| 1 | # -*- Mode: python -*- |
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| 2 | ### =========================================================================== |
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| 3 | ### |
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| 4 | ### Compute runoff weights. |
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| 5 | ### For LMDZ only. Not suitable for DYNAMICO |
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| 6 | ### |
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| 7 | ### =========================================================================== |
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| 8 | ## |
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| 9 | ## Warning, to install, configure, run, use any of Olivier Marti's |
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| 10 | ## software or to read the associated documentation you'll need at least |
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| 11 | ## one (1) brain in a reasonably working order. Lack of this implement |
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| 12 | ## will void any warranties (either express or implied). |
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| 13 | ## O. Marti assumes no responsability for errors, omissions, |
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| 14 | ## data loss, or any other consequences caused directly or indirectly by |
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| 15 | ## the usage of his software by incorrectly or partially configured |
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| 16 | ## personal. |
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| 17 | ## |
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| 18 | # SVN information |
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| 19 | __Author__ = "$Author$" |
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| 20 | __Date__ = "$Date$" |
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| 21 | __Revision__ = "$Revision$" |
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| 22 | __Id__ = "$Id$" |
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| 23 | __HeadURL__ = "$HeadURL$" |
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| 24 | __SVN_Date__ = "$SVN_Date: $" |
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| 25 | ## |
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| 26 | |
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| 27 | ## Modules |
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| 28 | import netCDF4 |
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| 29 | import numpy as np |
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| 30 | import nemo |
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| 31 | from scipy import ndimage |
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| 32 | import sys, os, platform, argparse, textwrap, time |
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| 33 | |
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| 34 | ## Userful constants |
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| 35 | zero = np.dtype('float64').type(0.0) |
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| 36 | zone = np.dtype('float64').type(1.0) |
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| 37 | epsfrac = np.dtype('float64').type(1.0E-10) |
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| 38 | pi = np.pi |
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| 39 | rad = pi/np.dtype('float64').type(180.0) |
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| 40 | ra = np.dtype('float64').type(6371229.0) # Earth radius |
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| 41 | |
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| 42 | ## Functions |
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| 43 | def geodist (plon1, plat1, plon2, plat2) : |
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| 44 | """Distance between two points (on sphere)""" |
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| 45 | zs = np.sin (rad*plat1) * np.sin (rad*plat2) + np.cos (rad*plat1) * np.cos (rad*plat2) * np.cos(rad*(plon2-plon1)) |
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| 46 | zs = np.maximum (-zone, np.minimum (zone, zs)) |
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| 47 | geodist = np.arccos (zs) |
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| 48 | return geodist |
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| 49 | |
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| 50 | ### ===== Reading command line parameters ================================================== |
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| 51 | # Creating a parser |
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| 52 | parser = argparse.ArgumentParser ( |
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| 53 | description = """Compute calving weights""", |
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| 54 | epilog='-------- End of the help message --------') |
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| 55 | |
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| 56 | # Adding arguments |
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| 57 | parser.add_argument ('--oce' , help='oce model name', type=str, default='eORCA1.2', choices=['ORCA2.3', 'eORCA1.2', 'eORCA025'] ) |
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| 58 | parser.add_argument ('--atm' , help='atm model name (LMD*)', type=str, default='LMD9695' ) |
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| 59 | parser.add_argument ('--atmCoastWidth', help='width of the coastal band in atmosphere (in grid points)', type=int, default=1 ) |
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| 60 | parser.add_argument ('--oceCoastWidth', help='width of the coastal band in ocean (in grid points)' , type=int, default=2 ) |
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| 61 | parser.add_argument ('--searchRadius' , help='max distance to connect a land point to an ocean point (in km)', type=float, default=600000.0) |
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| 62 | parser.add_argument ('--grids' , help='grids file name', default='grids.nc' ) |
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| 63 | parser.add_argument ('--areas' , help='masks file name', default='areas.nc' ) |
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| 64 | parser.add_argument ('--masks' , help='areas file name', default='masks.nc' ) |
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| 65 | parser.add_argument ('--o2a' , help='o2a file name' , default='o2a.nc' ) |
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| 66 | parser.add_argument ('--output', help='output rmp file name', default='rmp_tlmd_to_torc_runoff_64bit.nc' ) |
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| 67 | parser.add_argument ('--fmt' , help='NetCDF file format, using nco syntax', default='64bit', choices=['classic', 'netcdf3', '64bit', '64bit_data', '64bit_data', 'netcdf4', 'netcdf4_classsic'] ) |
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| 68 | |
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| 69 | # Parse command line |
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| 70 | myargs = parser.parse_args() |
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| 71 | |
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| 72 | # |
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| 73 | grids = myargs.grids |
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| 74 | areas = myargs.areas |
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| 75 | masks = myargs.masks |
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| 76 | o2a = myargs.o2a |
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| 77 | |
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| 78 | # Model Names |
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| 79 | atm_Name = myargs.atm |
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| 80 | oce_Name = myargs.oce |
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| 81 | # Width of the coastal band (land points) in the atmopshere |
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| 82 | atmCoastWidth = myargs.atmCoastWidth |
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| 83 | # Width of the coastal band (ocean points) in the ocean |
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| 84 | oceCoastWidth = myargs.oceCoastWidth |
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| 85 | searchRadius = myargs.searchRadius * 1000.0 # From km to meters |
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| 86 | # Netcdf format |
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| 87 | if myargs.fmt == 'classic' : FmtNetcdf = 'CLASSIC' |
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| 88 | if myargs.fmt == 'netcdf3' : FmtNetcdf = 'CLASSIC' |
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| 89 | if myargs.fmt == '64bit' : FmtNetcdf = 'NETCDF3_64BIT_OFFSET' |
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| 90 | if myargs.fmt == '64bit_data' : FmtNetcdf = 'NETCDF3_64BIT_DATA' |
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| 91 | if myargs.fmt == '64bit_offset' : FmtNetcdf = 'NETCDF3_64BIT_OFFSET' |
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| 92 | if myargs.fmt == 'netcdf4' : FmtNetcdf = 'NETCDF4' |
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| 93 | if myargs.fmt == 'netcdf4_classic' : FmtNetcdf = 'NETCDF4_CLASSIC' |
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| 94 | |
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| 95 | ### Read coordinates of all models |
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| 96 | ### |
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| 97 | |
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| 98 | diaFile = netCDF4.Dataset ( o2a ) |
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| 99 | gridFile = netCDF4.Dataset ( grids ) |
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| 100 | areaFile = netCDF4.Dataset ( areas ) |
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| 101 | maskFile = netCDF4.Dataset ( masks ) |
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| 102 | |
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| 103 | o2aFrac = diaFile ['OceFrac'][:].squeeze() |
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| 104 | o2aFrac = np.where ( np.abs(o2aFrac) < 1E10, o2aFrac, 0.0) |
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| 105 | |
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| 106 | atm_grid_center_lat = gridFile['tlmd.lat'][:] |
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| 107 | atm_grid_center_lon = gridFile['tlmd.lon'][:] |
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| 108 | atm_grid_corner_lat = gridFile['tlmd.cla'][:] |
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| 109 | atm_grid_corner_lon = gridFile['tlmd.clo'][:] |
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| 110 | |
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| 111 | atm_grid_area = areaFile['tlmd.srf'][:] |
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| 112 | atm_grid_imask = 1-maskFile['tlmd.msk'][:].squeeze() |
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| 113 | atm_grid_dims = atm_grid_area.shape |
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| 114 | (atm_nvertex, atm_jpj, atm_jpi) = atm_grid_corner_lat.shape |
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| 115 | atm_perio = 0 |
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| 116 | atm_grid_pmask = nemo.lbc_mask (atm_grid_imask, 'T', atm_perio) |
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| 117 | atm_address = np.reshape ( np.arange(atm_jpj*atm_jpi), (atm_jpj, atm_jpi) ) |
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| 118 | atm_grid_size = atm_jpj*atm_jpi |
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| 119 | |
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| 120 | oce_grid_center_lat = gridFile['torc.lat'][:] |
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| 121 | oce_grid_center_lon = gridFile['torc.lon'][:] |
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| 122 | oce_grid_corner_lat = gridFile['torc.cla'][:] |
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| 123 | oce_grid_corner_lon = gridFile['torc.clo'][:] |
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| 124 | oce_grid_area = areaFile['torc.srf'][:] |
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| 125 | oce_grid_imask = 1-maskFile['torc.msk'][:] |
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| 126 | oce_grid_dims = oce_grid_area.shape |
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| 127 | (oce_nvertex, oce_jpj, oce_jpi) = oce_grid_corner_lat.shape ; jpon=oce_jpj*oce_jpj |
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| 128 | if oce_jpi == 182 : oce_perio = 4 # ORCA 2 |
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| 129 | if oce_jpi == 362 : oce_perio = 6 # ORCA 1 |
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| 130 | if oce_jpi == 1442 : oce_perio = 6 # ORCA 025 |
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| 131 | oce_grid_pmask = nemo.lbc_mask (oce_grid_imask, 'T', oce_perio) |
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| 132 | oce_address = np.reshape ( np.arange(oce_jpj*oce_jpi), (oce_jpj, oce_jpi) ) |
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| 133 | oce_grid_size = oce_jpj*oce_jpi |
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| 134 | |
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| 135 | ## Fill closed sea with image processing library |
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| 136 | oce_grid_imask = nemo.lbc_mask ( 1-ndimage.binary_fill_holes (1-nemo.lbc(oce_grid_imask, nperio=oce_perio, cd_type='T')), nperio=oce_perio, cd_type='T' ) |
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| 137 | |
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| 138 | ## |
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| 139 | print ("Determination d'une bande cotiere ocean") |
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| 140 | |
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| 141 | oceLand = np.where (oce_grid_pmask[:] < 0.5, True, False) |
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| 142 | oceOcean = np.where (oce_grid_pmask[:] > 0.5, True, False) |
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| 143 | |
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| 144 | NNocean = 1+2*oceCoastWidth |
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| 145 | oceOceanFiltered = ndimage.uniform_filter(oceOcean.astype(float), size=NNocean) |
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| 146 | oceCoast = np.where (oceOceanFiltered<(1.0-0.5/(NNocean**2)),True,False) & oceOcean |
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| 147 | oceCoast = nemo.lbc_mask (oceCoast, oce_perio, 'T') |
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| 148 | |
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| 149 | print ('Number of points in oceLand : ' + str(oceLand.sum()) ) |
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| 150 | print ('Number of points in oceOcean : ' + str(oceOcean.sum()) ) |
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| 151 | print ('Number of points in oceCoast : ' + str(oceCoast.sum()) ) |
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| 152 | |
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| 153 | # Arrays with coastal points only |
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| 154 | oceCoast_grid_center_lon = oce_grid_center_lon[oceCoast] |
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| 155 | oceCoast_grid_center_lat = oce_grid_center_lat[oceCoast] |
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| 156 | oceCoast_grid_area = oce_grid_area [oceCoast] |
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| 157 | oceCoast_grid_imask = oce_grid_imask [oceCoast] |
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| 158 | oceCoast_grid_pmask = oce_grid_pmask [oceCoast] |
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| 159 | oceCoast_address = oce_address [oceCoast] |
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| 160 | |
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| 161 | print ("Determination d'une bande cotiere atmosphere " ) |
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| 162 | atmLand = np.where (o2aFrac[:] < epsfrac , True, False) |
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| 163 | atmLandFrac = np.where (o2aFrac[:] < zone-epsfrac , True, False) |
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| 164 | atmFrac = np.where (o2aFrac[:] > epsfrac , True, False) & np.where (o2aFrac[:] < (zone-epsfrac), True, False) |
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| 165 | atmOcean = np.where (o2aFrac[:] < (zone-epsfrac), True, False) |
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| 166 | atmOceanFrac = np.where (o2aFrac[:] > epsfrac , True, False) |
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| 167 | |
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| 168 | NNatm = 1+2*atmCoastWidth |
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| 169 | atmLandFiltered = ndimage.uniform_filter(atmLand.astype(float), size=NNatm) |
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| 170 | atmCoast = np.where (atmLandFiltered<(1.0-0.5/(NNatm**2)),True,False) & atmLandFrac |
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| 171 | atmCoast = nemo.lbc_mask (atmCoast, 1, 'T') |
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| 172 | |
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| 173 | print ('Number of points in atmLand : ' + str(atmLand.sum()) ) |
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| 174 | print ('Number of points in atmOcean : ' + str(atmOcean.sum()) ) |
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| 175 | print ('Number of points in atmCoast : ' + str(atmCoast.sum()) ) |
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| 176 | |
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| 177 | # Arrays with coastal points only |
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| 178 | atmCoast_grid_center_lon = atm_grid_center_lon[atmCoast] |
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| 179 | atmCoast_grid_center_lat = atm_grid_center_lat[atmCoast] |
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| 180 | atmCoast_grid_area = atm_grid_area [atmCoast] |
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| 181 | atmCoast_grid_imask = atm_grid_imask [atmCoast] |
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| 182 | atmCoast_grid_pmask = atm_grid_pmask [atmCoast] |
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| 183 | atmCoast_address = atm_address [atmCoast] |
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| 184 | |
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| 185 | remap_matrix = np.empty ( shape=(0), dtype=np.float64 ) |
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| 186 | atm_address = np.empty ( shape=(0), dtype=np.int32 ) |
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| 187 | oce_address = np.empty ( shape=(0), dtype=np.int32 ) |
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| 188 | |
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| 189 | ## Loop on atmosphere coastal points |
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| 190 | for ja in np.arange(len(atmCoast_grid_pmask)) : |
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| 191 | z_dist = geodist ( atmCoast_grid_center_lon[ja], atmCoast_grid_center_lat[ja], oceCoast_grid_center_lon, oceCoast_grid_center_lat) |
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| 192 | z_mask = np.where ( z_dist*ra < searchRadius, True, False) |
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| 193 | num_links = z_mask.sum() |
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| 194 | if num_links == 0 : continue |
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| 195 | z_area = oceCoast_grid_area[z_mask].sum() |
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| 196 | poids = 1.0 / z_area |
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| 197 | #print ( num_links, z_mask.sum(), z_area ) |
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| 198 | # |
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| 199 | matrix_local = np.ones ((num_links),dtype=np.float64) * poids |
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| 200 | # address on source grid : all links points to the same LMDZ point. |
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| 201 | atm_address_local = np.ones(num_links, dtype=np.int32 ) * atmCoast_address[ja] |
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| 202 | # address on destination grid |
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| 203 | oce_address_local = oceCoast_address[z_mask] |
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| 204 | # Append to global tabs |
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| 205 | remap_matrix = np.append ( remap_matrix, matrix_local ) |
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| 206 | atm_address = np.append ( atm_address , atm_address_local ) |
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| 207 | oce_address = np.append ( oce_address , oce_address_local ) |
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| 208 | |
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| 209 | print ('End of loop') |
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| 210 | |
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| 211 | num_links = remap_matrix.shape[0] |
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| 212 | |
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| 213 | ### Output file |
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| 214 | runoff = myargs.output |
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| 215 | f_runoff = netCDF4.Dataset ( runoff, 'w', format=FmtNetcdf ) |
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| 216 | print ('Output file: ' + runoff ) |
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| 217 | |
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| 218 | f_runoff.Conventions = "CF-1.6" |
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| 219 | f_runoff.source = "IPSL Earth system model" |
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| 220 | f_runoff.group = "ICMC IPSL Climate Modelling Center" |
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| 221 | f_runoff.Institution = "IPSL https.//www.ipsl.fr" |
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| 222 | f_runoff.Ocean = oce_Name + " https://www.nemo-ocean.eu" |
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| 223 | f_runoff.Atmosphere = atm_Name + " http://lmdz.lmd.jussieu.fr" |
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| 224 | f_runoff.associatedFiles = grids + " " + areas + " " + masks |
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| 225 | f_runoff.directory = os.getcwd () |
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| 226 | f_runoff.description = "Generated with cotes_etal.py" |
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| 227 | f_runoff.title = runoff |
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| 228 | f_runoff.Program = "Generated by " + sys.argv[0] + " with flags " + str(sys.argv[1:]) |
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| 229 | f_runoff.atmCoastWidth = str(atmCoastWidth) + " grid points" |
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| 230 | f_runoff.oceCoastWidth = str(oceCoastWidth) + " grid points" |
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| 231 | f_runoff.searchRadius = str(searchRadius/1000.) + " km" |
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| 232 | f_runoff.gridsFile = grids |
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| 233 | f_runoff.areasFile = areas |
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| 234 | f_runoff.masksFile = masks |
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| 235 | f_runoff.o2aFile = o2a |
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| 236 | f_runoff.timeStamp = time.asctime() |
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| 237 | f_runoff.uuid = areaFile.uuid |
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| 238 | f_runoff.HOSTNAME = platform.node() |
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| 239 | #f_runoff.LOGNAME = os.getlogin() |
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| 240 | f_runoff.Python = "Python version " + platform.python_version() |
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| 241 | f_runoff.OS = platform.system() |
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| 242 | f_runoff.release = platform.release() |
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| 243 | f_runoff.hardware = platform.machine() |
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| 244 | f_runoff.conventions = "SCRIP" |
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| 245 | f_runoff.source_grid = "curvilinear" |
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| 246 | f_runoff.dest_grid = "curvilinear" |
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| 247 | f_runoff.Model = "IPSL CM6" |
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| 248 | f_runoff.SVN_Author = "$Author$" |
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| 249 | f_runoff.SVN_Date = "$Date$" |
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| 250 | f_runoff.SVN_Revision = "$Revision$" |
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| 251 | f_runoff.SVN_Id = "$Id$" |
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| 252 | f_runoff.SVN_HeadURL = "$HeadURL$" |
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| 253 | |
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| 254 | d_num_links = f_runoff.createDimension ('num_links' , num_links ) |
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| 255 | d_num_wgts = f_runoff.createDimension ('num_wgts' , 1 ) |
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| 256 | |
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| 257 | d_atm_grid_size = f_runoff.createDimension ('src_grid_size' , atm_grid_size ) |
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| 258 | d_atm_grid_corners = f_runoff.createDimension ('src_grid_corners', atm_grid_corner_lon.shape[0] ) |
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| 259 | d_atm_grid_rank = f_runoff.createDimension ('src_grid_rank' , 2 ) |
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| 260 | |
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| 261 | d_oce_grid_size = f_runoff.createDimension ('dst_grid_size' , oce_grid_size ) |
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| 262 | d_oce_grid_corners = f_runoff.createDimension ('dst_grid_corners', oce_grid_corner_lon.shape[0] ) |
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| 263 | d_oce_grid_rank = f_runoff.createDimension ('dst_grid_rank' , 2 ) |
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| 264 | |
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| 265 | v_remap_matrix = f_runoff.createVariable ( 'remap_matrix', 'f8', ('num_links', 'num_wgts') ) |
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| 266 | |
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| 267 | v_atm_address = f_runoff.createVariable ( 'src_address' , 'i4', ('num_links',) ) |
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| 268 | v_oce_address = f_runoff.createVariable ( 'dst_address' , 'i4', ('num_links',) ) |
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| 269 | |
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| 270 | v_remap_matrix[:] = remap_matrix |
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| 271 | v_atm_address [:] = atm_address + 1 # OASIS uses Fortran style indexing |
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| 272 | v_oce_address [:] = oce_address + 1 |
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| 273 | |
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| 274 | v_atm_grid_dims = f_runoff.createVariable ( 'src_grid_dims' , 'i4', ('src_grid_rank',) ) |
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| 275 | v_atm_grid_center_lon = f_runoff.createVariable ( 'src_grid_center_lon', 'i4', ('src_grid_size',) ) |
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| 276 | v_atm_grid_center_lat = f_runoff.createVariable ( 'src_grid_center_lat', 'i4', ('src_grid_size',) ) |
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| 277 | v_atm_grid_center_lon.units='degrees_east' ; v_atm_grid_center_lon.long_name='Longitude' ; v_atm_grid_center_lon.long_name='longitude' ; v_atm_grid_center_lon.bounds="src_grid_corner_lon" |
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| 278 | v_atm_grid_center_lat.units='degrees_north' ; v_atm_grid_center_lat.long_name='Latitude' ; v_atm_grid_center_lat.long_name='latitude ' ; v_atm_grid_center_lat.bounds="src_grid_corner_lat" |
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| 279 | v_atm_grid_corner_lon = f_runoff.createVariable ( 'src_grid_corner_lon', 'f8', ('src_grid_size', 'src_grid_corners') ) |
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| 280 | v_atm_grid_corner_lat = f_runoff.createVariable ( 'src_grid_corner_lat', 'f8', ('src_grid_size', 'src_grid_corners') ) |
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| 281 | v_atm_grid_corner_lon.units="degrees_east" |
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| 282 | v_atm_grid_corner_lat.units="degrees_north" |
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| 283 | v_atm_grid_area = f_runoff.createVariable ( 'src_grid_area' , 'f8', ('src_grid_size',) ) |
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| 284 | v_atm_grid_area.long_name="Grid area" ; v_atm_grid_area.standard_name="cell_area" ; v_atm_grid_area.units="m2" |
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| 285 | v_atm_grid_imask = f_runoff.createVariable ( 'src_grid_imask' , 'i4', ('src_grid_size',) ) |
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| 286 | v_atm_grid_imask.long_name="Land-sea mask" ; v_atm_grid_imask.units="Land:1, Ocean:0" |
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| 287 | v_atm_grid_pmask = f_runoff.createVariable ( 'src_grid_pmask' , 'i4', ('src_grid_size',) ) |
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| 288 | v_atm_grid_pmask.long_name="Land-sea mask (periodicity removed)" ; v_atm_grid_pmask.units="Land:1, Ocean:0" |
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| 289 | |
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| 290 | v_atm_grid_dims [:] = atm_grid_dims |
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| 291 | v_atm_grid_center_lon[:] = atm_grid_center_lon[:].ravel() |
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| 292 | v_atm_grid_center_lat[:] = atm_grid_center_lat[:].ravel() |
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| 293 | v_atm_grid_corner_lon[:] = atm_grid_corner_lon.reshape( (atm_jpi*atm_jpj, d_atm_grid_corners.__len__()) ) |
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| 294 | v_atm_grid_corner_lat[:] = atm_grid_corner_lat.reshape( (atm_jpi*atm_jpj, d_atm_grid_corners.__len__()) ) |
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| 295 | v_atm_grid_area [:] = atm_grid_area[:].ravel() |
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| 296 | v_atm_grid_imask [:] = atm_grid_imask[:].ravel() |
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| 297 | v_atm_grid_pmask [:] = atm_grid_pmask[:].ravel() |
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| 298 | |
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| 299 | # -- |
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| 300 | |
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| 301 | v_oce_grid_dims = f_runoff.createVariable ( 'dst_grid_dims' , 'i4', ('dst_grid_rank',) ) |
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| 302 | v_oce_grid_center_lon = f_runoff.createVariable ( 'dst_grid_center_lon', 'i4', ('dst_grid_size',) ) |
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| 303 | v_oce_grid_center_lat = f_runoff.createVariable ( 'dst_grid_center_lat', 'i4', ('dst_grid_size',) ) |
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| 304 | v_oce_grid_center_lon.units='degrees_east' ; v_oce_grid_center_lon.long_name='Longitude' ; v_oce_grid_center_lon.long_name='longitude' ; v_oce_grid_center_lon.bounds="dst_grid_corner_lon" |
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| 305 | v_oce_grid_center_lat.units='degrees_north' ; v_oce_grid_center_lat.long_name='Latitude' ; v_oce_grid_center_lat.long_name='latitude' ; v_oce_grid_center_lat.bounds="dst_grid_corner_lat" |
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| 306 | v_oce_grid_corner_lon = f_runoff.createVariable ( 'dst_grid_corner_lon', 'f8', ('dst_grid_size', 'dst_grid_corners') ) |
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| 307 | v_oce_grid_corner_lat = f_runoff.createVariable ( 'dst_grid_corner_lat', 'f8', ('dst_grid_size', 'dst_grid_corners') ) |
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| 308 | v_oce_grid_corner_lon.units="degrees_east" |
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| 309 | v_oce_grid_corner_lat.units="degrees_north" |
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| 310 | v_oce_grid_area = f_runoff.createVariable ( 'dst_grid_area' , 'f8', ('dst_grid_size',) ) |
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| 311 | v_oce_grid_area.long_name="Grid area" ; v_oce_grid_area.standard_name="cell_area" ; v_oce_grid_area.units="m2" |
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| 312 | v_oce_grid_imask = f_runoff.createVariable ( 'dst_grid_imask' , 'i4', ('dst_grid_size',) ) |
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| 313 | v_oce_grid_imask.long_name="Land-sea mask" ; v_oce_grid_imask.units="Land:1, Ocean:0" |
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| 314 | v_oce_grid_pmask = f_runoff.createVariable ( 'dst_grid_pmask' , 'i4', ('dst_grid_size',) ) |
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| 315 | v_oce_grid_pmask.long_name="Land-sea mask (periodicity removed)" ; v_oce_grid_pmask.units="Land:1, Ocean:0" |
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| 316 | |
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| 317 | v_oce_grid_dims [:] = oce_grid_dims |
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| 318 | v_oce_grid_center_lon[:] = oce_grid_center_lon[:].ravel() |
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| 319 | v_oce_grid_center_lat[:] = oce_grid_center_lat[:].ravel() |
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| 320 | v_oce_grid_corner_lon[:] = oce_grid_corner_lon.reshape( (oce_jpi*oce_jpj, d_oce_grid_corners.__len__()) ) |
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| 321 | v_oce_grid_corner_lat[:] = oce_grid_corner_lon.reshape( (oce_jpi*oce_jpj, d_oce_grid_corners.__len__()) ) |
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| 322 | v_oce_grid_area [:] = oce_grid_area[:].ravel() |
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| 323 | v_oce_grid_imask [:] = oce_grid_imask[:].ravel() |
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| 324 | v_oce_grid_pmask [:] = oce_grid_pmask[:].ravel() |
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| 325 | |
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| 326 | v_atm_lon_addressed = f_runoff.createVariable ( 'src_lon_addressed' , 'f8', ('num_links',) ) |
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| 327 | v_atm_lat_addressed = f_runoff.createVariable ( 'src_lat_addressed' , 'f8', ('num_links',) ) |
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| 328 | v_atm_area_addressed = f_runoff.createVariable ( 'src_area_addressed' , 'f8', ('num_links',) ) |
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| 329 | v_atm_imask_addressed = f_runoff.createVariable ( 'src_imask_addressed', 'i4', ('num_links',) ) |
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| 330 | v_atm_pmask_addressed = f_runoff.createVariable ( 'src_pmask_addressed', 'i4', ('num_links',) ) |
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| 331 | |
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| 332 | v_oce_lon_addressed = f_runoff.createVariable ( 'dst_lon_addressed' , 'f8', ('num_links',) ) |
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| 333 | v_oce_lat_addressed = f_runoff.createVariable ( 'dst_lat_addressed' , 'f8', ('num_links',) ) |
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| 334 | v_oce_area_addressed = f_runoff.createVariable ( 'dst_area_addressed' , 'f8', ('num_links',) ) |
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| 335 | v_oce_imask_addressed = f_runoff.createVariable ( 'dst_imask_addressed', 'i4', ('num_links',) ) |
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| 336 | v_oce_pmask_addressed = f_runoff.createVariable ( 'dst_pmask_addressed', 'i4', ('num_links',) ) |
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| 337 | |
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| 338 | v_atm_lon_addressed.long_name="Longitude" ; v_atm_lon_addressed.standard_name="longitude" ; v_atm_lon_addressed.units="degrees_east" |
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| 339 | v_atm_lat_addressed.long_name="Latitude" ; v_atm_lat_addressed.standard_name="latitude" ; v_atm_lat_addressed.units="degrees_north" |
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| 340 | v_atm_lon_addressed [:] = atm_grid_center_lon.ravel()[atm_address].ravel() |
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| 341 | v_atm_lat_addressed [:] = atm_grid_center_lat.ravel()[atm_address].ravel() |
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| 342 | v_atm_area_addressed [:] = atm_grid_area.ravel()[atm_address].ravel() |
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| 343 | v_atm_imask_addressed[:] = 1-atm_grid_imask.ravel()[atm_address].ravel() |
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| 344 | v_atm_pmask_addressed[:] = 1-atm_grid_pmask.ravel()[atm_address].ravel() |
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| 345 | |
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| 346 | v_oce_lon_addressed.long_name="Longitude" ; v_oce_lon_addressed.standard_name="longitude" ; v_oce_lon_addressed.units="degrees_east" |
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| 347 | v_oce_lat_addressed.long_name="Latitude" ; v_oce_lat_addressed.standard_name="latitude" ; v_oce_lat_addressed.units="degrees_north" |
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| 348 | v_oce_lon_addressed [:] = oce_grid_center_lon.ravel()[oce_address].ravel() |
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| 349 | v_oce_lat_addressed [:] = oce_grid_center_lat.ravel()[oce_address].ravel() |
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| 350 | v_oce_area_addressed [:] = oce_grid_area.ravel()[oce_address].ravel() |
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| 351 | v_oce_imask_addressed[:] = 1-oce_grid_imask.ravel()[oce_address].ravel() |
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| 352 | v_oce_pmask_addressed[:] = 1-oce_grid_pmask.ravel()[oce_address].ravel() |
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| 353 | |
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| 354 | v_atmLand = f_runoff.createVariable ( 'atmLand' , 'i4', ('src_grid_size',) ) |
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| 355 | v_atmLandFiltered = f_runoff.createVariable ( 'atmLandFiltered', 'f4', ('src_grid_size',) ) |
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| 356 | v_atmLandFrac = f_runoff.createVariable ( 'atmLandFrac' , 'i4', ('src_grid_size',) ) |
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| 357 | v_atmFrac = f_runoff.createVariable ( 'atmFrac' , 'i4', ('src_grid_size',) ) |
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| 358 | v_atmOcean = f_runoff.createVariable ( 'atmOcean' , 'i4', ('src_grid_size',) ) |
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| 359 | v_atmOceanFrac = f_runoff.createVariable ( 'atmOceanFrac' , 'i4', ('src_grid_size',) ) |
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| 360 | v_atmCoast = f_runoff.createVariable ( 'atmCoast' , 'i4', ('src_grid_size',) ) |
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| 361 | |
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| 362 | v_atmLand[:] = atmLand.ravel() |
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| 363 | v_atmLandFrac[:] = atmLandFrac.ravel() |
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| 364 | v_atmLandFiltered[:] = atmLandFiltered.ravel() |
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| 365 | v_atmFrac[:] = atmFrac.ravel() |
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| 366 | v_atmOcean[:] = atmOcean.ravel() |
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| 367 | v_atmOceanFrac[:] = atmOceanFrac.ravel() |
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| 368 | v_atmCoast[:] = atmCoast.ravel() |
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| 369 | |
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| 370 | v_oceLand = f_runoff.createVariable ( 'oceLand' , 'i4', ('dst_grid_size',) ) |
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| 371 | v_oceOcean = f_runoff.createVariable ( 'oceOcean' , 'i4', ('dst_grid_size',) ) |
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| 372 | v_oceOceanFiltered = f_runoff.createVariable ( 'oceOceanFiltered', 'f4', ('dst_grid_size',) ) |
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| 373 | v_oceCoast = f_runoff.createVariable ( 'oceCoast' , 'i4', ('dst_grid_size',) ) |
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| 374 | |
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| 375 | v_oceLand[:] = oceLand.ravel() |
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| 376 | v_oceOcean[:] = oceOcean.ravel() |
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| 377 | v_oceOceanFiltered[:] = oceOceanFiltered.ravel() |
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| 378 | v_oceCoast[:] = oceCoast.ravel() |
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| 379 | |
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| 380 | f_runoff.sync () |
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| 381 | |
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| 382 | ## |
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| 383 | f_runoff.close() |
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| 384 | |
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| 385 | print ('The end') |
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| 386 | |
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| 387 | ## ====================================================================================== |
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