| 1 | #!/usr/bin/env python3 |
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| 2 | # -*- coding: utf-8 -*- |
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| 3 | |
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| 4 | #------------------------------------------------------------------------------# |
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| 5 | # |
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| 6 | # Scripts for processing of WRF and CAMx files to PALM dynamic driver |
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| 7 | # |
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| 8 | # This program is free software: you can redistribute it and/or modify |
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| 9 | # it under the terms of the GNU General Public License as published by |
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| 10 | # the Free Software Foundation, either version 3 of the License, or |
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| 11 | # (at your option) any later version. |
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| 12 | # |
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| 13 | # This program is distributed in the hope that it will be useful, |
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| 14 | # but WITHOUT ANY WARRANTY; without even the implied warranty of |
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| 15 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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| 16 | # GNU General Public License for more details. |
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| 17 | # |
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| 18 | # You should have received a copy of the GNU General Public License |
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| 19 | # along with this program. If not, see <https://www.gnu.org/licenses/>. |
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| 20 | # |
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| 21 | # Copyright 2018-2020 Institute of Computer Science |
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| 22 | # of the Czech Academy of Sciences, Prague |
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| 23 | # Authors: Krystof Eben, Jaroslav Resler, Pavel Krc |
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| 24 | # |
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| 25 | #------------------------------------------------------------------------------# |
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| 26 | ''' |
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| 27 | This file creates and writes the dynamic driver netcdf file based on preprepared |
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| 28 | transformed and interpolated wrf and camx files. |
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| 29 | ''' |
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| 30 | |
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| 31 | import os |
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| 32 | import time |
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| 33 | import numpy as np |
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| 34 | import netCDF4 |
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| 35 | from palm_wrf_utils import palm_wrf_gw |
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| 36 | |
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| 37 | |
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| 38 | def palm_dynamic_output(wrf_files, interp_files, camx_interp_fname, dynamic_driver_file, times_sec, |
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| 39 | dimensions, z_levels, z_levels_stag, ztop, |
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| 40 | z_soil_levels, dx, dy, lon_center, lat_center, |
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| 41 | rad_times_proc, rad_values_proc, sma, nested_domain): |
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| 42 | |
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| 43 | print('Processing interpolated files to dynamic driver') |
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| 44 | # dimension of the time coordinate |
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| 45 | dimtimes = len(times_sec) |
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| 46 | # other coordinates |
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| 47 | dimnames = ['z', 'zw', 'zsoil', 'x','xu', 'y', 'yv'] # z height agl in m, zw staggered, zsoil 4 lev from wrf |
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| 48 | dimsize_names = ['zdim' , 'zwdim', 'zsoildim', 'xdim', 'xudim', 'ydim', 'yvdim'] # palm: zw = z - 1 |
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| 49 | x = np.arange(dx, dimensions['xdim']*dx+dx, dx) # clean this |
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| 50 | print('dimension of x:', len(x)) |
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| 51 | y = np.arange(dy, dimensions['ydim']*dy+dy, dy) # clean this |
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| 52 | print('dimension of y:', len(y)) |
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| 53 | # fill values |
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| 54 | fillvalue_float = float(-9999.0) |
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| 55 | # check out file and remove for sure |
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| 56 | try: |
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| 57 | os.remove(dynamic_driver_file) |
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| 58 | except: |
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| 59 | pass |
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| 60 | # create netcdf out file |
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| 61 | print('Driver file:', dynamic_driver_file) |
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| 62 | outfile = netCDF4.Dataset(dynamic_driver_file, "w", format="NETCDF4" ) |
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| 63 | try: |
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| 64 | # time dimension and variable |
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| 65 | outfile.createDimension('time', dimtimes) |
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| 66 | _val_times = outfile.createVariable('time',"f4", ("time")) |
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| 67 | # other dimensions and corresponding variables |
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| 68 | for _dim in zip(dimnames, dimsize_names): #range (len(dimnames)): |
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| 69 | print(_dim[0],_dim[1], dimensions[_dim[1]]) |
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| 70 | outfile.createDimension(_dim[0], dimensions[_dim[1]]) |
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| 71 | _val_z_levels = outfile.createVariable('z',"f4", ("z")) |
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| 72 | _val_z_levels_stag = outfile.createVariable('zw',"f4", ("zw")) |
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| 73 | _val_z_soil_levels = outfile.createVariable('zsoil',"f4", ("zsoil")) |
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| 74 | _val_y = outfile.createVariable('y',"f4", ("y")) |
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| 75 | _val_x = outfile.createVariable('x',"f4", ("x")) |
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| 76 | |
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| 77 | # prepare influx/outflux area sizes |
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| 78 | zstag_all = np.r_[0., z_levels_stag, ztop] |
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| 79 | zwidths = zstag_all[1:] - zstag_all[:-1] |
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| 80 | print('zwidths', zwidths) |
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| 81 | areas_xb = np.zeros((len(z_levels), 1)) |
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| 82 | areas_xb[:,0] = zwidths * dy |
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| 83 | areas_yb = np.zeros((len(z_levels), 1)) |
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| 84 | areas_yb[:,0] = zwidths * dx |
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| 85 | areas_zb = dx*dy |
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| 86 | area_boundaries = (areas_xb.sum()*dimensions['ydim']*2 |
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| 87 | + areas_yb.sum()*dimensions['xdim']*2 |
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| 88 | + areas_zb*dimensions['xdim']*dimensions['ydim']) |
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| 89 | |
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| 90 | # write values for coordinates |
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| 91 | _val_times[:] = times_sec[:] |
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| 92 | _val_z_levels[:] = z_levels[:] |
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| 93 | _val_z_levels_stag[:] = z_levels_stag[:] |
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| 94 | _val_z_soil_levels[:] = z_soil_levels[:] |
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| 95 | _val_y[:] = y[:] |
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| 96 | _val_x[:] = x[:] |
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| 97 | |
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| 98 | # initialization of the variables and setting of init_* variables |
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| 99 | print("Processing initialization from file", interp_files[0]) |
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| 100 | # open corresponding |
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| 101 | infile = netCDF4.Dataset(interp_files[0], "r", format="NETCDF4") |
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| 102 | try: |
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| 103 | # open variables in the input file |
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| 104 | init_atmosphere_pt = infile.variables['init_atmosphere_pt'] |
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| 105 | init_atmosphere_qv = infile.variables['init_atmosphere_qv'] |
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| 106 | init_atmosphere_u = infile.variables['init_atmosphere_u'] |
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| 107 | init_atmosphere_v = infile.variables['init_atmosphere_v'] |
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| 108 | init_atmosphere_w = infile.variables['init_atmosphere_w'] |
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| 109 | init_soil_m = infile.variables['init_soil_m'] |
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| 110 | init_soil_t = infile.variables['init_soil_t'] |
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| 111 | |
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| 112 | # create netcdf structure |
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| 113 | _val_init_atmosphere_pt = outfile.createVariable('init_atmosphere_pt', "f4", ("z", "y", "x"), |
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| 114 | fill_value=fillvalue_float) |
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| 115 | _val_init_atmosphere_pt.setncattr('lod', 2) |
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| 116 | _val_init_atmosphere_qv = outfile.createVariable('init_atmosphere_qv', "f4", ("z", "y", "x"), |
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| 117 | fill_value=fillvalue_float) |
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| 118 | _val_init_atmosphere_qv.setncattr('lod', 2) |
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| 119 | _val_init_atmosphere_u = outfile.createVariable('init_atmosphere_u', "f4", ("z", "y", "xu"), |
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| 120 | fill_value=fillvalue_float) |
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| 121 | _val_init_atmosphere_u.setncattr('lod', 2) |
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| 122 | _val_init_atmosphere_v = outfile.createVariable('init_atmosphere_v', "f4", ("z", "yv", "x"), |
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| 123 | fill_value=fillvalue_float) |
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| 124 | _val_init_atmosphere_v.setncattr('lod', 2) |
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| 125 | _val_init_atmosphere_w = outfile.createVariable('init_atmosphere_w', "f4", ("zw", "y", "x"), |
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| 126 | fill_value=fillvalue_float) |
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| 127 | _val_init_atmosphere_w.setncattr('lod', 2) |
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| 128 | _val_init_soil_t = outfile.createVariable('init_soil_t', "f4", ("zsoil", "y", "x"), fill_value=fillvalue_float) |
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| 129 | _val_init_soil_t.setncattr('lod', 2) |
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| 130 | _val_init_soil_m = outfile.createVariable('init_soil_m', "f4", ("zsoil", "y", "x"), fill_value=fillvalue_float) |
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| 131 | _val_init_soil_m.setncattr('lod', 2) |
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| 132 | # time dependent variables |
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| 133 | if not nested_domain: |
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| 134 | # SURFACE PRESSURE |
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| 135 | _val_surface_forcing_surface_pressure = outfile.createVariable('surface_forcing_surface_pressure', "f4", |
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| 136 | ("time")) |
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| 137 | # BOUNDARY - vertical slices from left, right, south, north, top |
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| 138 | varname = 'pt' |
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| 139 | _val_ls_forcing_pt_left = outfile.createVariable('ls_forcing_left_' + varname, "f4", ("time", "z", "y"), |
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| 140 | fill_value=fillvalue_float) |
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| 141 | _val_ls_forcing_pt_right = outfile.createVariable('ls_forcing_right_' + varname, "f4", ("time", "z", "y"), |
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| 142 | fill_value=fillvalue_float) |
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| 143 | _val_ls_forcing_pt_south = outfile.createVariable('ls_forcing_south_' + varname, "f4", ("time", "z", "x"), |
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| 144 | fill_value=fillvalue_float) |
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| 145 | _val_ls_forcing_pt_north = outfile.createVariable('ls_forcing_north_' + varname, "f4", ("time", "z", "x"), |
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| 146 | fill_value=fillvalue_float) |
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| 147 | _val_ls_forcing_pt_top = outfile.createVariable('ls_forcing_top_' + varname, "f4", ("time", "y", "x"), |
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| 148 | fill_value=fillvalue_float) |
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| 149 | |
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| 150 | varname = 'qv' |
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| 151 | _val_ls_forcing_qv_left = outfile.createVariable('ls_forcing_left_' + varname, "f4", ("time", "z", "y"), |
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| 152 | fill_value=fillvalue_float) |
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| 153 | _val_ls_forcing_qv_right = outfile.createVariable('ls_forcing_right_' + varname, "f4", ("time", "z", "y"), |
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| 154 | fill_value=fillvalue_float) |
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| 155 | _val_ls_forcing_qv_south = outfile.createVariable('ls_forcing_south_' + varname, "f4", ("time", "z", "x"), |
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| 156 | fill_value=fillvalue_float) |
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| 157 | _val_ls_forcing_qv_north = outfile.createVariable('ls_forcing_north_' + varname, "f4", ("time", "z", "x"), |
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| 158 | fill_value=fillvalue_float) |
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| 159 | _val_ls_forcing_qv_top = outfile.createVariable('ls_forcing_top_' + varname, "f4", ("time", "y", "x"), |
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| 160 | fill_value=fillvalue_float) |
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| 161 | |
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| 162 | varname = 'u' |
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| 163 | _val_ls_forcing_u_left = outfile.createVariable('ls_forcing_left_' + varname, "f4", ("time", "z", "y"), |
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| 164 | fill_value=fillvalue_float) |
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| 165 | _val_ls_forcing_u_right = outfile.createVariable('ls_forcing_right_' + varname, "f4", ("time", "z", "y"), |
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| 166 | fill_value=fillvalue_float) |
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| 167 | _val_ls_forcing_u_south = outfile.createVariable('ls_forcing_south_' + varname, "f4", ("time", "z", "xu"), |
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| 168 | fill_value=fillvalue_float) |
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| 169 | _val_ls_forcing_u_north = outfile.createVariable('ls_forcing_north_' + varname, "f4", ("time", "z", "xu"), |
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| 170 | fill_value=fillvalue_float) |
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| 171 | _val_ls_forcing_u_top = outfile.createVariable('ls_forcing_top_' + varname, "f4", ("time", "y", "xu"), |
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| 172 | fill_value=fillvalue_float) |
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| 173 | |
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| 174 | varname = 'v' |
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| 175 | _val_ls_forcing_v_left = outfile.createVariable('ls_forcing_left_' + varname, "f4", ("time", "z", "yv"), |
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| 176 | fill_value=fillvalue_float) |
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| 177 | _val_ls_forcing_v_right = outfile.createVariable('ls_forcing_right_' + varname, "f4", ("time", "z", "yv"), |
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| 178 | fill_value=fillvalue_float) |
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| 179 | _val_ls_forcing_v_south = outfile.createVariable('ls_forcing_south_' + varname, "f4", ("time", "z", "x"), |
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| 180 | fill_value=fillvalue_float) |
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| 181 | _val_ls_forcing_v_north = outfile.createVariable('ls_forcing_north_' + varname, "f4", ("time", "z", "x"), |
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| 182 | fill_value=fillvalue_float) |
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| 183 | _val_ls_forcing_v_top = outfile.createVariable('ls_forcing_top_' + varname, "f4", ("time", "yv", "x"), |
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| 184 | fill_value=fillvalue_float) |
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| 185 | |
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| 186 | varname = 'w' |
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| 187 | _val_ls_forcing_w_left = outfile.createVariable('ls_forcing_left_' + varname, "f4", ("time", "zw", "y"), |
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| 188 | fill_value=fillvalue_float) |
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| 189 | _val_ls_forcing_w_right = outfile.createVariable('ls_forcing_right_' + varname, "f4", ("time", "zw", "y"), |
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| 190 | fill_value=fillvalue_float) |
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| 191 | _val_ls_forcing_w_south = outfile.createVariable('ls_forcing_south_' + varname, "f4", ("time", "zw", "x"), |
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| 192 | fill_value=fillvalue_float) |
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| 193 | _val_ls_forcing_w_north = outfile.createVariable('ls_forcing_north_' + varname, "f4", ("time", "zw", "x"), |
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| 194 | fill_value=fillvalue_float) |
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| 195 | _val_ls_forcing_w_top = outfile.createVariable('ls_forcing_top_' + varname, "f4", ("time", "y", "x"), |
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| 196 | fill_value=fillvalue_float) |
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| 197 | |
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| 198 | # geostrophic wind |
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| 199 | _val_ls_forcing_ug = outfile.createVariable('ls_forcing_ug', "f4", ("time", "z"), |
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| 200 | fill_value=fillvalue_float) |
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| 201 | _val_ls_forcing_vg = outfile.createVariable('ls_forcing_vg', "f4", ("time", "z"), |
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| 202 | fill_value=fillvalue_float) |
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| 203 | time.sleep(1) |
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| 204 | |
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| 205 | # write values for initialization variables |
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| 206 | _val_init_atmosphere_pt[:, :, :] = init_atmosphere_pt[0, :, :, :] |
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| 207 | _val_init_atmosphere_qv[:, :, :] = init_atmosphere_qv[0, :, :, :] |
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| 208 | _val_init_atmosphere_u[:, :, :] = init_atmosphere_u[0, :, :, 1:] |
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| 209 | _val_init_atmosphere_v[:, :, :] = init_atmosphere_v[0, :, 1:, :] |
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| 210 | _val_init_atmosphere_w[:, :, :] = init_atmosphere_w[0, :, :, :] |
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| 211 | _val_init_soil_t[:, :, :] = init_soil_t[0, :, :, :] |
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| 212 | for k in range(0,_val_init_soil_m.shape[0]): |
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| 213 | # adjust soil moisture according soil_moisture_adjust field (if exists) |
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| 214 | _val_init_soil_m[k, :, :] = init_soil_m[0, k, :, :] * sma[:, :] |
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| 215 | finally: |
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| 216 | # close interpolated file |
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| 217 | infile.close() |
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| 218 | # |
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| 219 | if not nested_domain: |
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| 220 | # cycle over all included time steps |
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| 221 | for ts in range(0, len(interp_files)): |
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| 222 | print("Processing file",interp_files[ts]) |
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| 223 | # open corresponding interpolated file |
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| 224 | infile = netCDF4.Dataset(interp_files[ts], "r", format="NETCDF4") |
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| 225 | try: |
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| 226 | # open variables in the input file |
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| 227 | init_atmosphere_pt = infile.variables['init_atmosphere_pt'] |
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| 228 | init_atmosphere_qv = infile.variables['init_atmosphere_qv'] |
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| 229 | init_atmosphere_u = infile.variables['init_atmosphere_u'] |
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| 230 | init_atmosphere_v = infile.variables['init_atmosphere_v'] |
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| 231 | init_atmosphere_w = infile.variables['init_atmosphere_w'] |
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| 232 | surface_forcing_surface_pressure = infile.variables['surface_forcing_surface_pressure'] |
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| 233 | |
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| 234 | ################################## |
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| 235 | # write values for time dependent values |
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| 236 | # surface pressure |
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| 237 | _val_surface_forcing_surface_pressure[ts] = np.average(surface_forcing_surface_pressure[:,:,:], axis = (1,2))[0] |
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| 238 | # boundary conditions |
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| 239 | _val_ls_forcing_pt_left[ts, :, :] = init_atmosphere_pt[0, :, :, 0] |
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| 240 | _val_ls_forcing_pt_right[ts, :, :] = init_atmosphere_pt[0, :, :, dimensions['xdim'] - 1] |
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| 241 | _val_ls_forcing_pt_south[ts, :, :] = init_atmosphere_pt[0, :, 0, :] |
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| 242 | _val_ls_forcing_pt_north[ts, :, :] = init_atmosphere_pt[0, :, dimensions['ydim'] - 1, :] |
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| 243 | _val_ls_forcing_pt_top[ts, :, :] = init_atmosphere_pt[0, dimensions['zdim'] - 1, :, :] |
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| 244 | |
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| 245 | _val_ls_forcing_qv_left[ts, :, :] = init_atmosphere_qv[0, :, :, 0] |
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| 246 | _val_ls_forcing_qv_right[ts, :, :] = init_atmosphere_qv[0, :, :, dimensions['xdim'] - 1] |
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| 247 | _val_ls_forcing_qv_south[ts, :, :] = init_atmosphere_qv[0, :, 0, :] |
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| 248 | _val_ls_forcing_qv_north[ts, :, :] = init_atmosphere_qv[0, :, dimensions['ydim'] - 1, :] |
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| 249 | _val_ls_forcing_qv_top[ts, :, :] = init_atmosphere_qv[0, dimensions['zdim'] - 1, :, :] |
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| 250 | |
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| 251 | # Perform mass balancing |
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| 252 | uxleft = init_atmosphere_u[0, :, :, 0] |
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| 253 | uxright = init_atmosphere_u[0, :, :, dimensions['xdim'] - 1] |
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| 254 | vysouth = init_atmosphere_v[0, :, 0, :] |
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| 255 | vynorth = init_atmosphere_v[0, :, dimensions['ydim'] - 1, :] |
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| 256 | wztop = init_atmosphere_w[0, dimensions['zwdim'] - 1, :, :] |
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| 257 | mass_disbalance = ((uxleft * areas_xb).sum() |
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| 258 | - (uxright * areas_xb).sum() |
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| 259 | + (vysouth * areas_yb).sum() |
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| 260 | - (vynorth * areas_yb).sum() |
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| 261 | - (wztop * areas_zb).sum()) |
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| 262 | mass_corr_v = mass_disbalance / area_boundaries |
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| 263 | print('Mass disbalance: {0:8g} m3/s (avg = {1:8g} m/s)'.format( |
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| 264 | mass_disbalance, mass_corr_v)) |
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| 265 | uxleft -= mass_corr_v |
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| 266 | uxright += mass_corr_v |
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| 267 | vysouth -= mass_corr_v |
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| 268 | vynorth += mass_corr_v |
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| 269 | wztop += mass_corr_v |
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| 270 | |
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| 271 | # Verify mass balance (optional) |
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| 272 | #mass_disbalance = ((uxleft * areas_xb).sum() |
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| 273 | # - (uxright * areas_xb).sum() |
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| 274 | # + (vysouth * areas_yb).sum() |
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| 275 | # - (vynorth * areas_yb).sum() |
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| 276 | # - (wztop * areas_zb).sum()) |
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| 277 | #mass_corr_v = mass_disbalance / area_boundaries |
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| 278 | #print('Mass balanced: {0:8g} m3/s (avg = {1:8g} m/s)'.format( |
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| 279 | # mass_disbalance, mass_corr_v)) |
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| 280 | |
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| 281 | _val_ls_forcing_u_left[ts, :, :] = uxleft |
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| 282 | _val_ls_forcing_u_right[ts, :, :] = uxright |
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| 283 | _val_ls_forcing_u_south[ts, :, :] = init_atmosphere_u[0, :, 0, 1:] |
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| 284 | _val_ls_forcing_u_north[ts, :, :] = init_atmosphere_u[0, :, dimensions['ydim'] - 1, 1:] |
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| 285 | _val_ls_forcing_u_top[ts, :, :] = init_atmosphere_u[0, dimensions['zdim'] - 1, :, 1:] |
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| 286 | |
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| 287 | _val_ls_forcing_v_left[ts, :, :] = init_atmosphere_v[0, :, 1:, 0] |
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| 288 | _val_ls_forcing_v_right[ts, :, :] = init_atmosphere_v[0, :, 1:, dimensions['xdim'] - 1] |
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| 289 | _val_ls_forcing_v_south[ts, :, :] = vysouth |
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| 290 | _val_ls_forcing_v_north[ts, :, :] = vynorth |
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| 291 | _val_ls_forcing_v_top[ts, :, :] = init_atmosphere_v[0, dimensions['zdim'] - 1, 1:, :] |
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| 292 | |
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| 293 | _val_ls_forcing_w_left[ts, :, :] = init_atmosphere_w[0, :, :, 0] |
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| 294 | _val_ls_forcing_w_right[ts, :, :] = init_atmosphere_w[0, :, :, dimensions['xdim'] - 1] |
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| 295 | _val_ls_forcing_w_south[ts, :, :] = init_atmosphere_w[0, :, 0, :] |
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| 296 | _val_ls_forcing_w_north[ts, :, :] = init_atmosphere_w[0, :, dimensions['ydim'] - 1, :] |
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| 297 | _val_ls_forcing_w_top[ts, :, :] = wztop |
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| 298 | |
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| 299 | finally: |
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| 300 | # close interpolated file |
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| 301 | infile.close() |
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| 302 | |
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| 303 | # write geostrophic wind |
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| 304 | print('Open wrf file '+wrf_files[ts]) |
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| 305 | nc_wrf = netCDF4.Dataset(wrf_files[ts], 'r') |
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| 306 | try: |
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| 307 | ug, vg = palm_wrf_gw(nc_wrf, lon_center, lat_center, z_levels) |
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| 308 | _val_ls_forcing_ug[ts, :] = ug |
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| 309 | _val_ls_forcing_vg[ts, :] = vg |
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| 310 | finally: |
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| 311 | nc_wrf.close() |
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| 312 | |
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| 313 | # Write chemical boundary conds |
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| 314 | if camx_interp_fname: |
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| 315 | f_camx = netCDF4.Dataset(camx_interp_fname) |
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| 316 | try: |
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| 317 | for vname, vval in f_camx.variables.items(): |
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| 318 | # PALM doesn't support 3D LOD=2 init for chem yet, we have to average the field |
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| 319 | var = outfile.createVariable('init_atmosphere_'+vname, |
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| 320 | 'f4', ('z',), fill_value=fillvalue_float) |
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| 321 | var.units = vval.units |
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| 322 | var.lod = 1 |
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| 323 | var[:] = vval[0,:,:,:].mean(axis=(1,2)) |
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| 324 | |
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| 325 | var = outfile.createVariable('ls_forcing_left_'+vname, |
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| 326 | 'f4', ('time','z','y'), fill_value=fillvalue_float) |
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| 327 | var.units = vval.units |
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| 328 | var[:] = vval[:,:,:,0] |
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| 329 | |
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| 330 | var = outfile.createVariable('ls_forcing_right_'+vname, |
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| 331 | 'f4', ('time','z','y'), fill_value=fillvalue_float) |
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| 332 | var.units = vval.units |
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| 333 | var[:] = vval[:,:,:,-1] |
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| 334 | |
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| 335 | var = outfile.createVariable('ls_forcing_south_'+vname, |
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| 336 | 'f4', ('time','z','x'), fill_value=fillvalue_float) |
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| 337 | var.units = vval.units |
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| 338 | var[:] = vval[:,:,0,:] |
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| 339 | |
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| 340 | var = outfile.createVariable('ls_forcing_north_'+vname, |
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| 341 | 'f4', ('time','z','x'), fill_value=fillvalue_float) |
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| 342 | var.units = vval.units |
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| 343 | var[:] = vval[:,:,-1,:] |
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| 344 | |
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| 345 | var = outfile.createVariable('ls_forcing_top_'+vname, |
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| 346 | 'f4', ('time','y','x'), fill_value=fillvalue_float) |
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| 347 | var.units = vval.units |
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| 348 | var[:] = vval[:,-1,:,:] |
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| 349 | finally: |
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| 350 | f_camx.close() |
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| 351 | |
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| 352 | if len(rad_times_proc) > 0: |
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| 353 | # process radiation inputs |
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| 354 | # radiation time dimension and variable |
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| 355 | outfile.createDimension('time_rad', len(rad_times_proc)) |
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| 356 | _val_times = outfile.createVariable('time_rad',"f4", ("time_rad")) |
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| 357 | _val_times[:] = rad_times_proc[:] |
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| 358 | # radiation variables |
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| 359 | var = outfile.createVariable('rad_sw_in', "f4", ("time_rad"), fill_value=fillvalue_float) |
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| 360 | var.setncattr('lod', 1) |
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| 361 | var.units = 'W/m2' |
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| 362 | var[:] = rad_values_proc[0][:] |
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| 363 | var = outfile.createVariable('rad_lw_in', "f4", ("time_rad"), fill_value=fillvalue_float) |
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| 364 | var.setncattr('lod', 1) |
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| 365 | var.units = 'W/m2' |
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| 366 | var[:] = rad_values_proc[1][:] |
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| 367 | var = outfile.createVariable('rad_sw_in_dif', "f4", ("time_rad"), fill_value=fillvalue_float) |
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| 368 | var.setncattr('lod', 1) |
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| 369 | var.units = 'W/m2' |
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| 370 | var[:] = rad_values_proc[2][:] |
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| 371 | |
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| 372 | finally: |
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| 373 | outfile.close() |
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| 374 | |
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| 375 | |
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| 376 | |
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| 377 | |
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| 378 | |
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