First commit

README

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+README for py-roms2roms
+
+Version 1.0.1
+
+py-roms2roms is a Python version of roms2roms (see Mason etal, 2010 and
+www.molemaker.org) that was written in Matlab.
+
+pyroms2roms creates ROMS boundary files for offline nesting, but it has
+expanded to make:
+
+(1) boundary files with SODA, Mercator, ECCO2, IBI
+(2) forcing files using CFSR and/or CCMP.
+
+Copyright (c) 2014 by Evan Mason, IMEDEA
+Email: [email protected]

add_bry_flux_correction.py

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+# %run add_bry_flux_correction.py
+
+'''
+===========================================================================
+This file is part of py-roms2roms
+
+    py-roms2roms is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    py-roms2roms is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with py-roms2roms.  If not, see <http://www.gnu.org/licenses/>.
+
+Version 1.0.1
+
+Copyright (c) 2014 by Evan Mason, IMEDEA
+Email: [email protected]
+===========================================================================
+
+Create a forcing file based on six hourly CFSR data
+
+===========================================================================
+
+'''
+
+
+import netCDF4 as netcdf
+import matplotlib.pyplot as plt
+import numpy as np
+import time as time
+
+from py_roms2roms import RomsGrid
+
+
+
+
+
+if __name__ == '__main__':
+
+    # ROMS information
+    roms_dir = '/marula/emason/runs2014/nwmed5km/'
+
+
+    #bry_file = 'bry_nwmed5km_CORR_0pt2.nc'
+    #bry_file = 'bry_nwmed5km_VARCORR_0pt2.nc'
+    bry_file = 'bry_nwmed5km_weekly_clim_VARCORR_0pt2.nc'
+
+
+    #roms_grd = 'grd_nwmed5km.nc'
+    roms_grd = 'grd_nwmed5km_NARROW_STRAIT.nc'
+
+    variable_correction = True
+
+    flux_correction = 0.2 # Sv
+
+    open_boundary = 'east'
+
+
+    if 'roms_grd_NA2014_7pt5km.nc' in roms_grd:
+        sigma_params = dict(theta_s=6, theta_b=0, hc=120, N=32)
+        obc_dict = dict(south=1, east=1, north=1, west=1) # 1=open, 0=closed
+
+    elif 'grd_nwmed_2km.nc' in roms_grd:
+        sigma_params = dict(theta_s=6.5, theta_b=0, hc=110, N=36)
+        obc_dict = dict(south=1, east=1, north=1, west=1)
+
+    elif 'grd_na6km.nc' in roms_grd:
+        sigma_params = dict(theta_s=6., theta_b=0, hc=120, N=32)
+        obc_dict = dict(south=1, east=1, north=1, west=1)
+
+    elif 'grd_nwmed5km.nc' in roms_grd:
+        sigma_params = dict(theta_s=6.5, theta_b=0, hc=110, N=36)
+        obc_dict = dict(south=0, east=1, north=1, west=1)
+
+    elif 'grd_nwmed5km_NARROW_STRAIT.nc' in roms_grd:
+        sigma_params = dict(theta_s=6.5, theta_b=0, hc=110, N=36)
+        obc_dict = dict(south=0, east=1, north=1, west=1)
+
+    else:
+        print 'No sigma parameters defined for grid: %s' %roms_grd
+        raise Exception
+
+
+
+
+    # Set up a RomsGrid object
+    romsgrd = RomsGrid(''.join((roms_dir, roms_grd)), sigma_params, 'ROMS')
+    romsgrd.set_bry_dx()
+    romsgrd.set_bry_maskr()
+    romsgrd.set_bry_areas()
+
+    if variable_correction:
+
+        if 'west' in open_boundary:
+            bry_surface_area  = romsgrd.area_west * romsgrd.maskr_west
+        elif 'east' in open_boundary:
+            bry_surface_area  = romsgrd.area_east * romsgrd.maskr_east
+        elif 'south' in open_boundary:
+            bry_surface_area  = romsgrd.area_south * romsgrd.maskr_south
+        elif 'north' in open_boundary:
+            bry_surface_area  = romsgrd.area_north * romsgrd.maskr_north
+
+    else:
+
+        if 'west' in open_boundary:
+            bry_surface_area  = romsgrd.area_west.sum(axis=0) * romsgrd.maskr_west
+        elif 'east' in open_boundary:
+            bry_surface_area  = romsgrd.area_east.sum(axis=0) * romsgrd.maskr_east
+        elif 'south' in open_boundary:
+            bry_surface_area  = romsgrd.area_south.sum(axis=0) * romsgrd.maskr_south
+        elif 'north' in open_boundary:
+            bry_surface_area  = romsgrd.area_north.sum(axis=0) * romsgrd.maskr_north
+
+        # Velocity correction
+        correction = flux_correction * 1e6 / np.sum(bry_surface_area)
+
+
+    with netcdf.Dataset(roms_dir + bry_file, 'a') as nc:
+
+        bry_time = nc.variables['bry_time'][:]
+        tsize = bry_time.size
+        for tind in np.arange(tsize):
+            print tind, tsize
+
+            if variable_correction:
+
+                u_mask = nc.variables['u_%s' %open_boundary][tind]
+                u_mask = np.ma.masked_greater(u_mask, 0).mask
+
+                correction = flux_correction * 1e6 / np.sum(bry_surface_area * u_mask)
+
+                u = nc.variables['u_%s' %open_boundary][tind]
+                print correction
+                u[u_mask] += correction
+                nc.variables['u_%s' %open_boundary][tind] = u
+                ubar = np.sum(u *  bry_surface_area / romsgrd.dx_east, axis=0)
+                ubar /= romsgrd.h()[:,-1]
+                nc.variables['ubar_%s' %open_boundary][tind] = ubar
+
+            else:
+
+                nc.variables['u_%s' %open_boundary][tind] += correction
+                nc.variables['ubar_%s' %open_boundary][tind] += correction
+
+        nc.variables['u_%s' %open_boundary].variable_flux_correction = correction
+        nc.variables['ubar_%s' %open_boundary].variable_flux_correction = correction
+
+    print 'done'
+
+
+
+
+
+
+
+
+
+

diag_frc.py

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+# -*- coding: utf-8 -*-
+# %run diag_frc.py
+
+'''
+Compute annual means of two forcing files for comparison
+'''
+
+import netCDF4 as netcdf
+import pylab as plt
+import numpy as np
+
+def u2rho_2d(uu_in):
+    '''
+    Convert a 2D field at u points to a field at rho points
+    Checked against Jeroen's u2rho.m
+    '''
+    def uu2ur(uu_in, Mp, Lp):
+        L             = Lp - 1
+        Lm            = L  - 1
+        u_out         = np.zeros((Mp, Lp))
+        u_out[:, 1:L] = 0.5 * (uu_in[:, 0:Lm] + \
+                               uu_in[:, 1:L])
+        u_out[:, 0]   = u_out[:, 1]
+        u_out[:, L]   = u_out[:, Lm]
+        return (np.squeeze(u_out))
+    # First check to see if has time dimension
+    if uu_in.ndim < 3:
+        # No time dimension
+        Mshp, Lshp = uu_in.shape
+        u_out      = uu2ur(uu_in, Mshp, Lshp+1)
+    else:
+        # Has time dimension
+        time, Mshp, Lshp = uu_in.shape
+        u_out            = np.zeros((time, Mshp, Lshp+1))
+        for t in np.arange(time):
+            u_out[t] = uu2ur(uu_in[t], Mshp, Lshp+1)
+    return u_out
+
+
+def v2rho_2d(vv_in):
+    # Convert a 2D field at v points to a field at rho points
+    def vv2vr(vv_in, Mp, Lp):
+        M             = Mp - 1
+        Mm            = M  - 1
+        v_out         = np.zeros((Mp, Lp))
+        v_out[1:M, :] = 0.5 * (vv_in[0:Mm, :] + \
+                               vv_in[1:M, :])
+        v_out[0, :]   = v_out[1, :]
+        v_out[M, :]   = v_out[Mm, :]
+        return (np.squeeze(v_out))
+    # First check to see if has time dimension
+    if vv_in.ndim < 3:
+        # No time dimension
+        Mshp, Lshp = vv_in.shape
+        v_out      = vv2vr(vv_in, Mshp+1, Lshp)
+    else:
+        # Has time dimension
+        time, Mshp, Lshp = vv_in.shape
+        v_out            = np.zeros((time, Mshp+1, Lshp))
+        for t in np.arange(time):
+            v_out[t] = vv2vr(vv_in[t], Mshp+1, Lshp)
+    return v_out
+
+
+
+
+
+
+def get_frc(directory, frcname, varname):
+    '''
+    '''
+    nc = netcdf.Dataset(directory + frcname)
+    #lon = nc.variables['lon_rho'][:]
+    #lat = nc.variables['lat_rho'][:]
+    if 'sustr' in varname or 'svstr' in varname:
+        time = nc.variables['sms_time'][:]
+    elif 'shflux' in varname:
+        time = nc.variables['shf_time'][:]
+    elif 'swflux' in varname:
+        time = nc.variables['swf_time'][:]
+    elif 'SST' in varname or 'dQdSST' in varname:
+        time = nc.variables['sst_time'][:]
+    elif 'SSS' in varname:
+        time = nc.variables['sss_time'][:]
+    elif 'srflux' in varname or 'swrad' in varname:
+        time = nc.variables['srf_time'][:]
+
+    #print time
+    if 'sustr' in varname:
+        var = 0. * u2rho_2d(nc.variables[varname][0])
+    elif 'svstr' in varname:
+        var = 0. * v2rho_2d(nc.variables[varname][0])
+    else:
+        var = 0. * nc.variables[varname][0]
+    ind = 0
+
+    for tout in time:
+        #print ind
+        if 'sustr' in varname:
+            var += u2rho_2d(nc.variables[varname][ind])
+        elif'svstr' in varname:
+            var += v2rho_2d(nc.variables[varname][ind])
+        else:
+            var += nc.variables[varname][ind]
+        ind += 1
+
+    nc.close()
+    var /= ind
+    print 'Averaged over', ind, 'records'
+
+    return var
+
+
+
+
+plt.close('all')
+
+directory1 = '/home/emason/runs2012_tmp/MedSea5_R2.5/'
+directory2 = '/shared/emason/marula/emason/runs2012/MedSea5/'
+
+file1 = 'frc_intann_MedSea5.nc.TEST'
+file2 = 'frc_MedSea5.nc'
+
+
+grd = 'grd_MedSea5_R2.5.nc'
+
+#var = 'sustr'
+#var = 'svstr'
+#var = 'shflux'
+#var = 'swflux'
+var = 'SST'
+#var = 'SSS'
+#var = 'dQdSST'
+#var = 'swrad'
+
+
+
+#----------------------------------------------------------------
+
+nc = netcdf.Dataset(directory1 + grd)
+lon = nc.variables['lon_rho'][:]
+lat = nc.variables['lat_rho'][:]
+mask = nc.variables['mask_rho'][:]
+nc.close()
+
+var1 = get_frc(directory1, file1, var)
+var2 = get_frc(directory2, file2, var)
+
+var1 = np.ma.masked_where(mask == 0, var1)
+var2 = np.ma.masked_where(mask == 0, var2)
+
+vmin = np.ma.minimum(var1.min(), var2.min())
+vmax = np.ma.maximum(var1.max(), var2.max())
+
+
+plt.figure()
+plt.title(file1)
+plt.pcolormesh(lon, lat, var1)
+plt.axis('image')
+plt.clim(vmin, vmax)
+plt.colorbar()
+
+
+plt.figure()
+plt.title(file2)
+plt.pcolormesh(lon, lat, var2)
+plt.axis('image')
+plt.clim(vmin, vmax)
+plt.colorbar()
+
+
+plt.show()
+
+
+
+
+
+
+