def iceberg_meltwater(grid_path, input_dir, output_file, nc_out=None, prec=32):
from plot_latlon import latlon_plot
input_dir = real_dir(input_dir)
file_head = 'icebergs_'
file_tail = '.nc'
print 'Building grids'
# Read the NEMO grid from the first file
# It has longitude in the range -180 to 180
file_path = input_dir + file_head + '01' + file_tail
nemo_lon = read_netcdf(file_path, 'nav_lon')
nemo_lat = read_netcdf(file_path, 'nav_lat')
# Build the model grid
model_grid = Grid(grid_path, max_lon=180)
print 'Interpolating'
icebergs_interp = np.zeros([12, model_grid.ny, model_grid.nx])
for month in range(12):
print '...month ' + str(month + 1)
# Read the data
file_path = input_dir + file_head + '{0:02d}'.format(month +
1) + file_tail
icebergs = read_netcdf(file_path, 'berg_total_melt', time_index=0)
# Interpolate
icebergs_interp_tmp = interp_nonreg_xy(nemo_lon,
nemo_lat,
icebergs,
model_grid.lon_1d,
model_grid.lat_1d,
fill_value=0)
# Make sure the land and ice shelf cavities don't get any iceberg melt
icebergs_interp_tmp[model_grid.land_mask + model_grid.ice_mask] = 0
# Save to the master array
icebergs_interp[month, :] = icebergs_interp_tmp
write_binary(icebergs_interp, output_file, prec=prec)
print 'Plotting'
# Make a nice plot of the annual mean
latlon_plot(mask_land_ice(np.mean(icebergs_interp, axis=0), model_grid),
model_grid,
include_shelf=False,
vmin=0,
title=r'Annual mean iceberg melt (kg/m$^2$/s)')
if nc_out is not None:
# Also write to NetCDF file
print 'Writing ' + nc_out
ncfile = NCfile(nc_out, model_grid, 'xyt')
ncfile.add_time(np.arange(12) + 1, units='months')
ncfile.add_variable('iceberg_melt',
icebergs_interp,
'xyt',
units='kg/m^2/s')
ncfile.close()
def read_data(file_path):
f = loadmat(file_path)
x, y, connectivity = read_ua_mesh(f)
# Set up regular grid. This will be the same for both steps because the boundary is fixed.
x_reg = np.linspace(np.amin(x), np.amax(x), num=nx)
y_reg = np.linspace(np.amin(y), np.amax(y), num=ny)
if var == 'velb':
data = np.sqrt(f['ub'][:, 0]**2 + f['vb'][:, 0]**2)
else:
data = f[var][:, 0]
data_reg = interp_nonreg_xy(x, y, data, x_reg, y_reg)
if mask is not None:
# Read ice base elevation and bedrock depth
ice_base = f['b'][:, 0]
bedrock = f['B'][:, 0]
flt_mask = interp_nonreg_xy(x, y,
(ice_base > bedrock).astype(float),
x_reg, y_reg)
flt_mask[flt_mask < 0.5] = 0
flt_mask[flt_mask >= 0.5] = 1
else:
flt_mask = None
return x_reg, y_reg, data_reg, flt_mask