17.418213, -17.219795,\n",
       "        -17.020658],\n",
       "       ...,\n",
       "       [-17.020658, -17.219795, -17.418213, ..., -17.418213, -17.219795,\n",
       "        -17.020658],\n",
       "       [-16.822655, -17.021584, -17.219795, ..., -17.219795, -17.021584,\n",
       "        -16.822655],\n",
       "       [-16.623926, -16.822655, -17.020658, ..., -17.020658, -16.822655,\n",
       "        -16.623926]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>315.0 315.1 315.3 ... 135.1 135.0</div><input id='attrs-93ec659b-2688-4da0-881e-39bfa7eeb8d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93ec659b-2688-4da0-881e-39bfa7eeb8d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a97ac8f2-bd7a-4359-a01b-dade1ea94b1e' class='xr-var-data-in' type='checkbox'><label for='data-a97ac8f2-bd7a-4359-a01b-dade1ea94b1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[315.      , 315.13324 , 315.26712 , ...,  44.732887,  44.866753,\n",
       "         45.      ],\n",
       "       [314.86676 , 315.      , 315.13388 , ...,  44.86613 ,  45.      ,\n",
       "         45.133247],\n",
       "       [314.73288 , 314.86612 , 315.      , ...,  45.      ,  45.13387 ,\n",
       "         45.267113],\n",
       "       ...,\n",
       "       [225.2671  , 225.13387 , 225.      , ..., 135.      , 134.86613 ,\n",
       "        134.7329  ],\n",
       "       [225.13324 , 225.      , 224.86613 , ..., 135.13387 , 135.      ,\n",
       "        134.86676 ],\n",
       "       [225.      , 224.86676 , 224.7329  , ..., 135.2671  , 135.13324 ,\n",
       "        135.      ]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-85182d0f-3d2c-4e45-84d1-1db41fb978f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85182d0f-3d2c-4e45-84d1-1db41fb978f5' class='xr-section-summary' >Data variables: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Azimuthal_Grid</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-2147483647</div><input id='attrs-23605d73-67f7-464e-a22e-2780e03e140a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-23605d73-67f7-464e-a22e-2780e03e140a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f59808b-9ab1-4217-9b8e-88cf6af41558' class='xr-var-data-in' type='checkbox'><label for='data-0f59808b-9ab1-4217-9b8e-88cf6af41558' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_mean</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-28249205-3f6f-4950-ab24-a314de9bad1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28249205-3f6f-4950-ab24-a314de9bad1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e762af66-91ce-48df-be85-9a0541a1df40' class='xr-var-data-in' type='checkbox'><label for='data-e762af66-91ce-48df-be85-9a0541a1df40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_stddev</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1c18242c-2cf7-4c96-a251-4e1c179a3f06' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c18242c-2cf7-4c96-a251-4e1c179a3f06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-603ee641-63cb-490a-8f45-04db1fc95630' class='xr-var-data-in' type='checkbox'><label for='data-603ee641-63cb-490a-8f45-04db1fc95630' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_members</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10</div><input id='attrs-bdd33095-cad1-4249-a391-7f73a6d20335' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bdd33095-cad1-4249-a391-7f73a6d20335' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-639d43b6-0bf1-4f4b-a02b-b4ae0b72adea' class='xr-var-data-in' type='checkbox'><label for='data-639d43b6-0bf1-4f4b-a02b-b4ae0b72adea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_0</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c0e70775-b215-4cd0-bd1b-73aabb0d1daa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0e70775-b215-4cd0-bd1b-73aabb0d1daa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1959709e-4040-4a32-a5d1-4d992be97936' class='xr-var-data-in' type='checkbox'><label for='data-1959709e-4040-4a32-a5d1-4d992be97936' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.43546271, 0.37026793, 0.38513866, ..., 0.20089132,\n",
       "          0.22477475, 0.29234824],\n",
       "         [0.34813896, 0.21314788, 0.29871118, ..., 0.085154  ,\n",
       "          0.11338163, 0.16429025],\n",
       "         [0.22015163, 0.1430112 , 0.19584388, ..., 0.03289658,\n",
       "          0.05897863, 0.08072057],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_1</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e4d1c947-ba0d-44ad-a0f5-134764fb8c05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e4d1c947-ba0d-44ad-a0f5-134764fb8c05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce3732bc-b333-470b-b92d-da08e8e4e124' class='xr-var-data-in' type='checkbox'><label for='data-ce3732bc-b333-470b-b92d-da08e8e4e124' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.27981219, 0.20967744, 0.28286988, ..., 0.33187747,\n",
       "          0.38675809, 0.38616663],\n",
       "         [0.15031554, 0.08483678, 0.12239245, ..., 0.28936812,\n",
       "          0.33306465, 0.36288041],\n",
       "         [0.09304503, 0.05237206, 0.08056372, ..., 0.25192571,\n",
       "          0.29161525, 0.32653633],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_2</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f29b8a87-ade1-4367-8011-85bcca3dc36b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f29b8a87-ade1-4367-8011-85bcca3dc36b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6bf0a011-91bd-48ee-b1b3-3d031059ca54' class='xr-var-data-in' type='checkbox'><label for='data-6bf0a011-91bd-48ee-b1b3-3d031059ca54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "...\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[1.42367184e-01, 1.71970531e-01, 2.10496888e-01, ...,\n",
       "          1.73464596e-01, 1.96219593e-01, 1.56793818e-01],\n",
       "         [7.95661937e-03, 1.33165047e-02, 3.89877260e-02, ...,\n",
       "          7.06684813e-02, 8.52031112e-02, 8.54360610e-02],\n",
       "         [4.56487201e-03, 9.09389369e-03, 2.64396686e-02, ...,\n",
       "          4.74817008e-02, 6.29124641e-02, 7.47558698e-02],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_3</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a4cd0a72-a50b-4c8e-8add-2c85220a5ee6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a4cd0a72-a50b-4c8e-8add-2c85220a5ee6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5922b087-84eb-467c-ba41-584a04100f1f' class='xr-var-data-in' type='checkbox'><label for='data-5922b087-84eb-467c-ba41-584a04100f1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.17986992, 0.21535903, 0.33764455, ..., 0.07805378,\n",
       "          0.06725815, 0.10163599],\n",
       "         [0.08526587, 0.13014406, 0.19338752, ..., 0.01391541,\n",
       "          0.0088136 , 0.02054477],\n",
       "         [0.08408061, 0.15394139, 0.19280891, ..., 0.00511451,\n",
       "          0.00418384, 0.00732684],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_4</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-98620d1b-ec82-4d8a-8f46-3251611d9248' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98620d1b-ec82-4d8a-8f46-3251611d9248' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc6ad29c-2e0a-4825-9600-9fff357403a0' class='xr-var-data-in' type='checkbox'><label for='data-dc6ad29c-2e0a-4825-9600-9fff357403a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.31426087, 0.29592282, 0.27920938, ..., 0.26806128,\n",
       "          0.28302735, 0.29121372],\n",
       "         [0.19278514, 0.15577853, 0.14676079, ..., 0.20317332,\n",
       "          0.15370034, 0.19881955],\n",
       "         [0.12911101, 0.101769  , 0.08995824, ..., 0.13751206,\n",
       "          0.12890065, 0.18146357],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_5</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-35626238-a0c5-4aaf-9987-8dc56bf2f381' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-35626238-a0c5-4aaf-9987-8dc56bf2f381' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-759a57c3-bf1a-4b8a-9b06-50c40fac7798' class='xr-var-data-in' type='checkbox'><label for='data-759a57c3-bf1a-4b8a-9b06-50c40fac7798' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "...\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[2.46456698e-01, 2.35801056e-01, 2.66234815e-01, ...,\n",
       "          1.56594694e-01, 1.50486544e-01, 1.98674217e-01],\n",
       "         [1.15394250e-01, 1.02601603e-01, 1.23624563e-01, ...,\n",
       "          5.22547774e-02, 6.75010681e-02, 8.19411576e-02],\n",
       "         [5.91113493e-02, 7.05489814e-02, 8.60279724e-02, ...,\n",
       "          2.22039726e-02, 2.69966591e-02, 3.62032540e-02],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_6</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-13ad3b45-55f3-4bff-a69a-8df5f911b87b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13ad3b45-55f3-4bff-a69a-8df5f911b87b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db3a41dc-7542-4a56-8dab-6ecce0c97441' class='xr-var-data-in' type='checkbox'><label for='data-db3a41dc-7542-4a56-8dab-6ecce0c97441' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.1449472 , 0.13899584, 0.10194253, ..., 0.29294634,\n",
       "          0.24550755, 0.38018867],\n",
       "         [0.13430873, 0.109274  , 0.05767117, ..., 0.13798775,\n",
       "          0.11910193, 0.19426842],\n",
       "         [0.14191654, 0.11193305, 0.06901318, ..., 0.1086472 ,\n",
       "          0.0787862 , 0.15395975],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_7</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c6e14e7f-ac3f-4b72-87a9-d03d1ca8ee18' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c6e14e7f-ac3f-4b72-87a9-d03d1ca8ee18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d62c8b6a-f5dd-43a5-b7cf-555e17252714' class='xr-var-data-in' type='checkbox'><label for='data-d62c8b6a-f5dd-43a5-b7cf-555e17252714' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.15513363, 0.16686362, 0.19195944, ..., 0.13384481,\n",
       "          0.17087106, 0.11655044],\n",
       "         [0.04392734, 0.0482244 , 0.05548367, ..., 0.03709038,\n",
       "          0.06600705, 0.05891169],\n",
       "         [0.02791904, 0.02877719, 0.04118795, ..., 0.03086862,\n",
       "          0.0520237 , 0.05165823],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_8</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d5e20519-f550-4beb-adbc-7f90e13dee78' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5e20519-f550-4beb-adbc-7f90e13dee78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10c8458d-4eea-47f9-82b8-83230c45969b' class='xr-var-data-in' type='checkbox'><label for='data-10c8458d-4eea-47f9-82b8-83230c45969b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.39364347, 0.43082312, 0.4546288 , ..., 0.20071581,\n",
       "          0.24593955, 0.2685419 ],\n",
       "         [0.39204255, 0.40901262, 0.39442235, ..., 0.08475831,\n",
       "          0.07902467, 0.0975676 ],\n",
       "         [0.42609054, 0.43259823, 0.41768476, ..., 0.05672323,\n",
       "          0.05133029, 0.06806187],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_9</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fb83fae5-b756-48f1-87c8-f1c23d872f01' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fb83fae5-b756-48f1-87c8-f1c23d872f01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2aa9bb6-691c-4e81-8da6-c38814564a56' class='xr-var-data-in' type='checkbox'><label for='data-b2aa9bb6-691c-4e81-8da6-c38814564a56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "...\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[1.53539345e-01, 1.29758850e-01, 1.35938406e-01, ...,\n",
       "          2.07688555e-01, 1.29885882e-01, 2.10862756e-01],\n",
       "         [3.00696529e-02, 2.07671747e-02, 1.41037237e-02, ...,\n",
       "          5.39371110e-02, 4.55609709e-02, 9.63426828e-02],\n",
       "         [1.55482385e-02, 1.10586667e-02, 6.26199320e-03, ...,\n",
       "          4.71276678e-02, 6.30130172e-02, 1.08140334e-01],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-715a6530-eff4-4479-8e69-facd0ecf246c' class='xr-section-summary-in' type='checkbox'  ><label for='section-715a6530-eff4-4479-8e69-facd0ecf246c' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6ae77a65-2efc-4b27-a467-ecaa26c2a56f' class='xr-index-data-in' type='checkbox'/><label for='index-6ae77a65-2efc-4b27-a467-ecaa26c2a56f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-12-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>leadtime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-58e033ce-715f-442d-90d4-17f7ac324af2' class='xr-index-data-in' type='checkbox'/><label for='index-58e033ce-715f-442d-90d4-17f7ac324af2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "            18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,\n",
       "            35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,\n",
       "            52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68,\n",
       "            69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,\n",
       "            86, 87, 88, 89, 90],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;leadtime&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>forecast_date</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dbcebab3-089f-4ba7-8204-2101cbf6f2da' class='xr-index-data-in' type='checkbox'/><label for='index-dbcebab3-089f-4ba7-8204-2101cbf6f2da' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-12-02&#x27;, &#x27;2022-12-03&#x27;, &#x27;2022-12-04&#x27;, &#x27;2022-12-05&#x27;,\n",
       "               &#x27;2022-12-06&#x27;, &#x27;2022-12-07&#x27;, &#x27;2022-12-08&#x27;, &#x27;2022-12-09&#x27;,\n",
       "               &#x27;2022-12-10&#x27;, &#x27;2022-12-11&#x27;, &#x27;2022-12-12&#x27;, &#x27;2022-12-13&#x27;,\n",
       "               &#x27;2022-12-14&#x27;, &#x27;2022-12-15&#x27;, &#x27;2022-12-16&#x27;, &#x27;2022-12-17&#x27;,\n",
       "               &#x27;2022-12-18&#x27;, &#x27;2022-12-19&#x27;, &#x27;2022-12-20&#x27;, &#x27;2022-12-21&#x27;,\n",
       "               &#x27;2022-12-22&#x27;, &#x27;2022-12-23&#x27;, &#x27;2022-12-24&#x27;, &#x27;2022-12-25&#x27;,\n",
       "               &#x27;2022-12-26&#x27;, &#x27;2022-12-27&#x27;, &#x27;2022-12-28&#x27;, &#x27;2022-12-29&#x27;,\n",
       "               &#x27;2022-12-30&#x27;, &#x27;2022-12-31&#x27;, &#x27;2023-01-01&#x27;, &#x27;2023-01-02&#x27;,\n",
       "               &#x27;2023-01-03&#x27;, &#x27;2023-01-04&#x27;, &#x27;2023-01-05&#x27;, &#x27;2023-01-06&#x27;,\n",
       "               &#x27;2023-01-07&#x27;, &#x27;2023-01-08&#x27;, &#x27;2023-01-09&#x27;, &#x27;2023-01-10&#x27;,\n",
       "               &#x27;2023-01-11&#x27;, &#x27;2023-01-12&#x27;, &#x27;2023-01-13&#x27;, &#x27;2023-01-14&#x27;,\n",
       "               &#x27;2023-01-15&#x27;, &#x27;2023-01-16&#x27;, &#x27;2023-01-17&#x27;, &#x27;2023-01-18&#x27;,\n",
       "               &#x27;2023-01-19&#x27;, &#x27;2023-01-20&#x27;, &#x27;2023-01-21&#x27;, &#x27;2023-01-22&#x27;,\n",
       "               &#x27;2023-01-23&#x27;, &#x27;2023-01-24&#x27;, &#x27;2023-01-25&#x27;, &#x27;2023-01-26&#x27;,\n",
       "               &#x27;2023-01-27&#x27;, &#x27;2023-01-28&#x27;, &#x27;2023-01-29&#x27;, &#x27;2023-01-30&#x27;,\n",
       "               &#x27;2023-01-31&#x27;, &#x27;2023-02-01&#x27;, &#x27;2023-02-02&#x27;, &#x27;2023-02-03&#x27;,\n",
       "               &#x27;2023-02-04&#x27;, &#x27;2023-02-05&#x27;, &#x27;2023-02-06&#x27;, &#x27;2023-02-07&#x27;,\n",
       "               &#x27;2023-02-08&#x27;, &#x27;2023-02-09&#x27;, &#x27;2023-02-10&#x27;, &#x27;2023-02-11&#x27;,\n",
       "               &#x27;2023-02-12&#x27;, &#x27;2023-02-13&#x27;, &#x27;2023-02-14&#x27;, &#x27;2023-02-15&#x27;,\n",
       "               &#x27;2023-02-16&#x27;, &#x27;2023-02-17&#x27;, &#x27;2023-02-18&#x27;, &#x27;2023-02-19&#x27;,\n",
       "               &#x27;2023-02-20&#x27;, &#x27;2023-02-21&#x27;, &#x27;2023-02-22&#x27;, &#x27;2023-02-23&#x27;,\n",
       "               &#x27;2023-02-24&#x27;, &#x27;2023-02-25&#x27;, &#x27;2023-02-26&#x27;, &#x27;2023-02-27&#x27;,\n",
       "               &#x27;2023-02-28&#x27;, &#x27;2023-03-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;forecast_date&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>xc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-beeef3a1-661f-459d-a2a4-6353e66cb426' class='xr-index-data-in' type='checkbox'/><label for='index-beeef3a1-661f-459d-a2a4-6353e66cb426' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-5387.5, -5362.5, -5337.5, -5312.5, -5287.5, -5262.5, -5237.5,\n",
       "              -5212.5, -5187.5, -5162.5,\n",
       "              ...\n",
       "               5162.5,  5187.5,  5212.5,  5237.5,  5262.5,  5287.5,  5312.5,\n",
       "               5337.5,  5362.5,  5387.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;xc&#x27;, length=432))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-91d0978a-a602-444d-bc6a-5a118ed46b87' class='xr-index-data-in' type='checkbox'/><label for='index-91d0978a-a602-444d-bc6a-5a118ed46b87' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 5387.5,  5362.5,  5337.5,  5312.5,  5287.5,  5262.5,  5237.5,\n",
       "               5212.5,  5187.5,  5162.5,\n",
       "              ...\n",
       "              -5162.5, -5187.5, -5212.5, -5237.5, -5262.5, -5287.5, -5312.5,\n",
       "              -5337.5, -5362.5, -5387.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;yc&#x27;, length=432))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b8b4b497-63d4-4f74-ba4c-8d282838c850' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b8b4b497-63d4-4f74-ba4c-8d282838c850' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                 (time: 1, yc: 432, xc: 432, leadtime: 90,\n",
       "                             forecast_date: 90)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2022-12-01\n",
       "  * leadtime                (leadtime) int64 1 2 3 4 5 6 7 ... 85 86 87 88 89 90\n",
       "  * forecast_date           (forecast_date) datetime64[ns] 2022-12-02 ... 202...\n",
       "  * xc                      (xc) float64 -5.388e+03 -5.362e+03 ... 5.388e+03\n",
       "  * yc                      (yc) float64 5.388e+03 5.362e+03 ... -5.388e+03\n",
       "    lat                     (yc, xc) float32 -16.62 -16.82 ... -16.82 -16.62\n",
       "    lon                     (yc, xc) float32 315.0 315.1 315.3 ... 135.1 135.0\n",
       "Data variables: (12/14)\n",
       "    Lambert_Azimuthal_Grid  int32 -2147483647\n",
       "    sic_mean                (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    sic_stddev              (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    ensemble_members        (time) int64 10\n",
       "    sic_0                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_1                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    ...                      ...\n",
       "    sic_4                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_5                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_6                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_7                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_8                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_9                   (time, yc, xc, leadtime) float64 nan nan ... nan nan"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Update longitude range to be 0 to 360 instead of -180 to 180\n",
    "# makes life easier for Diagnostic 2.\n",
    "longitude = ds.lon.data.copy()\n",
    "longitude[longitude<0] += 360\n",
    "\n",
    "xarr = xr.Dataset(\n",
    "    data_vars=data_vars,\n",
    "    coords=dict(\n",
    "        time=[ds.time[1].data],\n",
    "        leadtime=ds.leadtime[:90].data,\n",
    "        forecast_date=ds.forecast_date[1][:90].data,\n",
    "        xc=ds.xc.data,\n",
    "        yc=ds.yc.data,\n",
    "        lat=((\"yc\", \"xc\"), ds.lat.data),\n",
    "        lon=((\"yc\", \"xc\"), longitude),\n",
    "    )\n",
    ")\n",
    "\n",
    "xarr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define functions to compute sea ice area and binned sea ice area."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sic_compute_np(sea_ice_concentration, grid_cell_area=25*25, threshold=0.15, plot=False):\n",
    "    sic = sea_ice_concentration\n",
    "\n",
    "    # Mask values less than the threshold\n",
    "    sic = ma.masked_where(sic<threshold, sic)\n",
    "\n",
    "    # Multiply by grid-cell area\n",
    "    sic *= 25*25\n",
    "\n",
    "    print(sic)\n",
    "    # Divide by 10^6 due to SIPN South unit requirement\n",
    "    # (i.e., units must be in 10^6 km^2)\n",
    "    sea_ice_area = np.sum(sic) / 1E6\n",
    "\n",
    "\n",
    "    return sea_ice_area\n",
    "\n",
    "def compute_sea_ice_area_binned_np(sea_ice_concentration, *args, **kwargs):\n",
    "    sic = sea_ice_concentration\n",
    "\n",
    "    longitude_bin = xr.DataArray(np.linspace(0, 360, 36+1))\n",
    "\n",
    "    sea_ice_area_binned = sic.groupby_bins(\"lon\", longitude_bin).map(sic_compute_np, args=args, **kwargs)\n",
    "\n",
    "    return sea_ice_area_binned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sic_compute(sea_ice_concentration, grid_cell_area=25*25, threshold=0.15, plot=False):\n",
    "    sic = sea_ice_concentration\n",
    "\n",
    "    # Mask values less than the threshold\n",
    "    sic = sic.where(sic>0.15)\n",
    "\n",
    "    # Multiply by grid-cell area\n",
    "    sic *= 25*25\n",
    "\n",
    "    # Divide by 10^6 due to SIPN South unit requirement\n",
    "    # (i.e., units must be in 10^6 km^2)\n",
    "    sea_ice_area = sic.sum() / 1E6\n",
    "\n",
    "    return sea_ice_area\n",
    "\n",
    "def compute_sea_ice_area_binned(sea_ice_concentration, *args, **kwargs):\n",
    "    sic = sea_ice_concentration\n",
    "\n",
    "    longitude_bin = xr.DataArray(np.linspace(0, 360, 36+1))\n",
    "\n",
    "    sea_ice_area_binned = sic.groupby_bins(\"lon\", longitude_bin).map(sic_compute, args=args, **kwargs)\n",
    "\n",
    "    print(sea_ice_area_binned)\n",
    "\n",
    "    return sea_ice_area_binned\n",
    "\n",
    "# def compute_sea_ice_area_binned_dask(sea_ice_concentration):\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sic_0&#x27; ()&gt;\n",
       "array(9.06379805)\n",
       "Coordinates:\n",
       "    leadtime  int64 1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sic_0'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b23680eb-756e-446b-9ea4-49b4e5da128d' class='xr-array-in' type='checkbox' checked><label for='section-b23680eb-756e-446b-9ea4-49b4e5da128d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>9.064</span></div><div class='xr-array-data'><pre>array(9.06379805)</pre></div></div></li><li class='xr-section-item'><input id='section-3a6e31dc-0cb0-4733-9232-6d27f9935fbd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3a6e31dc-0cb0-4733-9232-6d27f9935fbd' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>leadtime</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-76862fa1-bdff-431e-ac89-175caf7ce1d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-76862fa1-bdff-431e-ac89-175caf7ce1d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf4c223c-f0f4-4ff7-b427-eeda8a339d69' class='xr-var-data-in' type='checkbox'><label for='data-bf4c223c-f0f4-4ff7-b427-eeda8a339d69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e662abe-ec14-499d-b1d5-4470fa2c9a85' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2e662abe-ec14-499d-b1d5-4470fa2c9a85' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-48d907c3-31d8-4c04-bb91-4b4f9327e2f6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-48d907c3-31d8-4c04-bb91-4b4f9327e2f6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sic_0' ()>\n",
       "array(9.06379805)\n",
       "Coordinates:\n",
       "    leadtime  int64 1"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_ice_area = xarr[f\"sic_{0}\"].isel(leadtime=0).map_blocks(sic_compute)\n",
    "\n",
    "sea_ice_area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Frozen({'leadtime': (5, 5, 5, 5, 5, 5, 5, 1)})"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define a template DataArray for what's being returned to map_blocks.\n",
    "ret_array = xr.DataArray(\n",
    "    np.zeros((36)),\n",
    "    coords={\"leadtime\": np.zeros((36))},\n",
    ").chunk(5)\n",
    "\n",
    "ret_array.chunksizes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DataArrayGroupBy, grouped over 'lon_bins'\n",
       "36 groups with labels (310.0,, 320.0], ..., (150.0,, ...."
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xarr[f\"sic_{0}\"].chunk({\"leadtime\": 5}).groupby_bins(\"lon\", longitude_bin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "xarr_chunk = xarr.chunk({\"leadtime\": -1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sea_ice_area_binned = xarr[f\"sic_{0}\"].chunk({\"leadtime\": 5}).map_blocks(compute_sea_ice_area_binned, template=ret_array).compute()\n",
    "\n",
    "# sea_ice_area_binned = xarr[f\"sic_{0}\"].map_blocks(compute_sea_ice_area_binned).compute()\n",
    "# sea_ice_area_binned = xr.apply_ufunc(compute_sea_ice_area_binned, xarr[f\"sic_{0}\"].chunk({\"leadtime\": 5}), dask=\"parallelized\", output_dtypes=[float])\n",
    "\n",
    "\n",
    "# longitude_bin = xr.DataArray(np.linspace(0, 360, 36+1))\n",
    "# sea_ice_area_binned = xr.apply_ufunc(sic_compute_np,\n",
    "#                                      xarr[f\"sic_{0}\"].isel(leadtime=0).groupby_bins(\"lon\", longitude_bin),\n",
    "#                                     #  input_core_dims=[[\"lon_bins\"]],\n",
    "#                                      output_core_dims=[[\"dummy\"]],\n",
    "#                                      dask=\"parallelized\",\n",
    "#                                      output_dtypes=[float]\n",
    "#                                      )\n",
    "# sea_ice_area_binned.compute()\n",
    "\n",
    "sea_ice_area_binned = xarr_chunk[f\"sic_{0}\"].map_blocks(compute_sea_ice_area_binned, template=ret_array)\n",
    "\n",
    "sea_ice_area_binned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.34327669, 0.3839828 , 0.43273046, 0.29784033, 0.15688105,\n",
      "       0.07072017, 0.13614046, 0.17237017, 0.07775545, 0.08777086,\n",
      "       0.09086775, 0.08306254, 0.09707625, 0.07262376, 0.03565898,\n",
      "       0.0870581 , 0.20366686, 0.31378991, 0.32147637, 0.39611291,\n",
      "       0.38858803, 0.3685207 , 0.51234148, 0.42099894, 0.19957403,\n",
      "       0.16657304, 0.18682177, 0.03583466, 0.02015961, 0.02886602,\n",
      "       0.46195762, 0.502402  , 0.49096155, 0.5194478 , 0.47865723,\n",
      "       0.42123173])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 1\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.33502117, 0.37432696, 0.42631134, 0.28953455, 0.14581124,\n",
      "       0.06775585, 0.12970424, 0.16246567, 0.0759885 , 0.08540233,\n",
      "       0.08905887, 0.08069495, 0.09497735, 0.07231736, 0.03546305,\n",
      "       0.08446485, 0.20015638, 0.3092064 , 0.31852199, 0.38964366,\n",
      "       0.37511226, 0.35022513, 0.48779807, 0.40283291, 0.19355556,\n",
      "       0.16454401, 0.18152951, 0.03463692, 0.0190133 , 0.02877582,\n",
      "       0.46179209, 0.50323335, 0.48976924, 0.51396287, 0.47357815,\n",
      "       0.41381007])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 2\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.34694218, 0.3808448 , 0.43012707, 0.28972307, 0.14104525,\n",
      "       0.0669747 , 0.12924569, 0.15991539, 0.07702646, 0.08659361,\n",
      "       0.0885412 , 0.08108758, 0.09630523, 0.07246916, 0.03566843,\n",
      "       0.09020332, 0.20368337, 0.31356209, 0.32048074, 0.38711011,\n",
      "       0.36956669, 0.34817867, 0.47508098, 0.40472234, 0.20071728,\n",
      "       0.1715194 , 0.18357236, 0.03916323, 0.02120701, 0.02904363,\n",
      "       0.46274256, 0.50978406, 0.5003453 , 0.52243518, 0.48043857,\n",
      "       0.42426439])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 3\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.34350536, 0.37415738, 0.42808299, 0.2821178 , 0.13128245,\n",
      "       0.06459833, 0.12549701, 0.15164923, 0.0769145 , 0.08575172,\n",
      "       0.08771981, 0.08079625, 0.09636623, 0.07255493, 0.03669163,\n",
      "       0.08808496, 0.20008118, 0.31338033, 0.32165582, 0.38228813,\n",
      "       0.3624358 , 0.34112842, 0.44845338, 0.38983598, 0.1986189 ,\n",
      "       0.17153306, 0.17723687, 0.03888412, 0.02066845, 0.02959106,\n",
      "       0.46295436, 0.51303652, 0.50300438, 0.52158476, 0.48303977,\n",
      "       0.42445059])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 4\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.32825821, 0.35859482, 0.41789093, 0.27104304, 0.12098726,\n",
      "       0.06183251, 0.119238  , 0.13867908, 0.0743423 , 0.08308225,\n",
      "       0.08464131, 0.0785559 , 0.09518967, 0.07074247, 0.03584177,\n",
      "       0.08929241, 0.20020832, 0.3116189 , 0.3208934 , 0.37139866,\n",
      "       0.34892651, 0.33019993, 0.4218271 , 0.36991719, 0.19595942,\n",
      "       0.16996005, 0.16871085, 0.03940994, 0.02015575, 0.02960118,\n",
      "       0.46291259, 0.51366429, 0.50220669, 0.51538   , 0.47535463,\n",
      "       0.41316363])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 5\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.31827202, 0.34502592, 0.40809173, 0.26227749, 0.11422807,\n",
      "       0.05897135, 0.11455373, 0.12756205, 0.07372443, 0.08258265,\n",
      "       0.08304177, 0.07814121, 0.09438995, 0.06995359, 0.03666104,\n",
      "       0.0933138 , 0.20205878, 0.31343181, 0.31838649, 0.36653007,\n",
      "       0.3435737 , 0.33059733, 0.40317664, 0.35933555, 0.19919153,\n",
      "       0.17050003, 0.16103053, 0.0417357 , 0.02033159, 0.02945435,\n",
      "       0.46235161, 0.51504212, 0.50352175, 0.5124946 , 0.47548427,\n",
      "       0.40760228])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 6\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.31504066, 0.33458887, 0.40095438, 0.25648415, 0.10806146,\n",
      "       0.05818463, 0.11303236, 0.12335995, 0.07551267, 0.08233562,\n",
      "       0.0837451 , 0.07816943, 0.09454754, 0.07016881, 0.03768427,\n",
      "       0.09978689, 0.20509964, 0.31635212, 0.32050347, 0.36422528,\n",
      "       0.3418286 , 0.33378373, 0.39670427, 0.35300903, 0.20276667,\n",
      "       0.17357977, 0.15703641, 0.04591932, 0.02491358, 0.03012511,\n",
      "       0.46462367, 0.5206613 , 0.5098471 , 0.51223644, 0.47755732,\n",
      "       0.40745442])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 7\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.30761838, 0.32575962, 0.39510804, 0.24855274, 0.10484827,\n",
      "       0.05797223, 0.11069328, 0.11842295, 0.07806358, 0.08461917,\n",
      "       0.08541132, 0.07905991, 0.09438894, 0.06983987, 0.03886734,\n",
      "       0.10343773, 0.20976807, 0.3210375 , 0.3244337 , 0.36084639,\n",
      "       0.33819188, 0.33653564, 0.39009735, 0.34567531, 0.20752185,\n",
      "       0.17629517, 0.15374269, 0.05144908, 0.02806945, 0.03077216,\n",
      "       0.46487956, 0.52372165, 0.5153798 , 0.51045951, 0.47507745,\n",
      "       0.40252214])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 8\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.29502993, 0.31279678, 0.38695887, 0.23997361, 0.10385961,\n",
      "       0.05753975, 0.10869273, 0.11386046, 0.08005206, 0.08736983,\n",
      "       0.08613497, 0.08043826, 0.09668378, 0.07116835, 0.0406839 ,\n",
      "       0.11165141, 0.2157999 , 0.32684396, 0.3242724 , 0.35919382,\n",
      "       0.33891903, 0.3442888 , 0.38720677, 0.33562956, 0.20574008,\n",
      "       0.17541383, 0.15103422, 0.05759582, 0.03044843, 0.03134332,\n",
      "       0.46734914, 0.52934538, 0.52461809, 0.51748171, 0.47601166,\n",
      "       0.39954371])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 9\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.27399925, 0.28970252, 0.36774904, 0.22593492, 0.10103371,\n",
      "       0.0558837 , 0.10312716, 0.10756112, 0.07913346, 0.08768427,\n",
      "       0.08625077, 0.08064141, 0.09674083, 0.0702271 , 0.04190298,\n",
      "       0.11379979, 0.21778504, 0.32693289, 0.32412795, 0.35120905,\n",
      "       0.33166181, 0.34053357, 0.37599819, 0.32414809, 0.20359674,\n",
      "       0.17469097, 0.14855345, 0.05880046, 0.03020649, 0.03163955,\n",
      "       0.46695998, 0.52935047, 0.52538173, 0.51248794, 0.4670144 ,\n",
      "       0.38396539])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 10\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.25934532, 0.27413247, 0.35827734, 0.21707438, 0.10406671,\n",
      "       0.05684095, 0.09960755, 0.10485899, 0.08200956, 0.09116989,\n",
      "       0.08824821, 0.08361271, 0.09940215, 0.07182342, 0.04501533,\n",
      "       0.12267161, 0.22293408, 0.32883469, 0.32566918, 0.35141467,\n",
      "       0.33392056, 0.34685937, 0.37519123, 0.31715968, 0.20736297,\n",
      "       0.17922165, 0.14629109, 0.05953393, 0.03040596, 0.03222754,\n",
      "       0.46842812, 0.53415817, 0.53625087, 0.51780475, 0.46828437,\n",
      "       0.37764198])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 11\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.23810062, 0.25715233, 0.34304297, 0.2040764 , 0.10248452,\n",
      "       0.05444403, 0.09046474, 0.09682774, 0.0797019 , 0.09133244,\n",
      "       0.08751407, 0.08376153, 0.09911421, 0.07187392, 0.04762089,\n",
      "       0.12774197, 0.22239847, 0.32995511, 0.32722392, 0.34221891,\n",
      "       0.32333581, 0.34031023, 0.36793997, 0.30964264, 0.2064461 ,\n",
      "       0.18169616, 0.14806003, 0.06393155, 0.03132704, 0.0321928 ,\n",
      "       0.46828688, 0.53446081, 0.539044  , 0.51387645, 0.45668851,\n",
      "       0.3622911 ])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 12\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.19970658, 0.22488564, 0.31400514, 0.18970449, 0.09823692,\n",
      "       0.05261477, 0.08094433, 0.08781611, 0.07611458, 0.08997563,\n",
      "       0.0851617 , 0.08322714, 0.09861697, 0.07153551, 0.05015569,\n",
      "       0.13049326, 0.2222225 , 0.32177644, 0.32154132, 0.33593927,\n",
      "       0.31811874, 0.33515178, 0.35741243, 0.29015932, 0.19584576,\n",
      "       0.17410414, 0.14250623, 0.05538731, 0.02999935, 0.03185182,\n",
      "       0.46693489, 0.53177475, 0.53674433, 0.50750518, 0.44547107,\n",
      "       0.33683243])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 13\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.17624765, 0.20865803, 0.29511251, 0.17999349, 0.10024348,\n",
      "       0.05024702, 0.07510478, 0.08322816, 0.07430352, 0.09001827,\n",
      "       0.08464742, 0.08394668, 0.09930719, 0.0723407 , 0.05321809,\n",
      "       0.13471436, 0.22276694, 0.32064191, 0.32270216, 0.33451815,\n",
      "       0.31740549, 0.336601  , 0.35659749, 0.28447237, 0.19411696,\n",
      "       0.17367597, 0.14156025, 0.05234243, 0.03053072, 0.03207832,\n",
      "       0.4664427 , 0.53241987, 0.53817418, 0.50676948, 0.44094453,\n",
      "       0.32255528])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 14\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.1471559 , 0.18861874, 0.26878284, 0.17028089, 0.10720702,\n",
      "       0.04868818, 0.0666056 , 0.07580402, 0.0703039 , 0.08897491,\n",
      "       0.08300873, 0.08713225, 0.10682981, 0.07256217, 0.05614994,\n",
      "       0.13920483, 0.22766683, 0.31894809, 0.32442351, 0.33019311,\n",
      "       0.31726905, 0.33682255, 0.3548839 , 0.27801289, 0.19395729,\n",
      "       0.17171322, 0.13898938, 0.05242974, 0.0341184 , 0.03268696,\n",
      "       0.46689535, 0.53092377, 0.53660392, 0.50459608, 0.43857364,\n",
      "       0.30157173])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 15\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.12370429, 0.17257876, 0.24841966, 0.16056175, 0.11023823,\n",
      "       0.04636337, 0.05783348, 0.07118807, 0.06633621, 0.08705501,\n",
      "       0.08067058, 0.08872199, 0.10672176, 0.07147426, 0.0587857 ,\n",
      "       0.14043784, 0.22743861, 0.31320176, 0.3194514 , 0.32310443,\n",
      "       0.31265549, 0.33041843, 0.35247307, 0.27210648, 0.19065956,\n",
      "       0.16712404, 0.13525455, 0.05239021, 0.03480645, 0.03271609,\n",
      "       0.46725407, 0.52786905, 0.53191878, 0.49888526, 0.42835817,\n",
      "       0.28021309])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 16\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.09960769, 0.15895199, 0.23276673, 0.15382505, 0.11252566,\n",
      "       0.04565128, 0.05214698, 0.06789326, 0.06242612, 0.08406518,\n",
      "       0.07822332, 0.09088434, 0.10865972, 0.07223625, 0.06317999,\n",
      "       0.14213083, 0.22935015, 0.3111282 , 0.31634547, 0.32187657,\n",
      "       0.31626239, 0.32998382, 0.35541025, 0.26679857, 0.18815529,\n",
      "       0.16243733, 0.13368021, 0.04987764, 0.03730499, 0.03331799,\n",
      "       0.46808995, 0.52687146, 0.5279249 , 0.49543165, 0.4250897 ,\n",
      "       0.25865164])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 17\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.07547044, 0.1427774 , 0.20873535, 0.14718043, 0.11406713,\n",
      "       0.04345509, 0.04414426, 0.06368931, 0.0580911 , 0.08082669,\n",
      "       0.07454587, 0.09000697, 0.10649529, 0.06959934, 0.06226552,\n",
      "       0.14099088, 0.22817946, 0.30402328, 0.31314496, 0.31355219,\n",
      "       0.30793556, 0.31770894, 0.34105408, 0.25566741, 0.18130681,\n",
      "       0.15656948, 0.12963932, 0.04651994, 0.03806216, 0.03320777,\n",
      "       0.46621462, 0.52077352, 0.52221427, 0.48623116, 0.40791295,\n",
      "       0.23200869])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 18\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.06333454, 0.12997076, 0.1858839 , 0.13806309, 0.11621872,\n",
      "       0.04139834, 0.03635928, 0.05908313, 0.05463936, 0.07671526,\n",
      "       0.07166205, 0.09173616, 0.10603067, 0.06945555, 0.06709188,\n",
      "       0.14151746, 0.22940731, 0.29688573, 0.30443467, 0.30570263,\n",
      "       0.30259465, 0.30772606, 0.33793728, 0.24579449, 0.17691874,\n",
      "       0.15165826, 0.12612465, 0.04534708, 0.03737207, 0.03492156,\n",
      "       0.46545822, 0.51620188, 0.51764828, 0.47719593, 0.39647115,\n",
      "       0.21359639])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 19\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.05589307, 0.11634542, 0.16762809, 0.13315076, 0.10802945,\n",
      "       0.03939898, 0.0288553 , 0.05466328, 0.05047785, 0.07266495,\n",
      "       0.06784114, 0.08702892, 0.09950193, 0.06753226, 0.06722608,\n",
      "       0.14059347, 0.22716144, 0.28835566, 0.29540994, 0.29433822,\n",
      "       0.29052331, 0.29014531, 0.32251047, 0.23340856, 0.16865715,\n",
      "       0.1481919 , 0.12188922, 0.03847206, 0.03690646, 0.03537567,\n",
      "       0.46338561, 0.5093202 , 0.50864099, 0.46639366, 0.37790932,\n",
      "       0.18987024])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 20\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.05224803, 0.11043161, 0.15632204, 0.12892663, 0.11155789,\n",
      "       0.03927427, 0.02662329, 0.05332673, 0.049695  , 0.07190041,\n",
      "       0.06687869, 0.08801697, 0.09801067, 0.06960072, 0.07121107,\n",
      "       0.13947254, 0.22652314, 0.28851363, 0.29212882, 0.29019925,\n",
      "       0.28940773, 0.28379339, 0.31725144, 0.22946941, 0.16822014,\n",
      "       0.14744748, 0.1200929 , 0.03699451, 0.03769124, 0.03794889,\n",
      "       0.46312741, 0.50718991, 0.50614642, 0.46398195, 0.37010489,\n",
      "       0.17725706])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 21\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.04721089, 0.10200817, 0.1406184 , 0.12217617, 0.10268897,\n",
      "       0.03780899, 0.02406712, 0.04946388, 0.04601306, 0.06701324,\n",
      "       0.06434153, 0.08444219, 0.09109989, 0.06985082, 0.0730619 ,\n",
      "       0.13883155, 0.22468329, 0.28209772, 0.28421621, 0.28163746,\n",
      "       0.27960645, 0.26872609, 0.30477432, 0.22154213, 0.16332466,\n",
      "       0.14616245, 0.12063293, 0.03514629, 0.03502807, 0.03895645,\n",
      "       0.46263149, 0.50192862, 0.49384361, 0.4535857 , 0.3538008 ,\n",
      "       0.1580896 ])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 22\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.04320225, 0.09544899, 0.12940475, 0.11801939, 0.09432517,\n",
      "       0.03538732, 0.02221488, 0.04610453, 0.04188621, 0.06130968,\n",
      "       0.06062459, 0.08073323, 0.08741327, 0.0684155 , 0.07481289,\n",
      "       0.13992662, 0.22128357, 0.27495016, 0.27446976, 0.27106583,\n",
      "       0.26463783, 0.24652984, 0.28787428, 0.2030292 , 0.15226921,\n",
      "       0.13993471, 0.11248267, 0.02772645, 0.03880498, 0.04224045,\n",
      "       0.46124382, 0.49535477, 0.48136542, 0.44092702, 0.3338703 ,\n",
      "       0.14209291])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 23\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.04110195, 0.09269904, 0.12341758, 0.11542856, 0.0940874 ,\n",
      "       0.03593619, 0.02178543, 0.04380024, 0.04029869, 0.05921463,\n",
      "       0.05953892, 0.08221063, 0.08616392, 0.06922534, 0.07612374,\n",
      "       0.13837303, 0.22039   , 0.27104184, 0.26899555, 0.2660533 ,\n",
      "       0.26014363, 0.23399866, 0.27496867, 0.1986021 , 0.14926156,\n",
      "       0.13794615, 0.11074752, 0.02679947, 0.03598621, 0.04273994,\n",
      "       0.45971318, 0.49081988, 0.47494099, 0.43615957, 0.32294854,\n",
      "       0.13267333])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 24\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.03827657, 0.08908257, 0.11679283, 0.11464138, 0.08740208,\n",
      "       0.03398211, 0.02138534, 0.04201101, 0.03795567, 0.05717746,\n",
      "       0.05730494, 0.0779438 , 0.08467437, 0.06848696, 0.07804454,\n",
      "       0.13738763, 0.21560066, 0.2669006 , 0.26299447, 0.2584002 ,\n",
      "       0.24680612, 0.21508108, 0.25783753, 0.18852201, 0.1423156 ,\n",
      "       0.13663591, 0.10876864, 0.02380537, 0.04297031, 0.04755586,\n",
      "       0.4587079 , 0.48585781, 0.46503957, 0.42730731, 0.30633939,\n",
      "       0.12248027])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 25\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.03551537, 0.08607698, 0.1118974 , 0.11066268, 0.08323274,\n",
      "       0.03296489, 0.02028522, 0.03980127, 0.035471  , 0.05370135,\n",
      "       0.05540673, 0.07603246, 0.08329896, 0.0698041 , 0.08158556,\n",
      "       0.13747719, 0.21620751, 0.2638043 , 0.25487158, 0.2521417 ,\n",
      "       0.23723762, 0.20091055, 0.24290116, 0.17618046, 0.13813621,\n",
      "       0.13455503, 0.10645536, 0.01974836, 0.04487759, 0.05247169,\n",
      "       0.45869643, 0.48224721, 0.45742461, 0.42039977, 0.29326524,\n",
      "       0.11467573])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 26\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.03330595, 0.08320837, 0.10737059, 0.1101098 , 0.078712  ,\n",
      "       0.031323  , 0.01959398, 0.03773085, 0.0330934 , 0.05117979,\n",
      "       0.05428057, 0.07300463, 0.08161401, 0.0685782 , 0.08294014,\n",
      "       0.13587679, 0.2140583 , 0.25977083, 0.24864211, 0.24222271,\n",
      "       0.22401931, 0.18502023, 0.21513437, 0.16499013, 0.13323596,\n",
      "       0.13152002, 0.10323932, 0.01517992, 0.04741141, 0.05302919,\n",
      "       0.45676563, 0.47761763, 0.44818531, 0.41055239, 0.27686436,\n",
      "       0.10681625])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 27\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.03171357, 0.0815117 , 0.10432222, 0.10914492, 0.07838764,\n",
      "       0.02985562, 0.01923531, 0.03650272, 0.03225668, 0.04944459,\n",
      "       0.05364623, 0.07335189, 0.08148918, 0.06899544, 0.08484492,\n",
      "       0.13754257, 0.21510268, 0.25796072, 0.24616994, 0.23934642,\n",
      "       0.22026   , 0.17663731, 0.202127  , 0.16096971, 0.13180043,\n",
      "       0.13097403, 0.10274717, 0.01477967, 0.04995451, 0.05515032,\n",
      "       0.45695327, 0.47519015, 0.44571413, 0.40666239, 0.26897536,\n",
      "       0.10168458])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 28\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.02881524, 0.0790466 , 0.10008676, 0.10636727, 0.07465508,\n",
      "       0.02867588, 0.01872343, 0.03439273, 0.0305684 , 0.0463943 ,\n",
      "       0.05230713, 0.07133535, 0.08044934, 0.06995847, 0.08744828,\n",
      "       0.13518368, 0.20992863, 0.25111318, 0.24208825, 0.23135073,\n",
      "       0.20897157, 0.16366034, 0.18500293, 0.14955944, 0.12679942,\n",
      "       0.12773363, 0.09939113, 0.0112261 , 0.05431545, 0.06341264,\n",
      "       0.4560477 , 0.46879625, 0.4350746 , 0.39231428, 0.25450839,\n",
      "       0.09380131])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 29\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.02760396, 0.07631929, 0.09647869, 0.10422569, 0.07406367,\n",
      "       0.02704036, 0.01774592, 0.03268113, 0.02914744, 0.04379887,\n",
      "       0.05048766, 0.0698058 , 0.0780699 , 0.0696415 , 0.0912475 ,\n",
      "       0.13434549, 0.2068382 , 0.24614362, 0.23471165, 0.22401041,\n",
      "       0.19760826, 0.15066658, 0.17011395, 0.13935392, 0.12373219,\n",
      "       0.12599402, 0.09627683, 0.01055917, 0.05420056, 0.0665367 ,\n",
      "       0.45499456, 0.46265992, 0.42808627, 0.38130437, 0.24147017,\n",
      "       0.08648106])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 30\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.02476477, 0.0745624 , 0.09398294, 0.10411456, 0.07242384,\n",
      "       0.0253765 , 0.01719224, 0.03064082, 0.0275383 , 0.04085978,\n",
      "       0.04881614, 0.06857162, 0.07696739, 0.06914817, 0.08522965,\n",
      "       0.13182348, 0.20402209, 0.23952931, 0.22931406, 0.21649368,\n",
      "       0.18921231, 0.13943103, 0.15232572, 0.12819294, 0.11944048,\n",
      "       0.12328918, 0.09327491, 0.00814891, 0.05263114, 0.06421864,\n",
      "       0.45311977, 0.45834407, 0.42208921, 0.37130997, 0.22713222,\n",
      "       0.0799402 ])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 31\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.02358772, 0.0716265 , 0.09075988, 0.10130034, 0.0712819 ,\n",
      "       0.02346087, 0.01607232, 0.02916546, 0.02634384, 0.03852057,\n",
      "       0.04759465, 0.06772228, 0.07564375, 0.06823813, 0.08768596,\n",
      "       0.1321675 , 0.20131491, 0.23189684, 0.22179411, 0.2073237 ,\n",
      "       0.17695533, 0.12896823, 0.13688358, 0.11505636, 0.11539123,\n",
      "       0.12017239, 0.09004911, 0.00726325, 0.05053521, 0.06384494,\n",
      "       0.45138884, 0.45293035, 0.41540739, 0.36043439, 0.21532177,\n",
      "       0.07258786])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 32\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.02256295, 0.07085556, 0.08991233, 0.10168956, 0.07175311,\n",
      "       0.02309526, 0.01605114, 0.02881883, 0.02605805, 0.03797382,\n",
      "       0.04717929, 0.0673364 , 0.07470334, 0.06836927, 0.08965162,\n",
      "       0.13062368, 0.19993975, 0.23074253, 0.22082029, 0.20625311,\n",
      "       0.1746278 , 0.12374063, 0.12838993, 0.11282722, 0.11338821,\n",
      "       0.11928493, 0.0890456 , 0.00628783, 0.05509938, 0.06844606,\n",
      "       0.45245478, 0.44990328, 0.41346995, 0.35584522, 0.21107329,\n",
      "       0.06901101])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 33\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.02142683, 0.06856927, 0.08771267, 0.10003064, 0.07037047,\n",
      "       0.02199853, 0.01573125, 0.02763867, 0.02522388, 0.0363219 ,\n",
      "       0.04608543, 0.06599639, 0.07351326, 0.06857075, 0.08650234,\n",
      "       0.12588644, 0.19499734, 0.22430609, 0.21444956, 0.19903915,\n",
      "       0.16448567, 0.11378674, 0.11372947, 0.10602465, 0.11023097,\n",
      "       0.11668785, 0.08548218, 0.005558  , 0.05456545, 0.06982771,\n",
      "       0.45085576, 0.44560072, 0.40805615, 0.34381079, 0.19925548,\n",
      "       0.06201754])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 34\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01961043, 0.06622538, 0.08566014, 0.09856702, 0.06959986,\n",
      "       0.02101149, 0.01476081, 0.02597613, 0.02368854, 0.03431389,\n",
      "       0.04384371, 0.06485692, 0.07138339, 0.06667074, 0.08337317,\n",
      "       0.1242984 , 0.18896228, 0.21350914, 0.20973348, 0.18967926,\n",
      "       0.15583572, 0.10180963, 0.09276791, 0.09905817, 0.10480456,\n",
      "       0.11312865, 0.08173988, 0.00458604, 0.05564233, 0.06716555,\n",
      "       0.4497349 , 0.43985931, 0.40133972, 0.32958007, 0.18876612,\n",
      "       0.05600315])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 35\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01930314, 0.06554322, 0.08492945, 0.09925934, 0.06950609,\n",
      "       0.02064852, 0.01481093, 0.0254926 , 0.02336016, 0.03374189,\n",
      "       0.04426811, 0.06454981, 0.07110561, 0.06690993, 0.08638268,\n",
      "       0.12596887, 0.18907719, 0.21151106, 0.2075759 , 0.18645378,\n",
      "       0.15217264, 0.09569175, 0.08642622, 0.09466392, 0.10381587,\n",
      "       0.11249994, 0.08026336, 0.00419567, 0.05870393, 0.07514209,\n",
      "       0.45085608, 0.43997678, 0.3999252 , 0.32808323, 0.18508833,\n",
      "       0.05257126])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 36\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01786811, 0.0641314 , 0.08392456, 0.09885305, 0.06901115,\n",
      "       0.02002175, 0.01468832, 0.02514061, 0.02305642, 0.03336462,\n",
      "       0.04343968, 0.06352601, 0.07040136, 0.06636473, 0.0831397 ,\n",
      "       0.12216124, 0.1837908 , 0.20692273, 0.202888  , 0.18090974,\n",
      "       0.14446266, 0.08575439, 0.07967067, 0.09056616, 0.10021243,\n",
      "       0.11035751, 0.0784859 , 0.0034589 , 0.05815318, 0.07617168,\n",
      "       0.44985565, 0.4369819 , 0.39469593, 0.31963327, 0.17724058,\n",
      "       0.04980099])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 37\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01636183, 0.06147165, 0.08093913, 0.0964783 , 0.06711895,\n",
      "       0.01893459, 0.01377964, 0.0232838 , 0.02120246, 0.03122822,\n",
      "       0.04167037, 0.0618296 , 0.06907787, 0.06499198, 0.07837418,\n",
      "       0.11999153, 0.18012318, 0.19655067, 0.19848639, 0.171487  ,\n",
      "       0.13422198, 0.07605373, 0.07115352, 0.08372817, 0.09527256,\n",
      "       0.10684462, 0.07333047, 0.00248576, 0.05517176, 0.07181363,\n",
      "       0.4470168 , 0.42845423, 0.3867381 , 0.30758008, 0.16471489,\n",
      "       0.04492977])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 38\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01575997, 0.05991078, 0.07958635, 0.09518796, 0.06673052,\n",
      "       0.01844753, 0.01313425, 0.02221129, 0.02038631, 0.03073981,\n",
      "       0.04071787, 0.06119729, 0.06744251, 0.06564068, 0.07922706,\n",
      "       0.11912363, 0.17811439, 0.19189495, 0.19165429, 0.16424869,\n",
      "       0.12582278, 0.06922952, 0.06604838, 0.07939901, 0.09334234,\n",
      "       0.10432683, 0.0704009 , 0.00195932, 0.05408799, 0.07509442,\n",
      "       0.44733906, 0.4282053 , 0.38262663, 0.30119787, 0.15801378,\n",
      "       0.04254566])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 39\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01524009, 0.05846958, 0.07860663, 0.09443836, 0.06600136,\n",
      "       0.01806597, 0.01298995, 0.02186324, 0.02004564, 0.03085881,\n",
      "       0.04025869, 0.06058258, 0.06623212, 0.06343409, 0.07552397,\n",
      "       0.11782648, 0.17532163, 0.18675559, 0.19159646, 0.15902216,\n",
      "       0.11917493, 0.06242172, 0.0621852 , 0.07688495, 0.0908845 ,\n",
      "       0.10279339, 0.06745039, 0.00139059, 0.05287479, 0.07635053,\n",
      "       0.44649442, 0.42650782, 0.3787392 , 0.29392965, 0.15033391,\n",
      "       0.04008497])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 40\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01449756, 0.05854056, 0.08058393, 0.09286634, 0.06426096,\n",
      "       0.01720574, 0.0119892 , 0.02027866, 0.01867269, 0.02914894,\n",
      "       0.03890535, 0.05919152, 0.06550588, 0.06206001, 0.06804585,\n",
      "       0.11374968, 0.1707856 , 0.17661976, 0.18454619, 0.15004865,\n",
      "       0.11029966, 0.05263961, 0.0543906 , 0.07179489, 0.08492817,\n",
      "       0.09779281, 0.06422076, 0.0008307 , 0.0478717 , 0.06942419,\n",
      "       0.4431606 , 0.41593325, 0.37099836, 0.284431  , 0.14151931,\n",
      "       0.03988375])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 41\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01359755, 0.05500191, 0.07691883, 0.09175718, 0.06327026,\n",
      "       0.0171073 , 0.01160831, 0.01956228, 0.01806799, 0.02890409,\n",
      "       0.037939  , 0.05866454, 0.06457425, 0.05945269, 0.064562  ,\n",
      "       0.11308857, 0.16963993, 0.17097289, 0.18140105, 0.14073403,\n",
      "       0.10208432, 0.04789295, 0.0510478 , 0.06911954, 0.08188883,\n",
      "       0.09685048, 0.06154661, 0.00059024, 0.04562987, 0.06812506,\n",
      "       0.44195013, 0.41439614, 0.36454722, 0.27381865, 0.13238194,\n",
      "       0.03532402])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 42\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([1.35481705e-02, 5.35096329e-02, 7.48627332e-02, 8.97002618e-02,\n",
      "       6.28801754e-02, 1.66386812e-02, 1.07818124e-02, 1.85597300e-02,\n",
      "       1.68330193e-02, 2.78991403e-02, 3.67110782e-02, 5.77715234e-02,\n",
      "       6.34432954e-02, 6.05659672e-02, 6.54671304e-02, 1.11920367e-01,\n",
      "       1.66672946e-01, 1.66632220e-01, 1.77432695e-01, 1.37036847e-01,\n",
      "       9.45369696e-02, 4.41208064e-02, 4.87986719e-02, 6.63022758e-02,\n",
      "       7.92954003e-02, 9.42076022e-02, 5.89251833e-02, 2.10010521e-04,\n",
      "       4.54728804e-02, 7.28337405e-02, 4.41328507e-01, 4.12313340e-01,\n",
      "       3.57652003e-01, 2.64165751e-01, 1.22750552e-01, 3.33687544e-02])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 43\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01296539, 0.05228414, 0.07474384, 0.08937296, 0.06204728,\n",
      "       0.01665913, 0.01061598, 0.01781825, 0.01650098, 0.02794953,\n",
      "       0.03622344, 0.05719508, 0.06318986, 0.05790905, 0.05971657,\n",
      "       0.11105946, 0.16558678, 0.16001094, 0.17211846, 0.12953906,\n",
      "       0.08461795, 0.03957834, 0.04651265, 0.06402458, 0.07604348,\n",
      "       0.09222528, 0.05749335, 0.        , 0.03640579, 0.06484715,\n",
      "       0.43824257, 0.40443049, 0.35075119, 0.25653351, 0.11457833,\n",
      "       0.03228329])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 44\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.0126944 , 0.0499281 , 0.07198461, 0.08587096, 0.06014854,\n",
      "       0.01606511, 0.00998873, 0.01675406, 0.01567531, 0.02719608,\n",
      "       0.03501193, 0.05577521, 0.06180094, 0.05573444, 0.05565469,\n",
      "       0.10710677, 0.16125618, 0.15152051, 0.16605099, 0.12073953,\n",
      "       0.07635514, 0.03521551, 0.04050802, 0.06047174, 0.07156924,\n",
      "       0.08879215, 0.05386837, 0.        , 0.03500301, 0.06228127,\n",
      "       0.43471129, 0.39904383, 0.34222325, 0.24579223, 0.10475313,\n",
      "       0.02920537])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 45\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01224157, 0.04858497, 0.07191308, 0.08483253, 0.05942403,\n",
      "       0.0157296 , 0.00957542, 0.01649528, 0.01506141, 0.02625462,\n",
      "       0.0340436 , 0.05530015, 0.0615927 , 0.05413985, 0.05129327,\n",
      "       0.10546562, 0.1600369 , 0.14891771, 0.16286907, 0.11636933,\n",
      "       0.0732682 , 0.03351586, 0.03835202, 0.05839586, 0.06986449,\n",
      "       0.08658271, 0.05225497, 0.        , 0.03126685, 0.06567629,\n",
      "       0.43354835, 0.3986954 , 0.33534104, 0.24130299, 0.09833046,\n",
      "       0.02809984])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 46\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01195306, 0.04680986, 0.06949233, 0.08279193, 0.05840083,\n",
      "       0.01552534, 0.00923367, 0.01585153, 0.01445607, 0.02634587,\n",
      "       0.03323671, 0.0550289 , 0.06119238, 0.05353283, 0.04931848,\n",
      "       0.10631186, 0.15894274, 0.14062862, 0.15569498, 0.10961475,\n",
      "       0.06786321, 0.03212706, 0.0351404 , 0.05631389, 0.06608561,\n",
      "       0.08361753, 0.05061052, 0.        , 0.02670645, 0.05919774,\n",
      "       0.43266707, 0.39165012, 0.3243056 , 0.22890061, 0.08770156,\n",
      "       0.02525831])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 47\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01178656, 0.0444794 , 0.06838454, 0.08039093, 0.05722562,\n",
      "       0.01529146, 0.00863922, 0.0145037 , 0.01372996, 0.02641506,\n",
      "       0.03171497, 0.05436081, 0.06050369, 0.05070763, 0.04696562,\n",
      "       0.10238066, 0.15466675, 0.13384726, 0.14780738, 0.10121222,\n",
      "       0.06399625, 0.03055618, 0.03247004, 0.05478253, 0.06218245,\n",
      "       0.08019542, 0.04847003, 0.        , 0.0255841 , 0.0600683 ,\n",
      "       0.42983348, 0.3871616 , 0.31554365, 0.22227834, 0.081739  ,\n",
      "       0.02371448])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 48\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01152664, 0.04324724, 0.06701258, 0.07885071, 0.05589571,\n",
      "       0.01517303, 0.00815989, 0.0139996 , 0.01350446, 0.02616811,\n",
      "       0.03060333, 0.05353281, 0.05974712, 0.04960075, 0.04256845,\n",
      "       0.10011371, 0.15215441, 0.12697502, 0.14153001, 0.09575227,\n",
      "       0.06153177, 0.02898649, 0.0301885 , 0.05253769, 0.05783329,\n",
      "       0.07776413, 0.04656305, 0.        , 0.02009509, 0.05629952,\n",
      "       0.42839115, 0.38357834, 0.30850047, 0.21535217, 0.07670876,\n",
      "       0.02233739])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 49\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01145522, 0.04143368, 0.0652448 , 0.07663032, 0.05490266,\n",
      "       0.01485061, 0.00785874, 0.0134587 , 0.01295114, 0.02520342,\n",
      "       0.02887574, 0.0529063 , 0.05893729, 0.04755064, 0.0415185 ,\n",
      "       0.10006067, 0.14923391, 0.11904292, 0.13465494, 0.08844487,\n",
      "       0.05878986, 0.02815908, 0.02614209, 0.05010057, 0.05420005,\n",
      "       0.0750732 , 0.04519467, 0.        , 0.01723459, 0.05615698,\n",
      "       0.42532482, 0.37694382, 0.30020864, 0.20379452, 0.06919745,\n",
      "       0.02026246])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 50\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01092345, 0.03935036, 0.06342127, 0.07449811, 0.05326912,\n",
      "       0.01414719, 0.00696619, 0.01214638, 0.01210992, 0.02346493,\n",
      "       0.02685846, 0.05189791, 0.05833652, 0.04505395, 0.03812012,\n",
      "       0.09814964, 0.14680336, 0.11178077, 0.12380808, 0.08464776,\n",
      "       0.05676086, 0.02701368, 0.02261347, 0.04763921, 0.0510168 ,\n",
      "       0.07182811, 0.04396625, 0.        , 0.01475812, 0.054488  ,\n",
      "       0.42366623, 0.37146279, 0.29194238, 0.19520353, 0.06050733,\n",
      "       0.01795955])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 51\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.0108026 , 0.03805753, 0.0624381 , 0.07318128, 0.05311788,\n",
      "       0.01443446, 0.00661674, 0.01200436, 0.01239418, 0.02392508,\n",
      "       0.02631551, 0.05181008, 0.05860123, 0.04499452, 0.0387957 ,\n",
      "       0.09795515, 0.14473132, 0.10754988, 0.11432097, 0.08109478,\n",
      "       0.05516538, 0.02612206, 0.02126634, 0.04606964, 0.04965749,\n",
      "       0.06904796, 0.04224915, 0.        , 0.01307095, 0.05232572,\n",
      "       0.42268599, 0.36762014, 0.28655698, 0.18900682, 0.05439882,\n",
      "       0.01638591])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 52\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01085151, 0.03652415, 0.06137839, 0.0713997 , 0.05194501,\n",
      "       0.01384698, 0.00633519, 0.01131041, 0.0119518 , 0.02336924,\n",
      "       0.02501731, 0.05068782, 0.05735736, 0.04369458, 0.03704655,\n",
      "       0.09453624, 0.14061603, 0.10116604, 0.10783096, 0.075879  ,\n",
      "       0.05312661, 0.02478609, 0.01829225, 0.04386835, 0.04815675,\n",
      "       0.06665435, 0.04090208, 0.        , 0.01201875, 0.0538645 ,\n",
      "       0.41952466, 0.3611431 , 0.2797962 , 0.18215667, 0.04869006,\n",
      "       0.01499437])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 53\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01044958, 0.03540883, 0.0601038 , 0.07017451, 0.05104387,\n",
      "       0.01355716, 0.00605384, 0.01051223, 0.01169531, 0.02300599,\n",
      "       0.02432839, 0.05086111, 0.05722679, 0.04202215, 0.03728514,\n",
      "       0.09527781, 0.13848756, 0.09655599, 0.09997629, 0.07213822,\n",
      "       0.05148499, 0.02426196, 0.01708761, 0.04230649, 0.04686555,\n",
      "       0.06451605, 0.03925925, 0.        , 0.0115409 , 0.05500162,\n",
      "       0.4185036 , 0.35841367, 0.27651737, 0.17825311, 0.04468427,\n",
      "       0.01273378])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 54\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01084727, 0.03414703, 0.05840126, 0.06836208, 0.05028144,\n",
      "       0.01322097, 0.00551871, 0.00994724, 0.01108874, 0.02220061,\n",
      "       0.02322534, 0.05044796, 0.05606766, 0.04110909, 0.03566115,\n",
      "       0.09256156, 0.13584885, 0.08985208, 0.09003241, 0.06869219,\n",
      "       0.0492838 , 0.0228034 , 0.01464543, 0.04051911, 0.04504695,\n",
      "       0.06203624, 0.03829455, 0.        , 0.01019858, 0.05189155,\n",
      "       0.41569398, 0.35252642, 0.2714513 , 0.17124436, 0.04079041,\n",
      "       0.01187292])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 55\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01069242, 0.03277903, 0.05647793, 0.06692129, 0.04996617,\n",
      "       0.01309082, 0.00521331, 0.00933906, 0.01076844, 0.02134793,\n",
      "       0.02235404, 0.05001209, 0.05560089, 0.03968622, 0.03601942,\n",
      "       0.09310827, 0.13327889, 0.08522244, 0.07908717, 0.06472996,\n",
      "       0.04757291, 0.02264247, 0.01295606, 0.03848219, 0.04378733,\n",
      "       0.05896349, 0.03704509, 0.        , 0.01097024, 0.05435552,\n",
      "       0.41336367, 0.34704014, 0.26627137, 0.16415561, 0.03791927,\n",
      "       0.01119515])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 56\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01026523, 0.0313116 , 0.05563575, 0.06604171, 0.04905284,\n",
      "       0.01273437, 0.00484276, 0.00879333, 0.01050137, 0.02106021,\n",
      "       0.02092226, 0.04974847, 0.05511915, 0.03768797, 0.03586783,\n",
      "       0.09073917, 0.12936701, 0.07886924, 0.0698602 , 0.06042218,\n",
      "       0.04554581, 0.0212273 , 0.01151571, 0.03657513, 0.04225154,\n",
      "       0.05655534, 0.03561359, 0.        , 0.01077024, 0.05414838,\n",
      "       0.41130286, 0.3426814 , 0.26104685, 0.15753438, 0.03433854,\n",
      "       0.00950712])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 57\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.00994712, 0.02948592, 0.0537456 , 0.0644692 , 0.04741407,\n",
      "       0.01246772, 0.00457658, 0.00851173, 0.0092049 , 0.01854433,\n",
      "       0.01874582, 0.04848476, 0.05417539, 0.03520335, 0.03398459,\n",
      "       0.08866833, 0.12561471, 0.06967534, 0.06311133, 0.05796605,\n",
      "       0.0438463 , 0.02010381, 0.01004295, 0.03421434, 0.04015809,\n",
      "       0.05398262, 0.03375961, 0.        , 0.00839119, 0.04843703,\n",
      "       0.40754098, 0.33646829, 0.25481375, 0.14964364, 0.02901927,\n",
      "       0.00759843])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 58\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.00986966, 0.02830764, 0.05274588, 0.06338562, 0.04639042,\n",
      "       0.01222554, 0.00428472, 0.00791689, 0.00911139, 0.01880424,\n",
      "       0.01805693, 0.04839869, 0.05347845, 0.03442219, 0.03576753,\n",
      "       0.08834577, 0.12156389, 0.06580297, 0.05214105, 0.05466722,\n",
      "       0.04160417, 0.01880471, 0.00905712, 0.03159919, 0.03787218,\n",
      "       0.05147156, 0.03154148, 0.        , 0.0093643 , 0.05433571,\n",
      "       0.40468974, 0.33382842, 0.25076358, 0.14338534, 0.02708492,\n",
      "       0.00722836])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 59\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.0104545 , 0.02799448, 0.0520982 , 0.06235465, 0.04552033,\n",
      "       0.01183826, 0.00418013, 0.0075243 , 0.00857564, 0.01760171,\n",
      "       0.01763101, 0.04765639, 0.05242253, 0.03191771, 0.03510847,\n",
      "       0.08755703, 0.11853729, 0.05998249, 0.04853179, 0.0506391 ,\n",
      "       0.04004914, 0.01861438, 0.00883799, 0.03042089, 0.03731245,\n",
      "       0.05001454, 0.03018976, 0.        , 0.0090191 , 0.0519973 ,\n",
      "       0.40216956, 0.33063981, 0.24748259, 0.14057973, 0.02525265,\n",
      "       0.00681074])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 60\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01001009, 0.02585607, 0.05049087, 0.06102943, 0.04434611,\n",
      "       0.01165916, 0.00396208, 0.00703482, 0.00818764, 0.01672898,\n",
      "       0.01621134, 0.04715284, 0.05226444, 0.03143768, 0.03464307,\n",
      "       0.08457901, 0.11467403, 0.05525804, 0.03971444, 0.04889889,\n",
      "       0.03869081, 0.01725111, 0.00794491, 0.02775209, 0.03541734,\n",
      "       0.04747798, 0.02884217, 0.        , 0.00955563, 0.05273207,\n",
      "       0.39927729, 0.32779446, 0.24184629, 0.13252553, 0.0221248 ,\n",
      "       0.0058845 ])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 61\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.00969755, 0.02522528, 0.04938453, 0.06032078, 0.04410496,\n",
      "       0.01157146, 0.00376908, 0.00649621, 0.00758472, 0.01583679,\n",
      "       0.01535968, 0.04683512, 0.0518901 , 0.03031025, 0.03492558,\n",
      "       0.08461917, 0.11284755, 0.05206621, 0.03721674, 0.04631371,\n",
      "       0.03766498, 0.01696824, 0.00753762, 0.02678255, 0.03415034,\n",
      "       0.04568809, 0.02773286, 0.        , 0.0092617 , 0.05297653,\n",
      "       0.3973341 , 0.32601981, 0.24022136, 0.13003396, 0.02055355,\n",
      "       0.00564196])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 62\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01000537, 0.02440447, 0.04903377, 0.05962985, 0.04385521,\n",
      "       0.0114548 , 0.00329431, 0.00664164, 0.00697704, 0.01549675,\n",
      "       0.01482916, 0.04649535, 0.05085334, 0.02938297, 0.03646787,\n",
      "       0.08242762, 0.10996763, 0.04914702, 0.03565513, 0.04373101,\n",
      "       0.0358499 , 0.01641796, 0.00711031, 0.02536421, 0.03348803,\n",
      "       0.04452421, 0.02605665, 0.        , 0.00984008, 0.05603555,\n",
      "       0.39541699, 0.32369167, 0.23604089, 0.12561729, 0.01962831,\n",
      "       0.00499443])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 63\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01019586, 0.02416735, 0.04865361, 0.0592566 , 0.043071  ,\n",
      "       0.01095654, 0.00305786, 0.00618833, 0.00674339, 0.01422227,\n",
      "       0.01415584, 0.04607176, 0.05024295, 0.02756839, 0.03586034,\n",
      "       0.08260183, 0.10666249, 0.04457761, 0.03469879, 0.04221783,\n",
      "       0.03506987, 0.01589646, 0.00677542, 0.02441911, 0.03217355,\n",
      "       0.04298582, 0.0249669 , 0.        , 0.0090873 , 0.05014065,\n",
      "       0.39303756, 0.32170259, 0.2330294 , 0.1217851 , 0.01827415,\n",
      "       0.00454133])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 64\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01037765, 0.02335615, 0.04800591, 0.05831047, 0.04184335,\n",
      "       0.01083804, 0.00282269, 0.00570455, 0.00610527, 0.01293975,\n",
      "       0.01333299, 0.04589894, 0.04990257, 0.02600736, 0.03716474,\n",
      "       0.08264617, 0.1038145 , 0.04141699, 0.03338452, 0.03903479,\n",
      "       0.03423824, 0.01560796, 0.0069711 , 0.02355289, 0.03146505,\n",
      "       0.0417283 , 0.02370369, 0.        , 0.00982438, 0.05308272,\n",
      "       0.39068225, 0.31931312, 0.22977865, 0.11848313, 0.01665059,\n",
      "       0.0043175 ])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 65\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01021968, 0.02264342, 0.04714875, 0.05720227, 0.04116049,\n",
      "       0.01040757, 0.00253472, 0.00533167, 0.00557052, 0.01211492,\n",
      "       0.01237725, 0.04515983, 0.04844186, 0.02487835, 0.03800122,\n",
      "       0.08022877, 0.10062441, 0.03984166, 0.03295993, 0.0375768 ,\n",
      "       0.03282573, 0.01443203, 0.00707757, 0.02227285, 0.03003782,\n",
      "       0.04040535, 0.02181961, 0.        , 0.01041052, 0.05570613,\n",
      "       0.38728201, 0.31716177, 0.22573607, 0.11396304, 0.01602584,\n",
      "       0.00414049])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 66\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.0101917 , 0.02301383, 0.04766082, 0.05755661, 0.04134077,\n",
      "       0.01059144, 0.00250833, 0.00536778, 0.00548017, 0.01200428,\n",
      "       0.01217927, 0.04554654, 0.04867805, 0.02445176, 0.04019446,\n",
      "       0.08141179, 0.10010053, 0.03819697, 0.03297719, 0.03541936,\n",
      "       0.03202432, 0.01468993, 0.00785858, 0.02189286, 0.02961546,\n",
      "       0.03978124, 0.02141176, 0.        , 0.0120318 , 0.06010557,\n",
      "       0.3885362 , 0.31876999, 0.22506941, 0.11324319, 0.01543292,\n",
      "       0.00392344])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 67\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.0101318 , 0.02209275, 0.04660573, 0.05664045, 0.039975  ,\n",
      "       0.01007241, 0.00216544, 0.00516089, 0.00498578, 0.01050128,\n",
      "       0.01185431, 0.04505796, 0.0477302 , 0.02332552, 0.04007297,\n",
      "       0.07925914, 0.09685329, 0.03526796, 0.03265686, 0.034202  ,\n",
      "       0.03148321, 0.01430772, 0.00779335, 0.02151227, 0.02878671,\n",
      "       0.0387667 , 0.02044634, 0.        , 0.01252866, 0.05770759,\n",
      "       0.38490332, 0.31591952, 0.22118276, 0.10902193, 0.01431063,\n",
      "       0.00345678])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 68\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.0105047 , 0.02242604, 0.0468306 , 0.05662766, 0.03991942,\n",
      "       0.01007042, 0.00195571, 0.00500614, 0.00479256, 0.0104373 ,\n",
      "       0.01167194, 0.04503447, 0.04720387, 0.02378435, 0.04453617,\n",
      "       0.08142958, 0.09633253, 0.03683153, 0.0337483 , 0.03341633,\n",
      "       0.03124155, 0.01447817, 0.00868777, 0.02152781, 0.02859606,\n",
      "       0.03842505, 0.01992975, 0.        , 0.01622949, 0.06647364,\n",
      "       0.38596275, 0.31594095, 0.21950292, 0.10828863, 0.01366151,\n",
      "       0.00337516])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 69\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.0101613 , 0.02179912, 0.04534033, 0.05518291, 0.03849993,\n",
      "       0.00955737, 0.0016738 , 0.00486844, 0.00400512, 0.00935806,\n",
      "       0.01081749, 0.04430059, 0.04588728, 0.02193663, 0.04363903,\n",
      "       0.07842024, 0.09279089, 0.03301168, 0.0334087 , 0.03111242,\n",
      "       0.03068422, 0.01387927, 0.0092241 , 0.02047206, 0.0283874 ,\n",
      "       0.03754473, 0.01811114, 0.        , 0.01561429, 0.06269587,\n",
      "       0.38160335, 0.31282988, 0.21548676, 0.10442849, 0.01308163,\n",
      "       0.00321273])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 70\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01002643, 0.02176691, 0.04547337, 0.05515948, 0.03827063,\n",
      "       0.00929095, 0.00156959, 0.00467488, 0.00354205, 0.00885728,\n",
      "       0.01056314, 0.04362366, 0.04524941, 0.02179237, 0.04582377,\n",
      "       0.07762419, 0.09132681, 0.03182084, 0.03393378, 0.02951648,\n",
      "       0.02966832, 0.01357017, 0.0097282 , 0.02007735, 0.02712673,\n",
      "       0.03659246, 0.0175508 , 0.        , 0.01902373, 0.06652267,\n",
      "       0.3818402 , 0.31242227, 0.21383857, 0.1021149 , 0.01206887,\n",
      "       0.00270307])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 71\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.00997044, 0.02185121, 0.04521432, 0.05476204, 0.03767863,\n",
      "       0.00916841, 0.00130642, 0.00439714, 0.00342011, 0.00845737,\n",
      "       0.01023047, 0.04341188, 0.04438189, 0.02114712, 0.04589198,\n",
      "       0.07810584, 0.0894381 , 0.03032692, 0.03500622, 0.02967858,\n",
      "       0.02973295, 0.01320301, 0.00970645, 0.01974708, 0.02736304,\n",
      "       0.03670795, 0.01666332, 0.        , 0.01989969, 0.06473692,\n",
      "       0.3804643 , 0.31291087, 0.21323511, 0.10146446, 0.01170149,\n",
      "       0.00253612])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 72\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01029325, 0.02190345, 0.04492389, 0.05428858, 0.0369971 ,\n",
      "       0.0087512 , 0.00110648, 0.00402644, 0.00314605, 0.00811123,\n",
      "       0.00982393, 0.04295568, 0.04339662, 0.02088845, 0.0506717 ,\n",
      "       0.08343355, 0.08999494, 0.03235118, 0.03610118, 0.02942611,\n",
      "       0.02911222, 0.0133004 , 0.01007774, 0.0192077 , 0.0279904 ,\n",
      "       0.03684025, 0.0160012 , 0.        , 0.02518169, 0.07328871,\n",
      "       0.38243237, 0.3143979 , 0.21243596, 0.10147238, 0.01112066,\n",
      "       0.00242055])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 73\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01031726, 0.02184496, 0.04451911, 0.0533874 , 0.03589189,\n",
      "       0.00860723, 0.00089613, 0.00410923, 0.00290103, 0.00714874,\n",
      "       0.0098674 , 0.04255678, 0.04229562, 0.02024743, 0.05529254,\n",
      "       0.08876046, 0.08778343, 0.03112898, 0.03862702, 0.02917399,\n",
      "       0.02936396, 0.01357209, 0.0120087 , 0.01893414, 0.0287538 ,\n",
      "       0.03674773, 0.01418911, 0.        , 0.02905172, 0.077229  ,\n",
      "       0.38158713, 0.31226884, 0.2099032 , 0.09907904, 0.01124433,\n",
      "       0.00245703])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 74\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01077183, 0.02174172, 0.04353382, 0.05221414, 0.03517633,\n",
      "       0.00821872, 0.00061792, 0.00385007, 0.0027842 , 0.00664913,\n",
      "       0.00941169, 0.04183303, 0.04075761, 0.01980209, 0.06604073,\n",
      "       0.09901821, 0.08625408, 0.03303166, 0.04065913, 0.0276443 ,\n",
      "       0.02904076, 0.01324687, 0.01378089, 0.01896872, 0.02976714,\n",
      "       0.03786454, 0.01303432, 0.        , 0.03252284, 0.08062336,\n",
      "       0.38150229, 0.3128741 , 0.20965466, 0.09758192, 0.01107273,\n",
      "       0.00239702])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 75\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01013816, 0.02160568, 0.04318024, 0.05166455, 0.03399399,\n",
      "       0.00767328, 0.00045339, 0.00376228, 0.00240624, 0.00619056,\n",
      "       0.00910048, 0.04130008, 0.04021592, 0.01931331, 0.07038603,\n",
      "       0.10281587, 0.08624363, 0.03262437, 0.04454881, 0.02901793,\n",
      "       0.02885015, 0.01305653, 0.01445123, 0.01798687, 0.03068485,\n",
      "       0.03754286, 0.01220648, 0.        , 0.03522643, 0.08040591,\n",
      "       0.38043876, 0.31153756, 0.20901282, 0.09599867, 0.0106615 ,\n",
      "       0.00212647])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 76\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01074492, 0.02170835, 0.04279536, 0.05104284, 0.03325572,\n",
      "       0.00755159, 0.00041653, 0.00354011, 0.00232135, 0.00581143,\n",
      "       0.00906124, 0.04117161, 0.03949561, 0.01829545, 0.08143027,\n",
      "       0.11945213, 0.08774689, 0.03592217, 0.05254864, 0.03151313,\n",
      "       0.02936606, 0.01334234, 0.01779029, 0.0184105 , 0.0332077 ,\n",
      "       0.03894233, 0.01132653, 0.        , 0.04045168, 0.08603651,\n",
      "       0.38421056, 0.31437753, 0.21228302, 0.09668628, 0.01087829,\n",
      "       0.00242804])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 77\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([1.07461928e-02, 2.15970475e-02, 4.22059131e-02, 5.01491822e-02,\n",
      "       3.27032467e-02, 6.93729028e-03, 2.02087378e-04, 3.14987835e-03,\n",
      "       2.10923042e-03, 5.39535629e-03, 8.74886455e-03, 4.00846105e-02,\n",
      "       3.80426715e-02, 1.78833623e-02, 9.08561519e-02, 1.30861913e-01,\n",
      "       8.78520590e-02, 3.81994869e-02, 5.97102513e-02, 3.49359819e-02,\n",
      "       3.00665742e-02, 1.31227314e-02, 1.96600436e-02, 1.77697654e-02,\n",
      "       3.43796417e-02, 3.88462743e-02, 9.79995497e-03, 0.00000000e+00,\n",
      "       4.60566102e-02, 9.15741371e-02, 3.86147085e-01, 3.16443622e-01,\n",
      "       2.14810346e-01, 9.60779246e-02, 1.06233433e-02, 2.57285351e-03])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 78\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([1.09167934e-02, 2.21427888e-02, 4.16083037e-02, 4.94850585e-02,\n",
      "       3.16562255e-02, 6.69884567e-03, 1.07594253e-04, 3.05348883e-03,\n",
      "       2.01323594e-03, 5.34674890e-03, 1.00014399e-02, 3.98907861e-02,\n",
      "       3.73928573e-02, 2.01830290e-02, 1.01097739e-01, 1.48362858e-01,\n",
      "       9.03991382e-02, 4.40279691e-02, 6.72178865e-02, 4.01486852e-02,\n",
      "       3.13882456e-02, 1.41613778e-02, 2.34823015e-02, 1.86328184e-02,\n",
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      "    leadtime  int64 79\n",
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      "    leadtime  int64 80\n",
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      "    leadtime  int64 81\n",
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      "    leadtime  int64 82\n",
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      "    leadtime  int64 83\n",
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      "    leadtime  int64 84\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
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      "    leadtime  int64 85\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
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      "    leadtime  int64 86\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
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      "    leadtime  int64 87\n",
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      "    leadtime  int64 88\n",
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      "       0.42418378, 0.16633035, 0.17546952, 0.14871389, 0.09027484,\n",
      "       0.04558896, 0.0428706 , 0.06035592, 0.02411696, 0.06149164,\n",
      "       0.05434063, 0.00357728, 0.00315805, 0.12098441, 0.26817927,\n",
      "       0.49134883, 0.39935494, 0.28338739, 0.13505351, 0.04004217,\n",
      "       0.01020039])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 89\n",
      "<xarray.DataArray 'sic_0' (lon_bins: 36)>\n",
      "array([0.01359974, 0.02303925, 0.03546891, 0.06273814, 0.0264594 ,\n",
      "       0.01028507, 0.        , 0.00220451, 0.0021772 , 0.00349712,\n",
      "       0.01514741, 0.03582471, 0.02705119, 0.06153308, 0.29207265,\n",
      "       0.47401127, 0.18565272, 0.19399131, 0.17090695, 0.09455729,\n",
      "       0.04713814, 0.04806998, 0.06317882, 0.02479159, 0.0653184 ,\n",
      "       0.05536418, 0.00388755, 0.00495329, 0.1322305 , 0.30146673,\n",
      "       0.50961331, 0.40825134, 0.28833036, 0.1429314 , 0.04447903,\n",
      "       0.01113974])\n",
      "Coordinates:\n",
      "  * lon_bins  (lon_bins) object (0.0, 10.0] (10.0, 20.0] ... (350.0, 360.0]\n",
      "    leadtime  int64 90\n"
     ]
    }
   ],
   "source": [
    "sea_ice_area_binned = np.asarray([xarr.isel(leadtime=day-1)[f\"sic_{0}\"].map_blocks(compute_sea_ice_area_binned) for day in xarr.leadtime])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask.array as da\n",
    "\n",
    "sea_ice_area_binned = np.asarray([da.map_blocks(compute_sea_ice_area_binned, xarr_chunk[f\"sic_{0}\"], dtype=xarr_chunk[f\"sic_{0}\"].dtype).compute() for day in xarr.leadtime])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
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       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sic_0&#x27; (time: 1, yc: 432, xc: 432)&gt;\n",
       "dask.array&lt;getitem, shape=(1, 432, 432), dtype=float64, chunksize=(1, 432, 432), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * time      (time) datetime64[ns] 2022-12-01\n",
       "    leadtime  int64 1\n",
       "  * xc        (xc) float64 -5.388e+03 -5.362e+03 ... 5.362e+03 5.388e+03\n",
       "  * yc        (yc) float64 5.388e+03 5.362e+03 ... -5.362e+03 -5.388e+03\n",
       "    lat       (yc, xc) float32 dask.array&lt;chunksize=(432, 432), meta=np.ndarray&gt;\n",
       "    lon       (yc, xc) float32 dask.array&lt;chunksize=(432, 432), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sic_0'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>yc</span>: 432</li><li><span class='xr-has-index'>xc</span>: 432</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5ad87170-7184-4d87-8c4c-7b4e37fa5857' class='xr-array-in' type='checkbox' checked><label for='section-5ad87170-7184-4d87-8c4c-7b4e37fa5857' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 432, 432), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.42 MiB </td>\n",
       "                        <td> 1.42 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1, 432, 432) </td>\n",
       "                        <td> (1, 432, 432) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"194\" height=\"184\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">1</text>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-be960bb1-162c-4c30-a52d-704ea4d7eb4a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-be960bb1-162c-4c30-a52d-704ea4d7eb4a' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-12-01</div><input id='attrs-94da6340-88d3-470b-b84f-37160eae1079' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94da6340-88d3-470b-b84f-37160eae1079' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61247b3b-3f15-4520-ad1e-45b3c8b99c88' class='xr-var-data-in' type='checkbox'><label for='data-61247b3b-3f15-4520-ad1e-45b3c8b99c88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-12-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>leadtime</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-764053f4-b70b-49ec-a1a2-b3b75d9fe465' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-764053f4-b70b-49ec-a1a2-b3b75d9fe465' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0bc1f25-64bd-4f11-9604-f05581c9be3b' class='xr-var-data-in' type='checkbox'><label for='data-a0bc1f25-64bd-4f11-9604-f05581c9be3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xc</span></div><div class='xr-var-dims'>(xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.388e+03 -5.362e+03 ... 5.388e+03</div><input id='attrs-60cb9fd4-6e33-4759-adef-785b23acc56a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60cb9fd4-6e33-4759-adef-785b23acc56a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-645c0e8c-dec1-450c-872a-00428007da68' class='xr-var-data-in' type='checkbox'><label for='data-645c0e8c-dec1-450c-872a-00428007da68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-5387.5, -5362.5, -5337.5, ...,  5337.5,  5362.5,  5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yc</span></div><div class='xr-var-dims'>(yc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.388e+03 5.362e+03 ... -5.388e+03</div><input id='attrs-e33d2132-712d-4cb1-849f-76200b40ea22' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e33d2132-712d-4cb1-849f-76200b40ea22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3c72b83-a694-4814-9b10-ac972f5490cd' class='xr-var-data-in' type='checkbox'><label for='data-b3c72b83-a694-4814-9b10-ac972f5490cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 5387.5,  5362.5,  5337.5, ..., -5337.5, -5362.5, -5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(432, 432), meta=np.ndarray&gt;</div><input id='attrs-b4c289c1-ffac-4b0f-aeee-d64a410133e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b4c289c1-ffac-4b0f-aeee-d64a410133e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50fa3941-c640-4521-aff0-20d65b5bb5c6' class='xr-var-data-in' type='checkbox'><label for='data-50fa3941-c640-4521-aff0-20d65b5bb5c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 729.00 kiB </td>\n",
       "                        <td> 729.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (432, 432) </td>\n",
       "                        <td> (432, 432) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(432, 432), meta=np.ndarray&gt;</div><input id='attrs-5292704c-62e2-4a99-805a-7ac25bcc9478' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5292704c-62e2-4a99-805a-7ac25bcc9478' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47cc84a3-7d28-4ed0-9cc2-002fa317c5ba' class='xr-var-data-in' type='checkbox'><label for='data-47cc84a3-7d28-4ed0-9cc2-002fa317c5ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    <tr>\n",
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       "                        <td> 729.00 kiB </td>\n",
       "                        <td> 729.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
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       "                        <td> (432, 432) </td>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</svg>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-d99f7d73-8e7a-4c9f-ab7a-d5194bc74004' class='xr-section-summary-in' type='checkbox'  ><label for='section-d99f7d73-8e7a-4c9f-ab7a-d5194bc74004' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b21863f1-73a4-4531-ba50-4d5b49100d2b' class='xr-index-data-in' type='checkbox'/><label for='index-b21863f1-73a4-4531-ba50-4d5b49100d2b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-12-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>xc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48583cfb-d67c-41e7-8034-fa8e521070e6' class='xr-index-data-in' type='checkbox'/><label for='index-48583cfb-d67c-41e7-8034-fa8e521070e6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-5387.5, -5362.5, -5337.5, -5312.5, -5287.5, -5262.5, -5237.5,\n",
       "              -5212.5, -5187.5, -5162.5,\n",
       "              ...\n",
       "               5162.5,  5187.5,  5212.5,  5237.5,  5262.5,  5287.5,  5312.5,\n",
       "               5337.5,  5362.5,  5387.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;xc&#x27;, length=432))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-94e7925c-0d1f-4b49-821d-bb9fac0b30b1' class='xr-index-data-in' type='checkbox'/><label for='index-94e7925c-0d1f-4b49-821d-bb9fac0b30b1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 5387.5,  5362.5,  5337.5,  5312.5,  5287.5,  5262.5,  5237.5,\n",
       "               5212.5,  5187.5,  5162.5,\n",
       "              ...\n",
       "              -5162.5, -5187.5, -5212.5, -5237.5, -5262.5, -5287.5, -5312.5,\n",
       "              -5337.5, -5362.5, -5387.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;yc&#x27;, length=432))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-190bb4a4-aa2e-474a-8059-7602b654c6f0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-190bb4a4-aa2e-474a-8059-7602b654c6f0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sic_0' (time: 1, yc: 432, xc: 432)>\n",
       "dask.array<getitem, shape=(1, 432, 432), dtype=float64, chunksize=(1, 432, 432), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * time      (time) datetime64[ns] 2022-12-01\n",
       "    leadtime  int64 1\n",
       "  * xc        (xc) float64 -5.388e+03 -5.362e+03 ... 5.362e+03 5.388e+03\n",
       "  * yc        (yc) float64 5.388e+03 5.362e+03 ... -5.362e+03 -5.388e+03\n",
       "    lat       (yc, xc) float32 dask.array<chunksize=(432, 432), meta=np.ndarray>\n",
       "    lon       (yc, xc) float32 dask.array<chunksize=(432, 432), meta=np.ndarray>"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xarr_chunk[f\"sic_{0}\"][:, :, :, 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                 (time: 1, yc: 432, xc: 432, leadtime: 90,\n",
       "                             forecast_date: 90)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2022-12-01\n",
       "  * leadtime                (leadtime) int64 1 2 3 4 5 6 7 ... 85 86 87 88 89 90\n",
       "  * forecast_date           (forecast_date) datetime64[ns] 2022-12-02 ... 202...\n",
       "  * xc                      (xc) float64 -5.388e+03 -5.362e+03 ... 5.388e+03\n",
       "  * yc                      (yc) float64 5.388e+03 5.362e+03 ... -5.388e+03\n",
       "    lat                     (yc, xc) float32 -16.62 -16.82 ... -16.82 -16.62\n",
       "    lon                     (yc, xc) float32 315.0 315.1 315.3 ... 135.1 135.0\n",
       "Data variables: (12/14)\n",
       "    Lambert_Azimuthal_Grid  int32 -2147483647\n",
       "    sic_mean                (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    sic_stddev              (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    ensemble_members        (time) int64 10\n",
       "    sic_0                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_1                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    ...                      ...\n",
       "    sic_4                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_5                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_6                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_7                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_8                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_9                   (time, yc, xc, leadtime) float64 nan nan ... nan nan</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-25c9b8a1-e425-4b3b-8369-c18055b933d2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-25c9b8a1-e425-4b3b-8369-c18055b933d2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>yc</span>: 432</li><li><span class='xr-has-index'>xc</span>: 432</li><li><span class='xr-has-index'>leadtime</span>: 90</li><li><span class='xr-has-index'>forecast_date</span>: 90</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-46df23c0-c463-4c3b-9fbd-ddd9df6f95a6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-46df23c0-c463-4c3b-9fbd-ddd9df6f95a6' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-12-01</div><input id='attrs-e11bc6bd-beb3-4004-b938-833e223bf7da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e11bc6bd-beb3-4004-b938-833e223bf7da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5357ebc-b39b-43ea-8c61-356f4845bea7' class='xr-var-data-in' type='checkbox'><label for='data-c5357ebc-b39b-43ea-8c61-356f4845bea7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-12-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>leadtime</span></div><div class='xr-var-dims'>(leadtime)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 85 86 87 88 89 90</div><input id='attrs-4a34ae56-405a-43d3-bb80-4eaa8111bc42' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a34ae56-405a-43d3-bb80-4eaa8111bc42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e427f701-95a0-4bac-9ed0-0ac2f9c1b3c4' class='xr-var-data-in' type='checkbox'><label for='data-e427f701-95a0-4bac-9ed0-0ac2f9c1b3c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,\n",
       "       55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,\n",
       "       73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>forecast_date</span></div><div class='xr-var-dims'>(forecast_date)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-12-02 ... 2023-03-01</div><input id='attrs-067442a3-96d9-415a-825e-925ce7d4afcd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-067442a3-96d9-415a-825e-925ce7d4afcd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-887e2f3e-f0c5-4345-a98c-a6cfb3897dde' class='xr-var-data-in' type='checkbox'><label for='data-887e2f3e-f0c5-4345-a98c-a6cfb3897dde' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-12-02T00:00:00.000000000&#x27;, &#x27;2022-12-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-04T00:00:00.000000000&#x27;, &#x27;2022-12-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-06T00:00:00.000000000&#x27;, &#x27;2022-12-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-08T00:00:00.000000000&#x27;, &#x27;2022-12-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-10T00:00:00.000000000&#x27;, &#x27;2022-12-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-12T00:00:00.000000000&#x27;, &#x27;2022-12-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-14T00:00:00.000000000&#x27;, &#x27;2022-12-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-16T00:00:00.000000000&#x27;, &#x27;2022-12-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-18T00:00:00.000000000&#x27;, &#x27;2022-12-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-20T00:00:00.000000000&#x27;, &#x27;2022-12-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-22T00:00:00.000000000&#x27;, &#x27;2022-12-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-24T00:00:00.000000000&#x27;, &#x27;2022-12-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-26T00:00:00.000000000&#x27;, &#x27;2022-12-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-28T00:00:00.000000000&#x27;, &#x27;2022-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-30T00:00:00.000000000&#x27;, &#x27;2022-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-01T00:00:00.000000000&#x27;, &#x27;2023-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-03T00:00:00.000000000&#x27;, &#x27;2023-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-05T00:00:00.000000000&#x27;, &#x27;2023-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-07T00:00:00.000000000&#x27;, &#x27;2023-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-09T00:00:00.000000000&#x27;, &#x27;2023-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-11T00:00:00.000000000&#x27;, &#x27;2023-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-13T00:00:00.000000000&#x27;, &#x27;2023-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-15T00:00:00.000000000&#x27;, &#x27;2023-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-17T00:00:00.000000000&#x27;, &#x27;2023-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-19T00:00:00.000000000&#x27;, &#x27;2023-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-21T00:00:00.000000000&#x27;, &#x27;2023-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-23T00:00:00.000000000&#x27;, &#x27;2023-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-25T00:00:00.000000000&#x27;, &#x27;2023-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-27T00:00:00.000000000&#x27;, &#x27;2023-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-29T00:00:00.000000000&#x27;, &#x27;2023-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-31T00:00:00.000000000&#x27;, &#x27;2023-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-02T00:00:00.000000000&#x27;, &#x27;2023-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-04T00:00:00.000000000&#x27;, &#x27;2023-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-06T00:00:00.000000000&#x27;, &#x27;2023-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-08T00:00:00.000000000&#x27;, &#x27;2023-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-10T00:00:00.000000000&#x27;, &#x27;2023-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-12T00:00:00.000000000&#x27;, &#x27;2023-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-14T00:00:00.000000000&#x27;, &#x27;2023-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-16T00:00:00.000000000&#x27;, &#x27;2023-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-18T00:00:00.000000000&#x27;, &#x27;2023-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-20T00:00:00.000000000&#x27;, &#x27;2023-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-22T00:00:00.000000000&#x27;, &#x27;2023-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-24T00:00:00.000000000&#x27;, &#x27;2023-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-26T00:00:00.000000000&#x27;, &#x27;2023-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-02-28T00:00:00.000000000&#x27;, &#x27;2023-03-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xc</span></div><div class='xr-var-dims'>(xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.388e+03 -5.362e+03 ... 5.388e+03</div><input id='attrs-ccfb6a93-b6ef-4ede-b025-a5f7cc5db2c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ccfb6a93-b6ef-4ede-b025-a5f7cc5db2c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46d6be6a-627b-4a4e-a5af-f0e32d99dbf4' class='xr-var-data-in' type='checkbox'><label for='data-46d6be6a-627b-4a4e-a5af-f0e32d99dbf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-5387.5, -5362.5, -5337.5, ...,  5337.5,  5362.5,  5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yc</span></div><div class='xr-var-dims'>(yc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.388e+03 5.362e+03 ... -5.388e+03</div><input id='attrs-e6cb8186-a766-44e0-a964-0603d2c1ac4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6cb8186-a766-44e0-a964-0603d2c1ac4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38a30b3d-42c6-4687-9ffc-918e52a68ef1' class='xr-var-data-in' type='checkbox'><label for='data-38a30b3d-42c6-4687-9ffc-918e52a68ef1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 5387.5,  5362.5,  5337.5, ..., -5337.5, -5362.5, -5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-16.62 -16.82 ... -16.82 -16.62</div><input id='attrs-115e9a2f-b569-47ff-913b-0996abdc27c5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-115e9a2f-b569-47ff-913b-0996abdc27c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d97bc94c-852f-41c8-be1a-7d02e5484400' class='xr-var-data-in' type='checkbox'><label for='data-d97bc94c-852f-41c8-be1a-7d02e5484400' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-16.623926, -16.822655, -17.020658, ..., -17.020658, -16.822655,\n",
       "        -16.623926],\n",
       "       [-16.822655, -17.021584, -17.219795, ..., -17.219795, -17.021584,\n",
       "        -16.822655],\n",
       "       [-17.020658, -17.219795, -17.418213, ..., -17.418213, -17.219795,\n",
       "        -17.020658],\n",
       "       ...,\n",
       "       [-17.020658, -17.219795, -17.418213, ..., -17.418213, -17.219795,\n",
       "        -17.020658],\n",
       "       [-16.822655, -17.021584, -17.219795, ..., -17.219795, -17.021584,\n",
       "        -16.822655],\n",
       "       [-16.623926, -16.822655, -17.020658, ..., -17.020658, -16.822655,\n",
       "        -16.623926]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>315.0 315.1 315.3 ... 135.1 135.0</div><input id='attrs-7a699419-554f-4d6d-a2b8-36b38e5bd1d7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7a699419-554f-4d6d-a2b8-36b38e5bd1d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1635475-1db3-4df7-9631-c0ffc1e0f129' class='xr-var-data-in' type='checkbox'><label for='data-a1635475-1db3-4df7-9631-c0ffc1e0f129' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[315.      , 315.13324 , 315.26712 , ...,  44.732887,  44.866753,\n",
       "         45.      ],\n",
       "       [314.86676 , 315.      , 315.13388 , ...,  44.86613 ,  45.      ,\n",
       "         45.133247],\n",
       "       [314.73288 , 314.86612 , 315.      , ...,  45.      ,  45.13387 ,\n",
       "         45.267113],\n",
       "       ...,\n",
       "       [225.2671  , 225.13387 , 225.      , ..., 135.      , 134.86613 ,\n",
       "        134.7329  ],\n",
       "       [225.13324 , 225.      , 224.86613 , ..., 135.13387 , 135.      ,\n",
       "        134.86676 ],\n",
       "       [225.      , 224.86676 , 224.7329  , ..., 135.2671  , 135.13324 ,\n",
       "        135.      ]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c51672b-9afc-4a3a-a48c-41eeecfdb8b4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7c51672b-9afc-4a3a-a48c-41eeecfdb8b4' class='xr-section-summary' >Data variables: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Azimuthal_Grid</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-2147483647</div><input id='attrs-818db371-0451-443a-90b1-e3782adbe727' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-818db371-0451-443a-90b1-e3782adbe727' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5aaec583-e436-4cf4-851a-35db49c51a89' class='xr-var-data-in' type='checkbox'><label for='data-5aaec583-e436-4cf4-851a-35db49c51a89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_mean</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8e6a8750-3a74-405a-b1d1-ab7012892b8b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e6a8750-3a74-405a-b1d1-ab7012892b8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8364297b-4083-466d-a5b5-7ee15550863b' class='xr-var-data-in' type='checkbox'><label for='data-8364297b-4083-466d-a5b5-7ee15550863b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_stddev</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e7e1cb09-42c2-4cee-8e09-73cdc6e4c737' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7e1cb09-42c2-4cee-8e09-73cdc6e4c737' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f58fba81-61b9-4932-9763-3a9353f4ff8b' class='xr-var-data-in' type='checkbox'><label for='data-f58fba81-61b9-4932-9763-3a9353f4ff8b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "        [[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "         ...,\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan],\n",
       "         [nan, nan, nan, ..., nan, nan, nan]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_members</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10</div><input id='attrs-bf0501e7-2995-4beb-ace8-a7aec0fdd99f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf0501e7-2995-4beb-ace8-a7aec0fdd99f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-904c7a84-1fb1-4cb7-921b-652cd3e23ba2' class='xr-var-data-in' type='checkbox'><label for='data-904c7a84-1fb1-4cb7-921b-652cd3e23ba2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_0</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a83c10d4-67fe-4453-a62d-542d52b189b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a83c10d4-67fe-4453-a62d-542d52b189b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b239daa-f7bd-4e76-aedb-b16644ae82cf' class='xr-var-data-in' type='checkbox'><label for='data-3b239daa-f7bd-4e76-aedb-b16644ae82cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.43546271, 0.37026793, 0.38513866, ..., 0.20089132,\n",
       "          0.22477475, 0.29234824],\n",
       "         [0.34813896, 0.21314788, 0.29871118, ..., 0.085154  ,\n",
       "          0.11338163, 0.16429025],\n",
       "         [0.22015163, 0.1430112 , 0.19584388, ..., 0.03289658,\n",
       "          0.05897863, 0.08072057],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_1</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-59f84d6b-e9ba-4f9d-babb-502e5628be95' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59f84d6b-e9ba-4f9d-babb-502e5628be95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e990e916-e509-4f07-aeeb-978da1991d91' class='xr-var-data-in' type='checkbox'><label for='data-e990e916-e509-4f07-aeeb-978da1991d91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.27981219, 0.20967744, 0.28286988, ..., 0.33187747,\n",
       "          0.38675809, 0.38616663],\n",
       "         [0.15031554, 0.08483678, 0.12239245, ..., 0.28936812,\n",
       "          0.33306465, 0.36288041],\n",
       "         [0.09304503, 0.05237206, 0.08056372, ..., 0.25192571,\n",
       "          0.29161525, 0.32653633],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_2</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-28b7b58f-6fe4-4110-8bd3-8cf069316ae8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28b7b58f-6fe4-4110-8bd3-8cf069316ae8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38258a03-dd15-411d-a6a2-a094e0e39b87' class='xr-var-data-in' type='checkbox'><label for='data-38258a03-dd15-411d-a6a2-a094e0e39b87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "...\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[1.42367184e-01, 1.71970531e-01, 2.10496888e-01, ...,\n",
       "          1.73464596e-01, 1.96219593e-01, 1.56793818e-01],\n",
       "         [7.95661937e-03, 1.33165047e-02, 3.89877260e-02, ...,\n",
       "          7.06684813e-02, 8.52031112e-02, 8.54360610e-02],\n",
       "         [4.56487201e-03, 9.09389369e-03, 2.64396686e-02, ...,\n",
       "          4.74817008e-02, 6.29124641e-02, 7.47558698e-02],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_3</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b96b5754-7456-4f77-bcb3-b0a1fc5123e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b96b5754-7456-4f77-bcb3-b0a1fc5123e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be76961a-7f35-49e6-8b57-de4fcade1ab0' class='xr-var-data-in' type='checkbox'><label for='data-be76961a-7f35-49e6-8b57-de4fcade1ab0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.17986992, 0.21535903, 0.33764455, ..., 0.07805378,\n",
       "          0.06725815, 0.10163599],\n",
       "         [0.08526587, 0.13014406, 0.19338752, ..., 0.01391541,\n",
       "          0.0088136 , 0.02054477],\n",
       "         [0.08408061, 0.15394139, 0.19280891, ..., 0.00511451,\n",
       "          0.00418384, 0.00732684],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_4</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c6a3ee43-0347-4e95-a9df-095fc77fd7e5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c6a3ee43-0347-4e95-a9df-095fc77fd7e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9100ba7-c357-471e-a48d-fdb8c07ee14d' class='xr-var-data-in' type='checkbox'><label for='data-f9100ba7-c357-471e-a48d-fdb8c07ee14d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.31426087, 0.29592282, 0.27920938, ..., 0.26806128,\n",
       "          0.28302735, 0.29121372],\n",
       "         [0.19278514, 0.15577853, 0.14676079, ..., 0.20317332,\n",
       "          0.15370034, 0.19881955],\n",
       "         [0.12911101, 0.101769  , 0.08995824, ..., 0.13751206,\n",
       "          0.12890065, 0.18146357],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_5</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-71e904fe-c236-4873-80ff-1e843ac15869' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-71e904fe-c236-4873-80ff-1e843ac15869' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afbb1ad6-ff41-4478-b51c-01a0dedae8f0' class='xr-var-data-in' type='checkbox'><label for='data-afbb1ad6-ff41-4478-b51c-01a0dedae8f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "...\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[2.46456698e-01, 2.35801056e-01, 2.66234815e-01, ...,\n",
       "          1.56594694e-01, 1.50486544e-01, 1.98674217e-01],\n",
       "         [1.15394250e-01, 1.02601603e-01, 1.23624563e-01, ...,\n",
       "          5.22547774e-02, 6.75010681e-02, 8.19411576e-02],\n",
       "         [5.91113493e-02, 7.05489814e-02, 8.60279724e-02, ...,\n",
       "          2.22039726e-02, 2.69966591e-02, 3.62032540e-02],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_6</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6c30150f-4893-449a-a1d3-aff46d65acb3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c30150f-4893-449a-a1d3-aff46d65acb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52bf1be0-870f-468e-b648-5c04e7e53e78' class='xr-var-data-in' type='checkbox'><label for='data-52bf1be0-870f-468e-b648-5c04e7e53e78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.1449472 , 0.13899584, 0.10194253, ..., 0.29294634,\n",
       "          0.24550755, 0.38018867],\n",
       "         [0.13430873, 0.109274  , 0.05767117, ..., 0.13798775,\n",
       "          0.11910193, 0.19426842],\n",
       "         [0.14191654, 0.11193305, 0.06901318, ..., 0.1086472 ,\n",
       "          0.0787862 , 0.15395975],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_7</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-11e5d441-4560-442a-bbc7-e6725f30dede' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11e5d441-4560-442a-bbc7-e6725f30dede' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e25a752-0de3-412f-9432-ba2f8cf227e7' class='xr-var-data-in' type='checkbox'><label for='data-9e25a752-0de3-412f-9432-ba2f8cf227e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.15513363, 0.16686362, 0.19195944, ..., 0.13384481,\n",
       "          0.17087106, 0.11655044],\n",
       "         [0.04392734, 0.0482244 , 0.05548367, ..., 0.03709038,\n",
       "          0.06600705, 0.05891169],\n",
       "         [0.02791904, 0.02877719, 0.04118795, ..., 0.03086862,\n",
       "          0.0520237 , 0.05165823],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_8</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9e9be905-f166-4c4c-ac73-2d59aedd51db' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9e9be905-f166-4c4c-ac73-2d59aedd51db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64552b00-f3af-431c-a6c5-39fd739d551e' class='xr-var-data-in' type='checkbox'><label for='data-64552b00-f3af-431c-a6c5-39fd739d551e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "...\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]],\n",
       "\n",
       "        [[0.39364347, 0.43082312, 0.4546288 , ..., 0.20071581,\n",
       "          0.24593955, 0.2685419 ],\n",
       "         [0.39204255, 0.40901262, 0.39442235, ..., 0.08475831,\n",
       "          0.07902467, 0.0975676 ],\n",
       "         [0.42609054, 0.43259823, 0.41768476, ..., 0.05672323,\n",
       "          0.05133029, 0.06806187],\n",
       "         ...,\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan],\n",
       "         [       nan,        nan,        nan, ...,        nan,\n",
       "                 nan,        nan]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sic_9</span></div><div class='xr-var-dims'>(time, yc, xc, leadtime)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-92e5cf3c-9758-49b3-be6b-e561d43bd1a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-92e5cf3c-9758-49b3-be6b-e561d43bd1a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35955dd1-5219-4187-b50a-3d7d1c588969' class='xr-var-data-in' type='checkbox'><label for='data-35955dd1-5219-4187-b50a-3d7d1c588969' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "...\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]],\n",
       "\n",
       "        [[1.53539345e-01, 1.29758850e-01, 1.35938406e-01, ...,\n",
       "          2.07688555e-01, 1.29885882e-01, 2.10862756e-01],\n",
       "         [3.00696529e-02, 2.07671747e-02, 1.41037237e-02, ...,\n",
       "          5.39371110e-02, 4.55609709e-02, 9.63426828e-02],\n",
       "         [1.55482385e-02, 1.10586667e-02, 6.26199320e-03, ...,\n",
       "          4.71276678e-02, 6.30130172e-02, 1.08140334e-01],\n",
       "         ...,\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan],\n",
       "         [           nan,            nan,            nan, ...,\n",
       "                     nan,            nan,            nan]]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5aa1a843-27fa-4505-976d-a53fd5220815' class='xr-section-summary-in' type='checkbox'  ><label for='section-5aa1a843-27fa-4505-976d-a53fd5220815' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9ecb1d70-7fdf-4b80-bfd8-9355d8b846a8' class='xr-index-data-in' type='checkbox'/><label for='index-9ecb1d70-7fdf-4b80-bfd8-9355d8b846a8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-12-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>leadtime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2d6a6c7c-3d58-4b7d-92d7-1b6aecde4a8e' class='xr-index-data-in' type='checkbox'/><label for='index-2d6a6c7c-3d58-4b7d-92d7-1b6aecde4a8e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "            18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,\n",
       "            35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,\n",
       "            52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68,\n",
       "            69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,\n",
       "            86, 87, 88, 89, 90],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;leadtime&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>forecast_date</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c5661819-b8f6-457b-aeea-8e386796e7bd' class='xr-index-data-in' type='checkbox'/><label for='index-c5661819-b8f6-457b-aeea-8e386796e7bd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-12-02&#x27;, &#x27;2022-12-03&#x27;, &#x27;2022-12-04&#x27;, &#x27;2022-12-05&#x27;,\n",
       "               &#x27;2022-12-06&#x27;, &#x27;2022-12-07&#x27;, &#x27;2022-12-08&#x27;, &#x27;2022-12-09&#x27;,\n",
       "               &#x27;2022-12-10&#x27;, &#x27;2022-12-11&#x27;, &#x27;2022-12-12&#x27;, &#x27;2022-12-13&#x27;,\n",
       "               &#x27;2022-12-14&#x27;, &#x27;2022-12-15&#x27;, &#x27;2022-12-16&#x27;, &#x27;2022-12-17&#x27;,\n",
       "               &#x27;2022-12-18&#x27;, &#x27;2022-12-19&#x27;, &#x27;2022-12-20&#x27;, &#x27;2022-12-21&#x27;,\n",
       "               &#x27;2022-12-22&#x27;, &#x27;2022-12-23&#x27;, &#x27;2022-12-24&#x27;, &#x27;2022-12-25&#x27;,\n",
       "               &#x27;2022-12-26&#x27;, &#x27;2022-12-27&#x27;, &#x27;2022-12-28&#x27;, &#x27;2022-12-29&#x27;,\n",
       "               &#x27;2022-12-30&#x27;, &#x27;2022-12-31&#x27;, &#x27;2023-01-01&#x27;, &#x27;2023-01-02&#x27;,\n",
       "               &#x27;2023-01-03&#x27;, &#x27;2023-01-04&#x27;, &#x27;2023-01-05&#x27;, &#x27;2023-01-06&#x27;,\n",
       "               &#x27;2023-01-07&#x27;, &#x27;2023-01-08&#x27;, &#x27;2023-01-09&#x27;, &#x27;2023-01-10&#x27;,\n",
       "               &#x27;2023-01-11&#x27;, &#x27;2023-01-12&#x27;, &#x27;2023-01-13&#x27;, &#x27;2023-01-14&#x27;,\n",
       "               &#x27;2023-01-15&#x27;, &#x27;2023-01-16&#x27;, &#x27;2023-01-17&#x27;, &#x27;2023-01-18&#x27;,\n",
       "               &#x27;2023-01-19&#x27;, &#x27;2023-01-20&#x27;, &#x27;2023-01-21&#x27;, &#x27;2023-01-22&#x27;,\n",
       "               &#x27;2023-01-23&#x27;, &#x27;2023-01-24&#x27;, &#x27;2023-01-25&#x27;, &#x27;2023-01-26&#x27;,\n",
       "               &#x27;2023-01-27&#x27;, &#x27;2023-01-28&#x27;, &#x27;2023-01-29&#x27;, &#x27;2023-01-30&#x27;,\n",
       "               &#x27;2023-01-31&#x27;, &#x27;2023-02-01&#x27;, &#x27;2023-02-02&#x27;, &#x27;2023-02-03&#x27;,\n",
       "               &#x27;2023-02-04&#x27;, &#x27;2023-02-05&#x27;, &#x27;2023-02-06&#x27;, &#x27;2023-02-07&#x27;,\n",
       "               &#x27;2023-02-08&#x27;, &#x27;2023-02-09&#x27;, &#x27;2023-02-10&#x27;, &#x27;2023-02-11&#x27;,\n",
       "               &#x27;2023-02-12&#x27;, &#x27;2023-02-13&#x27;, &#x27;2023-02-14&#x27;, &#x27;2023-02-15&#x27;,\n",
       "               &#x27;2023-02-16&#x27;, &#x27;2023-02-17&#x27;, &#x27;2023-02-18&#x27;, &#x27;2023-02-19&#x27;,\n",
       "               &#x27;2023-02-20&#x27;, &#x27;2023-02-21&#x27;, &#x27;2023-02-22&#x27;, &#x27;2023-02-23&#x27;,\n",
       "               &#x27;2023-02-24&#x27;, &#x27;2023-02-25&#x27;, &#x27;2023-02-26&#x27;, &#x27;2023-02-27&#x27;,\n",
       "               &#x27;2023-02-28&#x27;, &#x27;2023-03-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;forecast_date&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>xc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b7bcf88e-cb88-414d-bee1-33bcd694731c' class='xr-index-data-in' type='checkbox'/><label for='index-b7bcf88e-cb88-414d-bee1-33bcd694731c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-5387.5, -5362.5, -5337.5, -5312.5, -5287.5, -5262.5, -5237.5,\n",
       "              -5212.5, -5187.5, -5162.5,\n",
       "              ...\n",
       "               5162.5,  5187.5,  5212.5,  5237.5,  5262.5,  5287.5,  5312.5,\n",
       "               5337.5,  5362.5,  5387.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;xc&#x27;, length=432))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-406ae0c1-678b-432b-95b9-580372110fa8' class='xr-index-data-in' type='checkbox'/><label for='index-406ae0c1-678b-432b-95b9-580372110fa8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 5387.5,  5362.5,  5337.5,  5312.5,  5287.5,  5262.5,  5237.5,\n",
       "               5212.5,  5187.5,  5162.5,\n",
       "              ...\n",
       "              -5162.5, -5187.5, -5212.5, -5237.5, -5262.5, -5287.5, -5312.5,\n",
       "              -5337.5, -5362.5, -5387.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;yc&#x27;, length=432))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-98227ebf-9fde-4858-b374-d027486fd9a2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-98227ebf-9fde-4858-b374-d027486fd9a2' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                 (time: 1, yc: 432, xc: 432, leadtime: 90,\n",
       "                             forecast_date: 90)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2022-12-01\n",
       "  * leadtime                (leadtime) int64 1 2 3 4 5 6 7 ... 85 86 87 88 89 90\n",
       "  * forecast_date           (forecast_date) datetime64[ns] 2022-12-02 ... 202...\n",
       "  * xc                      (xc) float64 -5.388e+03 -5.362e+03 ... 5.388e+03\n",
       "  * yc                      (yc) float64 5.388e+03 5.362e+03 ... -5.388e+03\n",
       "    lat                     (yc, xc) float32 -16.62 -16.82 ... -16.82 -16.62\n",
       "    lon                     (yc, xc) float32 315.0 315.1 315.3 ... 135.1 135.0\n",
       "Data variables: (12/14)\n",
       "    Lambert_Azimuthal_Grid  int32 -2147483647\n",
       "    sic_mean                (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    sic_stddev              (time, yc, xc, leadtime) float32 nan nan ... nan nan\n",
       "    ensemble_members        (time) int64 10\n",
       "    sic_0                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_1                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    ...                      ...\n",
       "    sic_4                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_5                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_6                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_7                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_8                   (time, yc, xc, leadtime) float64 nan nan ... nan nan\n",
       "    sic_9                   (time, yc, xc, leadtime) float64 nan nan ... nan nan"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xarr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'DataArrayGroupBy' object has no attribute 'chunk'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[141], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mxarr\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msic_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[38;5;241;43m0\u001b[39;49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43misel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mleadtime\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroupby_bins\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlon\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlongitude_bin\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchunk\u001b[49m({\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mleadtime\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m5\u001b[39m})\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'DataArrayGroupBy' object has no attribute 'chunk'"
     ]
    }
   ],
   "source": [
    "xarr[f\"sic_{0}\"].isel(leadtime=0).groupby_bins(\"lon\", longitude_bin).chunk({\"leadtime\": 5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "# longitude_bin = xr.DataArray(np.linspace(0, 360, 36+1))\n",
    "# sia_bin = xarr[f\"sic_{0}\"].groupby_bins(\"lon\", longitude_bin).map(\n",
    "#                             sic_compute,\n",
    "#                             # keep_attrs=True,\n",
    "#                         )\n",
    "\n",
    "import dask.array as da\n",
    "\n",
    "sea_ice_area_binned = np.asarray([da.map_blocks(compute_sea_ice_area_binned, xarr_chunk[f\"sic_{0}\"].isel(leadtime=day-1), dtype=xarr_chunk[f\"sic_{0}\"].dtype) for day in xarr.leadtime])\n",
    "\n",
    "# sea_ice_area_binned.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(90, 36)"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_ice_area_binned.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[nan]\n",
      "  [nan]\n",
      "  [nan]\n",
      "  ...\n",
      "  [nan]\n",
      "  [nan]\n",
      "  [nan]]\n",
      "\n",
      " [[nan]\n",
      "  [nan]\n",
      "  [nan]\n",
      "  ...\n",
      "  [nan]\n",
      "  [nan]\n",
      "  [nan]]\n",
      "\n",
      " [[nan]\n",
      "  [nan]\n",
      "  [nan]\n",
      "  ...\n",
      "  [nan]\n",
      "  [nan]\n",
      "  [nan]]\n",
      "\n",
      " ...\n",
      "\n",
      " [[nan]\n",
      "  [nan]\n",
      "  [nan]\n",
      "  ...\n",
      "  [nan]\n",
      "  [nan]\n",
      "  [nan]]\n",
      "\n",
      " [[nan]\n",
      "  [nan]\n",
      "  [nan]\n",
      "  ...\n",
      "  [nan]\n",
      "  [nan]\n",
      "  [nan]]\n",
      "\n",
      " [[nan]\n",
      "  [nan]\n",
      "  [nan]\n",
      "  ...\n",
      "  [nan]\n",
      "  [nan]\n",
      "  [nan]]]\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "applied function returned data with unexpected number of dimensions. Received 0 dimension(s) but expected 1 dimensions with names: ('stacked_yc_xc',)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[172], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m longitude_bin \u001b[38;5;241m=\u001b[39m xr\u001b[38;5;241m.\u001b[39mDataArray(np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m360\u001b[39m, \u001b[38;5;241m36\u001b[39m\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m))\n\u001b[0;32m----> 2\u001b[0m sea_ice_area_binned \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_ufunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43msic_compute_np\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43mxarr\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msic_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[38;5;241;43m0\u001b[39;49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroupby_bins\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlon\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlongitude_bin\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43minput_core_dims\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mleadtime\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtime\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m                                    \u001b[49m\u001b[38;5;66;43;03m#  output_core_dims=[[]],\u001b[39;49;00m\n\u001b[1;32m      6\u001b[0m \u001b[43m                                    \u001b[49m\u001b[38;5;66;43;03m#  exclude_dims=set([\"time\", \"stacked_yc_xc\"]),\u001b[39;49;00m\n\u001b[1;32m      7\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43mdask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mparallelized\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43moutput_dtypes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      9\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43mdask_gufunc_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[43m                                         \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43moutput_sizes\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msia\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m36\u001b[39;49m\u001b[43m}\u001b[49m\n\u001b[1;32m     11\u001b[0m \u001b[43m                                        \u001b[49m\u001b[43m}\u001b[49m\n\u001b[1;32m     12\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     13\u001b[0m sea_ice_area_binned\u001b[38;5;241m.\u001b[39mcompute()\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/xarray/core/computation.py:1193\u001b[0m, in \u001b[0;36mapply_ufunc\u001b[0;34m(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, meta, dask_gufunc_kwargs, *args)\u001b[0m\n\u001b[1;32m   1177\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(a, GroupBy) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args):\n\u001b[1;32m   1178\u001b[0m     this_apply \u001b[38;5;241m=\u001b[39m functools\u001b[38;5;241m.\u001b[39mpartial(\n\u001b[1;32m   1179\u001b[0m         apply_ufunc,\n\u001b[1;32m   1180\u001b[0m         func,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1191\u001b[0m         dask_gufunc_kwargs\u001b[38;5;241m=\u001b[39mdask_gufunc_kwargs,\n\u001b[1;32m   1192\u001b[0m     )\n\u001b[0;32m-> 1193\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mapply_groupby_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mthis_apply\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1194\u001b[0m \u001b[38;5;66;03m# feed datasets apply_variable_ufunc through apply_dataset_vfunc\u001b[39;00m\n\u001b[1;32m   1195\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28many\u001b[39m(is_dict_like(a) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args):\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/xarray/core/computation.py:557\u001b[0m, in \u001b[0;36mapply_groupby_func\u001b[0;34m(func, *args)\u001b[0m\n\u001b[1;32m    554\u001b[0m     iterators\u001b[38;5;241m.\u001b[39mappend(iterator)\n\u001b[1;32m    556\u001b[0m applied \u001b[38;5;241m=\u001b[39m (func(\u001b[38;5;241m*\u001b[39mzipped_args) \u001b[38;5;28;01mfor\u001b[39;00m zipped_args \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39miterators))\n\u001b[0;32m--> 557\u001b[0m applied_example, applied \u001b[38;5;241m=\u001b[39m \u001b[43mpeek_at\u001b[49m\u001b[43m(\u001b[49m\u001b[43mapplied\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    558\u001b[0m combine \u001b[38;5;241m=\u001b[39m first_groupby\u001b[38;5;241m.\u001b[39m_combine\n\u001b[1;32m    559\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(applied_example, \u001b[38;5;28mtuple\u001b[39m):\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/xarray/core/utils.py:186\u001b[0m, in \u001b[0;36mpeek_at\u001b[0;34m(iterable)\u001b[0m\n\u001b[1;32m    182\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns the first value from iterable, as well as a new iterator with\u001b[39;00m\n\u001b[1;32m    183\u001b[0m \u001b[38;5;124;03mthe same content as the original iterable\u001b[39;00m\n\u001b[1;32m    184\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    185\u001b[0m gen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28miter\u001b[39m(iterable)\n\u001b[0;32m--> 186\u001b[0m peek \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mnext\u001b[39m(gen)\n\u001b[1;32m    187\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m peek, itertools\u001b[38;5;241m.\u001b[39mchain([peek], gen)\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/xarray/core/computation.py:556\u001b[0m, in \u001b[0;36m<genexpr>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    553\u001b[0m         iterator \u001b[38;5;241m=\u001b[39m itertools\u001b[38;5;241m.\u001b[39mrepeat(arg)\n\u001b[1;32m    554\u001b[0m     iterators\u001b[38;5;241m.\u001b[39mappend(iterator)\n\u001b[0;32m--> 556\u001b[0m applied \u001b[38;5;241m=\u001b[39m (\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mzipped_args\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m zipped_args \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39miterators))\n\u001b[1;32m    557\u001b[0m applied_example, applied \u001b[38;5;241m=\u001b[39m peek_at(applied)\n\u001b[1;32m    558\u001b[0m combine \u001b[38;5;241m=\u001b[39m first_groupby\u001b[38;5;241m.\u001b[39m_combine\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/xarray/core/computation.py:1208\u001b[0m, in \u001b[0;36mapply_ufunc\u001b[0;34m(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, meta, dask_gufunc_kwargs, *args)\u001b[0m\n\u001b[1;32m   1206\u001b[0m \u001b[38;5;66;03m# feed DataArray apply_variable_ufunc through apply_dataarray_vfunc\u001b[39;00m\n\u001b[1;32m   1207\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(a, DataArray) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args):\n\u001b[0;32m-> 1208\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mapply_dataarray_vfunc\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1209\u001b[0m \u001b[43m        \u001b[49m\u001b[43mvariables_vfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1210\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1211\u001b[0m \u001b[43m        \u001b[49m\u001b[43msignature\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msignature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1212\u001b[0m \u001b[43m        \u001b[49m\u001b[43mjoin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1213\u001b[0m \u001b[43m        \u001b[49m\u001b[43mexclude_dims\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexclude_dims\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1214\u001b[0m \u001b[43m        \u001b[49m\u001b[43mkeep_attrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeep_attrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1215\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1216\u001b[0m \u001b[38;5;66;03m# feed Variables directly through apply_variable_ufunc\u001b[39;00m\n\u001b[1;32m   1217\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(a, Variable) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args):\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/xarray/core/computation.py:315\u001b[0m, in \u001b[0;36mapply_dataarray_vfunc\u001b[0;34m(func, signature, join, exclude_dims, keep_attrs, *args)\u001b[0m\n\u001b[1;32m    310\u001b[0m result_coords, result_indexes \u001b[38;5;241m=\u001b[39m build_output_coords_and_indexes(\n\u001b[1;32m    311\u001b[0m     args, signature, exclude_dims, combine_attrs\u001b[38;5;241m=\u001b[39mkeep_attrs\n\u001b[1;32m    312\u001b[0m )\n\u001b[1;32m    314\u001b[0m data_vars \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mgetattr\u001b[39m(a, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvariable\u001b[39m\u001b[38;5;124m\"\u001b[39m, a) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args]\n\u001b[0;32m--> 315\u001b[0m result_var \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdata_vars\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    317\u001b[0m out: \u001b[38;5;28mtuple\u001b[39m[DataArray, \u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m] \u001b[38;5;241m|\u001b[39m DataArray\n\u001b[1;32m    318\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m signature\u001b[38;5;241m.\u001b[39mnum_outputs \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/xarray/core/computation.py:796\u001b[0m, in \u001b[0;36mapply_variable_ufunc\u001b[0;34m(func, signature, exclude_dims, dask, output_dtypes, vectorize, keep_attrs, dask_gufunc_kwargs, *args)\u001b[0m\n\u001b[1;32m    794\u001b[0m data \u001b[38;5;241m=\u001b[39m as_compatible_data(data)\n\u001b[1;32m    795\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mlen\u001b[39m(dims):\n\u001b[0;32m--> 796\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    797\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapplied function returned data with unexpected \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    798\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnumber of dimensions. Received \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata\u001b[38;5;241m.\u001b[39mndim\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m dimension(s) but \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    799\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mexpected \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlen\u001b[39m(dims)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m dimensions with names: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdims\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    800\u001b[0m     )\n\u001b[1;32m    802\u001b[0m var \u001b[38;5;241m=\u001b[39m Variable(dims, data, fastpath\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m    803\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m dim, new_size \u001b[38;5;129;01min\u001b[39;00m var\u001b[38;5;241m.\u001b[39msizes\u001b[38;5;241m.\u001b[39mitems():\n",
      "\u001b[0;31mValueError\u001b[0m: applied function returned data with unexpected number of dimensions. Received 0 dimension(s) but expected 1 dimensions with names: ('stacked_yc_xc',)"
     ]
    }
   ],
   "source": [
    "longitude_bin = xr.DataArray(np.linspace(0, 360, 36+1))\n",
    "sea_ice_area_binned = xr.apply_ufunc(sic_compute_np,\n",
    "                                     xarr[f\"sic_{0}\"].groupby_bins(\"lon\", longitude_bin),\n",
    "                                     input_core_dims=[[\"leadtime\", \"time\"]],\n",
    "                                    #  output_core_dims=[[]],\n",
    "                                    #  exclude_dims=set([\"time\", \"stacked_yc_xc\"]),\n",
    "                                     dask=\"parallelized\",\n",
    "                                     output_dtypes=[float],\n",
    "                                     dask_gufunc_kwargs={\n",
    "                                         \"output_sizes\": {\"sia\": 36}\n",
    "                                        }\n",
    "                                     )\n",
    "sea_ice_area_binned.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.ndarray'>\n"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'numpy.ndarray' object has no attribute 'groupby_bins'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[134], line 8\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m da\u001b[38;5;241m.\u001b[39mapply_along_axis(func, arr\u001b[38;5;241m=\u001b[39marr, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m)\n\u001b[1;32m      6\u001b[0m \u001b[38;5;66;03m# da.map_blocks(compute_sea_ice_area_binned, xarr_chunk[f\"sic_{0}\"], dtype=xarr_chunk[f\"sic_{0}\"].dtype).compute()\u001b[39;00m\n\u001b[0;32m----> 8\u001b[0m \u001b[43mapply_bin_along_leadtime\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcompute_sea_ice_area_binned\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mxarr_chunk\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msic_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[38;5;241;43m0\u001b[39;49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
      "Cell \u001b[0;32mIn[134], line 4\u001b[0m, in \u001b[0;36mapply_bin_along_leadtime\u001b[0;34m(func, arr)\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply_bin_along_leadtime\u001b[39m(func, arr):\n\u001b[0;32m----> 4\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mda\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_along_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43marr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43marr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/data/hpcdata/users/bryald/miniconda3/envs/icenet/lib/python3.11/site-packages/dask/array/routines.py:506\u001b[0m, in \u001b[0;36mapply_along_axis\u001b[0;34m(func1d, axis, arr, dtype, shape, *args, **kwargs)\u001b[0m\n\u001b[1;32m    504\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m shape \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mor\u001b[39;00m dtype \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    505\u001b[0m     test_data \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mones((\u001b[38;5;241m1\u001b[39m,), dtype\u001b[38;5;241m=\u001b[39marr\u001b[38;5;241m.\u001b[39mdtype)\n\u001b[0;32m--> 506\u001b[0m     test_result \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(\u001b[43mfunc1d\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtest_data\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m    507\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m shape \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    508\u001b[0m         shape \u001b[38;5;241m=\u001b[39m test_result\u001b[38;5;241m.\u001b[39mshape\n",
      "Cell \u001b[0;32mIn[133], line 23\u001b[0m, in \u001b[0;36mcompute_sea_ice_area_binned\u001b[0;34m(sea_ice_concentration, *args, **kwargs)\u001b[0m\n\u001b[1;32m     19\u001b[0m longitude_bin \u001b[38;5;241m=\u001b[39m xr\u001b[38;5;241m.\u001b[39mDataArray(np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m360\u001b[39m, \u001b[38;5;241m36\u001b[39m\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m))\n\u001b[1;32m     21\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28mtype\u001b[39m(sic))\n\u001b[0;32m---> 23\u001b[0m sea_ice_area_binned \u001b[38;5;241m=\u001b[39m \u001b[43msic\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroupby_bins\u001b[49m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlon\u001b[39m\u001b[38;5;124m\"\u001b[39m, longitude_bin)\u001b[38;5;241m.\u001b[39mmap(sic_compute, args\u001b[38;5;241m=\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m     25\u001b[0m \u001b[38;5;28mprint\u001b[39m(sea_ice_area_binned)\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m sea_ice_area_binned\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'numpy.ndarray' object has no attribute 'groupby_bins'"
     ]
    }
   ],
   "source": [
    "import dask.array as da\n",
    "\n",
    "def apply_bin_along_leadtime(func, arr):\n",
    "    return da.apply_along_axis(func, arr=arr, axis=3)\n",
    "\n",
    "# da.map_blocks(compute_sea_ice_area_binned, xarr_chunk[f\"sic_{0}\"], dtype=xarr_chunk[f\"sic_{0}\"].dtype).compute()\n",
    "\n",
    "apply_bin_along_leadtime(compute_sea_ice_area_binned, xarr_chunk[f\"sic_{0}\"])"
   ]
  }
 ],
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