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preprocess_code.f
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preprocess_code.f
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c preprocess_code.f
c Perform a variety of preprocessing steps, like read in topography
c and vegetation arrays, open input and output files, etc.
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
SUBROUTINE PREPROCESS_CODE(topoveg_fname,const_veg_flag,
& vegtype,veg_z0,vegsnowdepth,fetch,xmu,C_z,h_const,
& wind_min,Up_const,dz_susp,ztop_susp,fall_vel,Ur_const,
& ro_water,ro_air,gravity,vonKarman,pi,twopio360,snow_z0,
& nx,ny,sum_sprec,sum_qsubl,sum_trans,sum_unload,topo,
& topo_land,snow_d,topoflag,snow_d_init,snow_d_init_const,
& soft_snow_d,met_input_fname,igrads_metfile,deltax,deltay,
& snowtran_output_fname,micromet_output_fname,
& enbal_output_fname,snowpack_output_fname,print_micromet,
& print_enbal,print_snowpack,print_snowtran,run_micromet,
& run_enbal,run_snowpack,run_snowtran,ro_snow_grid,swe_depth,
& sum_runoff,sum_prec,ro_snow,twolayer_flag,sum_Qcs,
& canopy_int,ascii_topoveg,topo_ascii_fname,icorr_factor_loop,
& veg_ascii_fname,undef,isingle_stn_flag,max_iter,
& i_tair_flag,i_rh_flag,i_wind_flag,i_prec_flag,sum_glacmelt,
& snow_depth,sum_d_canopy_int,corr_factor,icorr_factor_index,
& sum_sfcsublim,barnes_lg_domain,n_stns_used,k_stn,xmn,ymn,
& ro_soft_snow_old,sum_swemelt,xlat,lat_solar_flag,xlat_grid,
& xlon_grid,UTC_flag,dt,swe_depth_old,canopy_int_old,
& vegsnowd_xy,iveg_ht_flag,ihrestart_flag,i_dataassim_loop,
& multilayer_snowpack,max_layers,multilayer_output_fname,
& print_multilayer,JJ,tslsnowfall,tsls_threshold,
& irun_data_assim,izero_snow_date,iclear_mn,iclear_dy,
& xclear_hr,dy_snow,swe_lyr,ro_layer,T_old,gamma,icond_flag,
& curve_lg_scale_flag,curve_wt_lg,check_met_data,seaice_run,
& snowmodel_line_flag,xg_line,yg_line,print_user,albedo_flag)
implicit none
include 'snowmodel.inc'
integer i,j,k,nx,ny,igrads_metfile,n_recs_out,iheader,
& isingle_stn_flag,max_iter,i_tair_flag,i_rh_flag,i_wind_flag,
& i_prec_flag,iter,iobs_num,n_stns_used,nveg,iveg_ht_flag,
& lat_solar_flag,ihrestart_flag,nstns_orig,i_dataassim_loop,
& multilayer_snowpack,max_layers,irun_data_assim,
& izero_snow_date,iclear_mn,iclear_dy,icond_flag,albedo_flag
real ro_water,ro_air,gravity,vonKarman,snow_z0,
& fetch,xmu,C_z,h_const,wind_min,Up_const,check_met_data,
& dz_susp,ztop_susp,fall_vel,Ur_const,pi,twopio360,topoflag,
& snow_d_init_const,const_veg_flag,ro_snow,twolayer_flag,
& ascii_topoveg,undef,barnes_lg_domain,xlat,UTC_flag,dt,
& print_multilayer,xclear_hr,curve_lg_scale_flag,seaice_run,
& snowmodel_line_flag,print_user
real topo_land(nx_max,ny_max)
real topo(nx_max,ny_max)
real vegtype(nx_max,ny_max)
real xlat_grid(nx_max,ny_max)
real xlon_grid(nx_max,ny_max)
real snow_d(nx_max,ny_max)
real snow_depth(nx_max,ny_max)
real snow_d_init(nx_max,ny_max)
real canopy_int(nx_max,ny_max)
real swe_depth_old(nx_max,ny_max)
real canopy_int_old(nx_max,ny_max)
real sum_sprec(nx_max,ny_max)
real sum_qsubl(nx_max,ny_max)
real sum_trans(nx_max,ny_max)
real sum_unload(nx_max,ny_max)
real soft_snow_d(nx_max,ny_max)
real ro_soft_snow_old(nx_max,ny_max)
real ro_snow_grid(nx_max,ny_max)
real swe_depth(nx_max,ny_max)
real sum_prec(nx_max,ny_max)
real sum_runoff(nx_max,ny_max)
real sum_Qcs(nx_max,ny_max)
real sum_glacmelt(nx_max,ny_max)
real sum_swemelt(nx_max,ny_max)
real sum_d_canopy_int(nx_max,ny_max)
real sum_sfcsublim(nx_max,ny_max)
real vegsnowdepth(nvegtypes)
real veg_z0(nx_max,ny_max)
real vegsnowd_xy(nx_max,ny_max)
real curve_wt_lg(nx_max,ny_max)
real corr_factor(nx_max,ny_max,max_obs_dates+1)
integer icorr_factor_index(max_time_steps)
integer icorr_factor_loop
integer k_stn(nx_max,ny_max,5)
double precision xmn,ymn
real deltax,deltay
integer icount,iii,jjj
double precision xg_line(nx_max,ny_max),yg_line(nx_max,ny_max)
real run_micromet,run_enbal,run_snowpack,run_snowtran
real print_micromet,print_enbal,print_snowpack,print_snowtran
character*80 topoveg_fname,met_input_fname,topo_ascii_fname,
& veg_ascii_fname
character*80 snowtran_output_fname,micromet_output_fname,
& enbal_output_fname,snowpack_output_fname,
& multilayer_output_fname
integer JJ(nx_max,ny_max)
real tslsnowfall(nx_max,ny_max)
real tsls_threshold
real dy_snow(nx_max,ny_max,nz_max)
real swe_lyr(nx_max,ny_max,nz_max)
real ro_layer(nx_max,ny_max,nz_max)
real T_old(nx_max,ny_max,nz_max)
real gamma(nx_max,ny_max,nz_max)
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
c Check to see whether the maximum array dimensions defined in
c snowmodel.inc are adequate for the simulation domain defined
c in snowmodel.par.
if (snowmodel_line_flag.eq.0.0) then
if (nx+1.gt.nx_max .or. ny+1.gt.ny_max) then
print *, 'Must increase the value of nx_max or ny_max'
print *, ' in snowmodel.inc to be greater than nx+1'
print *, ' and/or ny+1.'
print *, 'nx_max = ',nx_max,' ny_max = ',ny_max
print *, 'nx = ',nx,' ny = ',ny
stop
endif
else
if (nx.ge.nx_max .or. ny.ne.1 .or. ny_max.ne.2) then
print *, 'For snowmodel_line_flag = 1.0, we suggest setting'
print *, 'nx = number of grid cells, ny = 1, nx_max = nx+1,'
print *, 'and ny_max = ny+1 = 2 in snowmodel.inc.'
print *, ' The current values are:'
print *, ' nx_max = ',nx_max,' ny_max = ',ny_max
print *, ' nx = ',nx,' ny = ',ny
stop
endif
endif
if (multilayer_snowpack.eq.1) then
if (max_layers+1.gt.nz_max) then
print *, 'nz_max in snowmodel.inc must be at least 1 greater'
print *, ' than max_layers in the snowmodel.inc file. So,'
print *, ' if you want to run the multi-layer snowpack model'
print *, ' with a single snow layer, set nz_max=2. If you'
print *, ' want to run the original single-layer snowpack'
print *, ' model, you can set nz_max=1 in snowmodel.inc.'
print *, 'nz_max = ',nz_max
print *, 'max_layers = ',max_layers
stop
endif
endif
if (max_iter.gt.max_time_steps) then
print *, 'Must increase the value of max_time_steps'
print *, ' in snowmodel.inc to be greater than max_iter.'
print *, 'max_time_steps = ',max_time_steps
print *, 'max_iter = ',max_iter
stop
endif
c If running the concatenated configuration of the model, check to
c make sure the rest of the model is configured correctly.
if (snowmodel_line_flag.eq.1.0) then
if (run_snowtran.eq.1.0) then
print *, 'You cannot run snowmodel_line_flag = 1.0 with'
print *, 'run_snowtran = 1.0'
stop
endif
if (barnes_lg_domain.eq.0.0) then
print *, 'If snowmodel_line_flag = 1.0, then you must run'
print *, 'the model with barnes_lg_domain = 1.0'
stop
endif
endif
c Make sure the time since last snowfall treshold is not less
c than the model time step.
if (multilayer_snowpack.eq.1) then
if (tsls_threshold.lt.dt/3600.0) then
print *,'Need to correct tsls_threshold to'
print *,' be >= dt (in hours).'
stop
endif
endif
c Check the model dt value, and send an error message if dt < 3600.
if (dt.lt.3600.0) then
print *, 'You must modify the hour fraction calculation'
print *, ' in get_model_time subroutine to handle'
print *, ' dt values less that 3600.0 seconds.'
print *, 'dt = ',dt
stop
endif
c Define the date on which the snow arrays will be zeroed out.
iclear_mn = izero_snow_date / 10000
iclear_dy = (izero_snow_date - iclear_mn * 10000) / 100
xclear_hr =
& real((izero_snow_date - iclear_mn * 10000) - iclear_dy * 100)
c Check to see whether there is enough snow layers to calculate
c conductive surface fluxes.
if (icond_flag.eq.1) then
if (multilayer_snowpack.eq.0 .or. max_layers.lt.2) then
print *,'If icond_flag = 1, then multilayer_snowpack = 1'
print *,' and max_layers >= 2.'
stop
endif
endif
c Read in the topography array.
if (ascii_topoveg.eq.0.0) then
open (unit=37,file=topoveg_fname,
& form='unformatted',access='direct',recl=4*nx*ny)
read (37,rec=1) ((topo_land(i,j),i=1,nx),j=1,ny)
elseif (ascii_topoveg.eq.1.0) then
c Read off the header lines. I will assume that all of this
c information was input in the .par file correctly.
open (37,file=topo_ascii_fname,form='formatted')
iheader = 6
do k=1,iheader
read (37,*)
enddo
c Read the data in as real numbers, and do the yrev.
do j=ny,1,-1
read (37,*) (topo_land(i,j),i=1,nx)
enddo
endif
c If vegetation data is not available on the topography grid,
c define the vegetation to be constant.
if (const_veg_flag.ne.0.0) then
do i=1,nx
do j=1,ny
vegtype(i,j) = const_veg_flag
enddo
enddo
c Read in the vegetation array.
else
if (ascii_topoveg.eq.0.0) then
read (37,rec=2) ((vegtype(i,j),i=1,nx),j=1,ny)
elseif (ascii_topoveg.eq.1.0) then
c Read off the header lines. I will assume that all of this
c information was input in the .par file correctly.
open (38,file=veg_ascii_fname,form='formatted')
do k=1,iheader
read (38,*)
enddo
c Read the data in as real numbers, and do the yrev.
do j=ny,1,-1
read (38,*) (vegtype(i,j),i=1,nx)
enddo
endif
endif
c Now that we have read in the topo and veg data arrays, check
c whether all of the values look like valid numbers.
do i=1,nx
do j=1,ny
if (vegtype(i,j).lt.1.0 .or. vegtype(i,j).gt.30.0) then
print *, 'Found Invalid Vegetation-Type Value'
print *, ' Value =',vegtype(i,j),' at ',i,j
stop
endif
if (topo_land(i,j).lt.0.0 .or. topo_land(i,j).gt.9000.0) then
print *, 'Found Invalid Topography Value'
print *, ' Value =',topo_land(i,j),' at ',i,j
stop
endif
enddo
enddo
c J.PFLUG
c provide the opportunity to read in snow and rain precipitation data
if (i_prec_flag.eq.-1.0) then
open (99,file='met/TUO_elev_fp.txt',
& form='formatted')
rewind(99)
endif
if (albedo_flag.eq.1.0) then
open (98,file='extra_met/albedo.dat',
& form='formatted')
rewind (98)
endif
c END J.PFLUG
c Fill the the vegetation snow-holding depth array for vegetation
c types 1 through 24 (types 25 through 30 were filled from the
c .par file.
call fill_veg_shd(nvegtypes,vegsnowdepth)
c Use vegsnowdepth to fill the 2D spatial array, or read in the
c user-provided file of the vegetation heights (in cm).
if (iveg_ht_flag.eq.-1) then
open (191,file='topo_veg/veg_ht.gdat',
& form='unformatted',access='direct',recl=4*nx*ny)
read (191,rec=1) ((vegsnowd_xy(i,j),i=1,nx),j=1,ny)
close(191)
c Convert from cm to m.
do i=1,nx
do j=1,ny
vegsnowd_xy(i,j) = vegsnowd_xy(i,j) / 100.0
enddo
enddo
elseif (iveg_ht_flag.eq.1) then
open (191,file='topo_veg/veg_ht.asc',form='formatted')
iheader = 6
do k=1,iheader
read (191,*)
enddo
c Read the data in as real numbers, and do the yrev.
do j=ny,1,-1
read (191,*) (vegsnowd_xy(i,j),i=1,nx)
enddo
close(191)
c Convert from cm to m.
do i=1,nx
do j=1,ny
vegsnowd_xy(i,j) = vegsnowd_xy(i,j) / 100.0
enddo
enddo
elseif (iveg_ht_flag.eq.0) then
do i=1,nx
do j=1,ny
nveg = nint(vegtype(i,j))
vegsnowd_xy(i,j) = vegsnowdepth(nveg)
enddo
enddo
endif
c Define the roughness lengths for each of the vegetation types.
c Note that this is pretty arbitrary, because these values are
c really only used when there is no blowing snow, and thus have
c no impact on the simulation except to provide a non-zero value
c for any such parts of the domain.
do i=1,nx
do j=1,ny
veg_z0(i,j) = 0.25 * vegsnowd_xy(i,j)
enddo
enddo
c Read in the large-scale curvature weighting array, if the run
c requires it.
if (curve_lg_scale_flag.eq.1.0) then
open (444,file='extra_met/large_curvature_wt.gdat',
& form='unformatted',access='direct',recl=4*nx*ny)
read (444,rec=1) ((curve_wt_lg(i,j),i=1,nx),j=1,ny)
close (444)
endif
c If this is a sea ice run, open the sea ice concentration file.
if (seaice_run.ne.0.0) then
open (445,file='seaice/ice_conc.gdat',
& form='unformatted',access='direct',recl=4*nx*ny)
endif
c Check to make sure that if you are running SnowTran-3D and the
c EnBal and SnowPack models, you have also set the flag to run
c the SnowTran-3D two-layer submodel.
if (run_enbal.eq.1.0 .and. run_snowpack.eq.1.0 .and.
& run_snowtran.eq.1.0) then
if (twolayer_flag.ne.1.0) then
print *, 'For SnowTran-3D with EnBal and SnowPack,'
print *, ' twolayer_flag must equal 1.0'
stop
endif
endif
c Check to see that the defined domain is large enough to be
c running SnowTran-3D.
if (run_snowtran.eq.1.0) then
if (nx.lt.3 .or. ny.lt.3) then
print *, 'To run SnowTran-3D, nx and ny must both be 3'
print *, ' or greater (see SnowTran-3D code/notes)'
stop
endif
endif
c Check to see whether the model is configured correctly to be
c running the multi-layer snow model.
if (multilayer_snowpack.eq.1) then
if (irun_data_assim.eq.1 .or. ihrestart_flag.ne.-2 .or.
& snow_d_init_const.ne.0.0) then
print *, 'The multi-layer snowpack model requires:'
print *, ' irun_data_assim = 0'
print *, ' ihrestart_flag = -2'
print *, ' snow_d_init_const = 0.0'
c stop
endif
endif
c Get a collection of constants that are not generally modified.
call constants(fetch,xmu,C_z,h_const,wind_min,Up_const,
& dz_susp,ztop_susp,fall_vel,Ur_const,ro_water,ro_air,
& gravity,vonKarman,pi,twopio360,snow_z0)
c Run a check to see if SnowTran-3D is being run with grid
c increments that are too large.
if (deltax.gt.500.0 .or. deltay.gt.500.0) then
if (run_snowtran.eq.1.0) then
print *
print *, '!!! deltax,y should not be greater than 500 m'
print *, '!!! if you are also running SnowTran-3D'
print *
stop
endif
endif
c Initialize the summing arrays, and define the initial snow-depth
c distributions.
call initialize(nx,ny,sum_sprec,sum_qsubl,sum_trans,
& sum_unload,topo,topo_land,snow_d,topoflag,snow_d_init,
& snow_d_init_const,soft_snow_d,ro_water,sum_sfcsublim,
& ro_snow_grid,swe_depth,sum_runoff,sum_prec,ro_snow,
& sum_Qcs,canopy_int,sum_glacmelt,snow_depth,sum_d_canopy_int,
& ro_soft_snow_old,sum_swemelt,swe_depth_old,canopy_int_old,
& ihrestart_flag,i_dataassim_loop,max_iter,corr_factor,
& icorr_factor_index,JJ,tslsnowfall,tsls_threshold,dy_snow,
& swe_lyr,ro_layer,T_old,gamma)
c Check to see whether the data assimilation has been configured
c correctly.
if (irun_data_assim.eq.1) then
c Check to see whether the required output files will be created.
if (print_user.ne.1.0) then
print *, 'For a data assimilation run print_user must = 1.0'
stop
endif
c Check to see whether the corr_factor array is defined to be large
c enough to do the assimilation. It looks like I can't do that
c here because I don't know the name of the swe-obs input file yet.
c Therefore I will do a check when dataassim_user.f is called. So
c in the mean time I will just print a message to the screen telling
c the user to check this.
print *
print *, 'For a DATA ASSIMILATION RUN, MAX_OBS_DATES must be'
print *, 'defined in SNOWMODEL.INC to be greater than the'
print *, 'number of observation dates in the entire simulation'
print *, '+ (plus) the number of years in the simulation. For'
print *, 'example, for a 6-year simulation with two observation'
print *, 'dates in each year, you would set max_obs_dates to be'
print *, 'at least = 18.'
print *
endif
c Initialize the precipitation factor for the first iteration to
c equal 1.0.
if (icorr_factor_loop.eq.1) then
do iobs_num=1,max_obs_dates+1
do j=1,ny
do i=1,nx
corr_factor(i,j,iobs_num) = 1.0
enddo
enddo
enddo
do iter=1,max_iter
icorr_factor_index(iter) = 1
enddo
endif
c Read or build the latitude array that will be used to do the
c latitude weighting when calculating incoming solar radiation.
if (lat_solar_flag.eq.-1) then
open (91,file='extra_met/grid_lat.gdat',
& form='unformatted',access='direct',recl=4*nx*ny)
read (91,rec=1) ((xlat_grid(i,j),i=1,nx),j=1,ny)
close(91)
elseif (lat_solar_flag.eq.1) then
open (91,file='extra_met/grid_lat.asc',form='formatted')
iheader = 6
do k=1,iheader
read (91,*)
enddo
c Read the data in as real numbers, and do the yrev.
do j=ny,1,-1
read (91,*) (xlat_grid(i,j),i=1,nx)
enddo
close(91)
elseif (lat_solar_flag.eq.0) then
c Print an error if the y-domain is big enough to have important
c solar radiation differences from south to north.
if (ny*deltay.gt.500000.0) then
print *
print *,'YOUR DOMAIN IS PRETTY BIG TO NOT ACCOUNT FOR'
print *,' SOLAR RADIATION VARIATIONS WITH LATITUDE'
print *,' see the "lat_solar_flag" in snowmodel.par'
print *
stop
endif
do i=1,nx
do j=1,ny
xlat_grid(i,j) = xlat
enddo
enddo
endif
c Read or build the lonitude array that will be used to do the
c lonitude influence when calculating incoming solar radiation.
if (UTC_flag.eq.-1.0) then
open (91,file='extra_met/grid_lon.gdat',
& form='unformatted',access='direct',recl=4*nx*ny)
read (91,rec=1) ((xlon_grid(i,j),i=1,nx),j=1,ny)
close(91)
elseif (UTC_flag.eq.1.0) then
open (91,file='extra_met/grid_lon.asc',form='formatted')
iheader = 6
do k=1,iheader
read (91,*)
enddo
c Read the data in as real numbers, and do the yrev.
do j=ny,1,-1
read (91,*) (xlon_grid(i,j),i=1,nx)
enddo
close(91)
elseif (UTC_flag.eq.0.0) then
c Print an error if the x-domain is big enough to have important
c solar radiation differences from east to west.
if (nx*deltax.gt.500000.0) then
print *
print *,'YOUR DOMAIN IS PRETTY BIG TO NOT ACCOUNT FOR'
print *,' SOLAR RADIATION VARIATIONS WITH LONITUDE'
print *,' see the "UTC_flag" in snowmodel.par'
print *
stop
endif
endif
c Open the MicroMet station data input file.
if (igrads_metfile.eq.1) then
open(20,file=met_input_fname,form='unformatted',
& access='direct',recl=4*13)
else
open (20,file=met_input_fname,form='formatted')
endif
c Run a check to see whether there are any time slices with no
c valid data.
if (check_met_data.eq.1.0) then
print *
print *,'Checking for sufficient met forcing data to'
print *,' complete the model simulation. This may'
print *,' take a while, depending on how big your met'
print *,' input file is.'
print *
call met_data_check(undef,isingle_stn_flag,igrads_metfile,
& max_iter,i_tair_flag,i_rh_flag,i_wind_flag,i_prec_flag)
endif
c If the concatenated configuration of the model is used, read
c in the x and y coordinates for the concatenated grid cells.
if (snowmodel_line_flag.eq.1.0) then
open (1331,file='extra_met/snowmodel_line_pts.dat')
do j=1,ny
do i=1,nx
read (1331,*) icount,iii,jjj,xg_line(i,j),yg_line(i,j)
enddo
enddo
close (1331)
endif
c If the large-domain barnes oi scheme is used, generate the
c nearest-station indexing array.
if (barnes_lg_domain.eq.1.0) then
print *
print *,'You are running the large-domain Barnes oi scheme'
print *,' This requires:'
print *,' 1) no missing data for the fields of interest'
print *,' 2) no missing stations during the simulation'
print *,' 3) met file must list stations in the same order'
print *,' 4) the number of nearest stations used is 5 or less'
print *,' 5) **** no error checking for this is done ****'
print *
print *,'Generating nearest-station index. Be patient.'
print *
if (n_stns_used.gt.5 .or. n_stns_used.lt.1) then
print *,'invalid n_stns_used value'
stop
endif
call get_nearest_stns_1(nx,ny,xmn,ymn,deltax,deltay,
& n_stns_used,k_stn,snowmodel_line_flag,xg_line,yg_line)
endif
c If this is a history restart run, advance the micromet input
c file to the restart time.
if (ihrestart_flag.ge.0) then
if (igrads_metfile.eq.0) then
do iter=1,ihrestart_flag
if (isingle_stn_flag.eq.1) then
nstns_orig = 1
else
read(20,*) nstns_orig
endif
do k=1,nstns_orig
read(20,*)
enddo
enddo
endif
endif
c Open the files to be used to store model output.
c For MicroMet.
if (run_micromet.eq.1.0 .and. print_micromet.eq.1.0) then
n_recs_out = 8
open (81,file=micromet_output_fname,
& form='unformatted',access='direct',recl=4*n_recs_out*nx*ny)
endif
c For EnBal.
if (run_enbal.eq.1.0 .and. print_enbal.eq.1.0) then
n_recs_out = 10
open (82,file=enbal_output_fname,
& form='unformatted',access='direct',recl=4*n_recs_out*nx*ny)
endif
c For SnowPack.
if (run_snowpack.eq.1.0 .and. print_snowpack.eq.1.0) then
n_recs_out = 16
open (83,file=snowpack_output_fname,
& form='unformatted',access='direct',recl=4*n_recs_out*nx*ny)
endif
c For SnowTran-3D.
if (run_snowtran.eq.1.0 .and. print_snowtran.eq.1.0) then
n_recs_out = 7
open (84,file=snowtran_output_fname,
& form='unformatted',access='direct',recl=4*n_recs_out*nx*ny)
endif
c For Multi-Layer SnowPack.
if (run_snowpack.eq.1.0 .and. multilayer_snowpack.eq.1 .and.
& print_multilayer.eq.1.0) then
open (85,file=multilayer_output_fname,
& form='unformatted',access='direct',
& recl=4*(4*nx*ny+6*nx*ny*nz_max))
endif
c For random precipitation error
if (irun_data_assim.eq.1.and.icorr_factor_loop.eq.1) then
open(11,file='data/randomError.txt')
endif
return
end
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
subroutine initialize(nx,ny,sum_sprec,sum_qsubl,sum_trans,
& sum_unload,topo,topo_land,snow_d,topoflag,snow_d_init,
& snow_d_init_const,soft_snow_d,ro_water,sum_sfcsublim,
& ro_snow_grid,swe_depth,sum_runoff,sum_prec,ro_snow,
& sum_Qcs,canopy_int,sum_glacmelt,snow_depth,sum_d_canopy_int,
& ro_soft_snow_old,sum_swemelt,swe_depth_old,canopy_int_old,
& ihrestart_flag,i_dataassim_loop,max_iter,corr_factor,
& icorr_factor_index,JJ,tslsnowfall,tsls_threshold,dy_snow,
& swe_lyr,ro_layer,T_old,gamma)
implicit none
include 'snowmodel.inc'
integer i,j,nx,ny,ihrestart_flag,i_dataassim_loop,max_iter,k
real topoflag,snow_d_init_const,ro_water,ro_snow
real sum_sprec(nx_max,ny_max)
real sum_qsubl(nx_max,ny_max)
real sum_trans(nx_max,ny_max)
real sum_unload(nx_max,ny_max)
real topo(nx_max,ny_max)
real topo_land(nx_max,ny_max)
real snow_d(nx_max,ny_max)
real snow_depth(nx_max,ny_max)
real soft_snow_d(nx_max,ny_max)
real ro_soft_snow_old(nx_max,ny_max)
real ro_snow_grid(nx_max,ny_max)
real swe_depth(nx_max,ny_max)
real sum_prec(nx_max,ny_max)
real sum_runoff(nx_max,ny_max)
real sum_Qcs(nx_max,ny_max)
real canopy_int(nx_max,ny_max)
real sum_glacmelt(nx_max,ny_max)
real sum_swemelt(nx_max,ny_max)
real sum_d_canopy_int(nx_max,ny_max)
real sum_sfcsublim(nx_max,ny_max)
real snow_d_init(nx_max,ny_max)
real swe_depth_old(nx_max,ny_max)
real canopy_int_old(nx_max,ny_max)
integer JJ(nx_max,ny_max)
real tslsnowfall(nx_max,ny_max)
real tsls_threshold
real dy_snow(nx_max,ny_max,nz_max)
real swe_lyr(nx_max,ny_max,nz_max)
real ro_layer(nx_max,ny_max,nz_max)
real T_old(nx_max,ny_max,nz_max)
real gamma(nx_max,ny_max,nz_max)
integer icorr_factor_index(max_time_steps)
real corr_factor(nx_max,ny_max,max_obs_dates+1)
if (ihrestart_flag.ge.0) then
c Read in the saved data.
CALL HRESTART_READ(nx,ny,snow_d,snow_depth,
& canopy_int,soft_snow_d,ro_snow_grid,swe_depth,
& ro_soft_snow_old,snow_d_init,swe_depth_old,
& canopy_int_old,topo,sum_sprec,ihrestart_flag,
& i_dataassim_loop)
if (i_dataassim_loop.lt.0.0) then
CALL HRESTART_READ_DA(nx,ny,max_iter,corr_factor,
& icorr_factor_index,i_dataassim_loop)
endif
do i=1,nx
do j=1,ny
c Fill the summing arrays.
sum_runoff(i,j) = 0.0
sum_prec(i,j) = 0.0
c sum_sprec(i,j) = 0.0
sum_qsubl(i,j) = 0.0
sum_trans(i,j) = 0.0
sum_unload(i,j) = 0.0
sum_Qcs(i,j) = 0.0
sum_glacmelt(i,j) = 0.0
sum_swemelt(i,j) = 0.0
sum_d_canopy_int(i,j) = 0.0
sum_sfcsublim(i,j) = 0.0
c Define the initial snow-depth distributions.
c snow_d_init(i,j) = snow_d_init_const
c snow_d(i,j) = snow_d_init(i,j)
c snow_depth(i,j) = snow_d_init(i,j)
c canopy_int(i,j) = 0.0
c soft_snow_d(i,j) = snow_d(i,j)
c ro_snow_grid(i,j) = ro_snow
c swe_depth(i,j) = snow_d(i,j) * ro_snow_grid(i,j) / ro_water
c ro_soft_snow_old(i,j) = 50.0
c swe_depth_old(i,j) = swe_depth(i,j)
c canopy_int_old(i,j) = canopy_int(i,j)
enddo
enddo
else
do i=1,nx
do j=1,ny
c Fill the summing arrays.
sum_runoff(i,j) = 0.0
sum_prec(i,j) = 0.0
sum_sprec(i,j) = 0.0
sum_qsubl(i,j) = 0.0
sum_trans(i,j) = 0.0
sum_unload(i,j) = 0.0
sum_Qcs(i,j) = 0.0
sum_glacmelt(i,j) = 0.0
sum_swemelt(i,j) = 0.0
sum_d_canopy_int(i,j) = 0.0
sum_sfcsublim(i,j) = 0.0
c Define the initial snow-depth distributions.
snow_d_init(i,j) = snow_d_init_const
snow_d(i,j) = snow_d_init(i,j)
snow_depth(i,j) = snow_d_init(i,j)
canopy_int(i,j) = 0.0
soft_snow_d(i,j) = snow_d(i,j)
ro_snow_grid(i,j) = ro_snow
swe_depth(i,j) = snow_d(i,j) * ro_snow_grid(i,j) / ro_water
ro_soft_snow_old(i,j) = 50.0
swe_depth_old(i,j) = swe_depth(i,j)
canopy_int_old(i,j) = canopy_int(i,j)
c Initialize the multi-layer snowpack arrays.
JJ(i,j) = 0
tslsnowfall(i,j) = tsls_threshold
enddo
enddo
do i=1,nx
do j=1,ny
do k=1,nz_max
dy_snow(i,j,k) = 0.0
swe_lyr(i,j,k) = 0.0
ro_layer(i,j,k) = ro_snow
T_old(i,j,k) = 273.16
gamma(i,j,k) = 0.138 - 1.01 * (ro_layer(i,j,k)/1000.0) +
& 3.233 * (ro_layer(i,j,k)/1000.0)**2
enddo
enddo
enddo
if (topoflag.eq.1.0) then
do i=1,nx
do j=1,ny
topo(i,j) = topo_land(i,j) + snow_d(i,j)
enddo
enddo
elseif (topoflag.eq.0.0) then
do i=1,nx
do j=1,ny
topo(i,j) = topo_land(i,j)
enddo
enddo
endif
endif
return
end
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
subroutine constants(fetch,xmu,C_z,h_const,wind_min,Up_const,
& dz_susp,ztop_susp,fall_vel,Ur_const,ro_water,ro_air,
& gravity,vonKarman,pi,twopio360,snow_z0)
implicit none
real fetch,xmu,C_z,h_const,wind_min,Up_const,
& dz_susp,ztop_susp,fall_vel,Ur_const,ro_water,ro_air,
& gravity,vonKarman,pi,twopio360,snow_z0
c These constants are not generally modified for a particular model
c run.
c Snow surface roughness length.
snow_z0 = 0.001
c Constants related to surface shear stress and saltation
c transport.
fetch = 500.0
xmu = 3.0
C_z = 0.12
h_const = 1.6
wind_min = 4.0
c Constants related to suspended snow profile.
Up_const = 2.8
dz_susp = 0.20
ztop_susp = 2.0
fall_vel = 0.3
Ur_const = 0.5
c General constants.
ro_water = 1000.0
ro_air = 1.275
gravity = 9.81
vonKarman = 0.4
pi = 2.0 * acos(0.0)
twopio360 = 2.0 * pi / 360.0
return
end
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
subroutine fill_veg_shd(nvegtypes,vegsnowdepth)
implicit none
integer k,nvegtypes,nvegtypes_fixed
parameter (nvegtypes_fixed=24)
real vegsnowdepth(nvegtypes),vegsnowdepth_fixed(nvegtypes_fixed)
c Fill the the vegetation snow-holding depth array for
c vegetation types 1 through 24 (types 25 through 30 were filled
c from the .par file.
c
c The following summary was taken from the .par file.
c
c The vegetation types are assumed to range from 1 through 30. The
c last 6 types are available to be user-defined vegetation types
c and vegetation snow-holding depth. The first 24 vegetation
c types, and the associated vegetation snow-holding depth
c (meters), are hard-coded to be:
c
c code description veg_shd example class
c
c 1 coniferous forest 15.00 spruce-fir/taiga/lodgepole forest
c 2 deciduous forest 12.00 aspen forest forest
c 3 mixed forest 14.00 aspen/spruce-fir/low taiga forest
c 4 scattered short-conifer 8.00 pinyon-juniper forest
c 5 clearcut conifer 4.00 stumps and regenerating forest
c
c 6 mesic upland shrub 0.50 deeper soils, less rocky shrub
c 7 xeric upland shrub 0.25 rocky, windblown soils shrub
c 8 playa shrubland 1.00 greasewood, saltbush shrub
c 9 shrub wetland/riparian 1.75 willow along streams shrub
c 10 erect shrub tundra 0.65 arctic shrubland shrub
c 11 low shrub tundra 0.30 low to medium arctic shrubs shrub
c
c 12 grassland rangeland 0.15 graminoids and forbs grass
c 13 subalpine meadow 0.25 meadows below treeline grass
c 14 tundra (non-tussock) 0.15 alpine, high arctic grass
c 15 tundra (tussock) 0.20 graminoid and dwarf shrubs grass
c 16 prostrate shrub tundra 0.10 graminoid dominated grass
c 17 arctic gram. wetland 0.20 grassy wetlands, wet tundra grass
c
c 18 bare 0.01 bare
c
c 19 water/possibly frozen 0.01 water
c 20 permanent snow/glacier 0.01 water
c
c 21 residential/urban 0.01 human
c 22 tall crops 0.40 e.g., corn stubble human
c 23 short crops 0.25 e.g., wheat stubble human
c 24 ocean 0.01 water
c
c 25 user defined (see below)
c 26 user defined (see below)
c 27 user defined (see below)
c 28 user defined (see below)
c 29 user defined (see below)
c 30 user defined (see below)
c
c Define the vegetation snow-holding depth (meters) for each
c of the user-defined vegetation types. The numbers in the
c list below correspond to the vegetation-type numbers in the
c vegetation-type data array (veg type 25.0 -> veg_shd_25). Note
c that even if these are not used, they cannot be commented out
c or you will get an error message.
c veg_shd_25 = 0.10
c veg_shd_26 = 0.10
c veg_shd_27 = 0.10
c veg_shd_28 = 0.10
c veg_shd_29 = 0.10
c veg_shd_30 = 0.10
data vegsnowdepth_fixed/15.00, 12.00, 14.00, 8.00, 4.00,
& 0.50, 0.25, 1.00, 1.75, 0.65, 0.30,
& 0.15, 0.25, 0.15, 0.20, 0.10, 0.20,
& 0.01, 0.01, 0.01, 0.01, 0.40, 0.25,
& 0.01/
do k=1,nvegtypes_fixed
vegsnowdepth(k) = vegsnowdepth_fixed(k)
enddo
return
end
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
subroutine met_data_check(undef,isingle_stn_flag,igrads_metfile,
& max_iter,i_tair_flag,i_rh_flag,i_wind_flag,i_prec_flag)
implicit none
include 'snowmodel.inc'
integer iyr,imo,idy ! year, month, and day of data