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diag_frc.py
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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()