def ua_topo(lon,
lat,
ua_file,
nc_out,
grounded_iceberg=True,
topo_dir=None,
rtopo_file=None):
from plot_latlon import plot_tmp_domain
if grounded_iceberg:
if topo_dir is None and rtopo_file is None:
print 'Error (ua_topo): must set topo_dir or rtopo_file if grounded_iceberg is True'
sys.exit()
if rtopo_file is None:
rtopo_file = topo_dir + 'RTopo-2.0.1_30sec_aux.nc'
print 'Reading ' + ua_file
f = loadmat(ua_file)
bathy = np.transpose(f['bathy'])
draft = np.transpose(f['draft'])
omask = np.transpose(f['omask'])
imask = np.transpose(f['imask'])
if (bathy.shape[0] != len(lat) - 1) or (bathy.shape[1] != len(lon) - 1):
print 'Error (ua_topo): The fields in ' + ua_file + ' do not agree with the dimensions of your latitude and longitude.'
sys.exit()
if grounded_iceberg:
bathy, omask = add_grounded_iceberg(rtopo_file, lon, lat, bathy, omask)
print 'Plotting'
lon_2d, lat_2d = np.meshgrid(lon, lat)
plot_tmp_domain(lon_2d, lat_2d, bathy, title='Bathymetry (m)')
plot_tmp_domain(lon_2d, lat_2d, draft, title='Ice shelf draft (m)')
plot_tmp_domain(lon_2d,
lat_2d,
draft - bathy,
title='Water column thickness (m)')
plot_tmp_domain(lon_2d, lat_2d, omask, title='Ocean mask')
plot_tmp_domain(lon_2d, lat_2d, imask, title='Ice mask')
# Write to NetCDF file (at cell centres not edges!)
ncfile = NCfile_basiclatlon(nc_out, 0.5 * (lon[1:] + lon[:-1]),
0.5 * (lat[1:] + lat[:-1]))
ncfile.add_variable('bathy', bathy, units='m')
ncfile.add_variable('draft', draft, units='m')
ncfile.add_variable('omask', omask)
ncfile.add_variable('imask', imask)
ncfile.close()
print 'The results have been written into ' + nc_out
print 'Take a look at this file and make whatever edits you would like to the mask (eg removing everything west of the peninsula; you can use edit_mask if you like)'
print "Then set your vertical layer thicknesses in a plain-text file, one value per line (make sure they clear the deepest bathymetry of " + str(
abs(np.amin(bathy))) + " m), and run remove_grid_problems"
def interp_bedmap2 (lon, lat, topo_dir, nc_out, bed_file=None, grounded_iceberg=False, rtopo_file=None):
import netCDF4 as nc
from plot_latlon import plot_tmp_domain
topo_dir = real_dir(topo_dir)
# BEDMAP2 file names
surface_file = topo_dir+'bedmap2_surface.flt'
thickness_file = topo_dir+'bedmap2_thickness.flt'
mask_file = topo_dir+'bedmap2_icemask_grounded_and_shelves.flt'
if bed_file is None:
bed_file = topo_dir+'bedmap2_bed.flt'
# GEBCO file name
gebco_file = topo_dir+'GEBCO_2014_2D.nc'
if grounded_iceberg and (rtopo_file is None):
# RTopo-2 file name (auxiliary file including masks)
rtopo_file = topo_dir+'RTopo-2.0.1_30sec_aux.nc'
if np.amin(lat) > -60:
print "Error (interp_bedmap2): this domain doesn't go south of 60S, so it's not covered by BEDMAP2."
sys.exit()
if np.amax(lat) > -60:
use_gebco = True
# Find the first index north of 60S
j_split = np.nonzero(lat >= -60)[0][0]
# Split grid into a BEDMAP2 section and a GEBCO section (remembering lat is edges, not centres, so lat[j_split-1] is in both sections)
lat_b = lat[:j_split]
lat_g = lat[j_split-1:]
else:
use_gebco = False
lat_b = lat
# Set up BEDMAP grid (polar stereographic)
x = np.arange(-bedmap_bdry, bedmap_bdry+bedmap_res, bedmap_res)
y = np.arange(-bedmap_bdry, bedmap_bdry+bedmap_res, bedmap_res)
print 'Reading data'
# Have to flip it vertically so lon0=0 in polar stereographic projection
# Otherwise, lon0=180 which makes x_interp and y_interp strictly decreasing when we call polar_stereo later, and the interpolation chokes
bathy = np.flipud(np.fromfile(bed_file, dtype='<f4').reshape([bedmap_dim, bedmap_dim]))
surf = np.flipud(np.fromfile(surface_file, dtype='<f4').reshape([bedmap_dim, bedmap_dim]))
thick = np.flipud(np.fromfile(thickness_file, dtype='<f4').reshape([bedmap_dim, bedmap_dim]))
mask = np.flipud(np.fromfile(mask_file, dtype='<f4').reshape([bedmap_dim, bedmap_dim]))
if np.amax(lat_b) > -61:
print 'Extending bathymetry past 60S'
# Bathymetry has missing values north of 60S. Extend into that mask so there are no artifacts in the splines near 60S.
bathy = extend_into_mask(bathy, missing_val=bedmap_missing_val, num_iters=5)
print 'Calculating ice shelf draft'
# Calculate ice shelf draft from ice surface and ice thickness
draft = surf - thick
print 'Calculating ocean and ice masks'
# Mask: -9999 is open ocean, 0 is grounded ice, 1 is ice shelf
# Make an ocean mask and an ice mask. Ice shelves are in both.
omask = (mask!=0).astype(float)
imask = (mask!=-9999).astype(float)
# Convert lon and lat to polar stereographic coordinates
lon_2d, lat_2d = np.meshgrid(lon, lat_b)
x_interp, y_interp = polar_stereo(lon_2d, lat_2d)
# Interpolate fields
print 'Interpolating bathymetry'
bathy_interp = interp_topo(x, y, bathy, x_interp, y_interp)
print 'Interpolating ice shelf draft'
draft_interp = interp_topo(x, y, draft, x_interp, y_interp)
print 'Interpolating ocean mask'
omask_interp = interp_topo(x, y, omask, x_interp, y_interp)
print 'Interpolating ice mask'
imask_interp = interp_topo(x, y, imask, x_interp, y_interp)
if use_gebco:
print 'Filling in section north of 60S with GEBCO data'
print 'Reading data'
id = nc.Dataset(gebco_file, 'r')
lat_gebco_grid = id.variables['lat'][:]
lon_gebco_grid = id.variables['lon'][:]
# Figure out which indices we actually care about - buffer zone of 5 cells so the splines have room to breathe
j_start = max(np.nonzero(lat_gebco_grid >= lat_g[0])[0][0] - 1 - 5, 0)
j_end = min(np.nonzero(lat_gebco_grid >= lat_g[-1])[0][0] + 5, lat_gebco_grid.size-1)
i_start = max(np.nonzero(lon_gebco_grid >= lon[0])[0][0] - 1 - 5, 0)
i_end = min(np.nonzero(lon_gebco_grid >= lon[-1])[0][0] + 5, lon_gebco_grid.size-1)
# Read GEBCO bathymetry just from this section
bathy_gebco = id.variables['elevation'][j_start:j_end, i_start:i_end]
id.close()
# Trim the grid too
lat_gebco_grid = lat_gebco_grid[j_start:j_end]
lon_gebco_grid = lon_gebco_grid[i_start:i_end]
print 'Interpolating bathymetry'
lon_2d, lat_2d = np.meshgrid(lon, lat_g)
bathy_gebco_interp = interp_topo(lon_gebco_grid, lat_gebco_grid, bathy_gebco, lon_2d, lat_2d)
print 'Combining BEDMAP2 and GEBCO sections'
# Deep copy the BEDMAP2 section of each field
bathy_bedmap_interp = np.copy(bathy_interp)
draft_bedmap_interp = np.copy(draft_interp)
omask_bedmap_interp = np.copy(omask_interp)
imask_bedmap_interp = np.copy(imask_interp)
# Now combine them (remember we interpolated to the centres of grid cells, but lat and lon arrays define the edges, so minus 1 in each dimension)
bathy_interp = np.empty([lat.size-1, lon.size-1])
bathy_interp[:j_split-1,:] = bathy_bedmap_interp
bathy_interp[j_split-1:,:] = bathy_gebco_interp
# Ice shelf draft will be 0 in GEBCO region
draft_interp = np.zeros([lat.size-1, lon.size-1])
draft_interp[:j_split-1,:] = draft_bedmap_interp
# Set ocean mask to 1 in GEBCO region; any land points will be updated later based on bathymetry > 0
omask_interp = np.ones([lat.size-1, lon.size-1])
omask_interp[:j_split-1,:] = omask_bedmap_interp
# Ice mask will be 0 in GEBCO region
imask_interp = np.zeros([lat.size-1, lon.size-1])
imask_interp[:j_split-1,:] = imask_bedmap_interp
print 'Processing masks'
# Deal with values interpolated between 0 and 1
omask_interp[omask_interp < 0.5] = 0
omask_interp[omask_interp >= 0.5] = 1
imask_interp[imask_interp < 0.5] = 0
imask_interp[imask_interp >= 0.5] = 1
# Zero out bathymetry and ice shelf draft on land
bathy_interp[omask_interp==0] = 0
draft_interp[omask_interp==0] = 0
# Zero out ice shelf draft in the open ocean
draft_interp[imask_interp==0] = 0
# Update masks due to interpolation changing their boundaries
# Anything with positive bathymetry should be land
index = bathy_interp > 0
omask_interp[index] = 0
bathy_interp[index] = 0
draft_interp[index] = 0
# Anything with negative or zero water column thickness should be land
index = draft_interp - bathy_interp <= 0
omask_interp[index] = 0
bathy_interp[index] = 0
draft_interp[index] = 0
# Anything with positive ice shelf draft should be land
index = draft_interp > 0
omask_interp[index] = 0
bathy_interp[index] = 0
draft_interp[index] = 0
# Any points with zero ice shelf draft should not be in the ice mask
# (This will also remove grounded ice, and ice shelves with total thickness (draft + freeboard) thinner than firn_air)
index = draft_interp == 0
imask_interp[index] = 0
print 'Removing isolated ocean cells'
omask_interp = remove_isolated_cells(omask_interp)
bathy_interp[omask_interp==0] = 0
draft_interp[omask_interp==0] = 0
imask_interp[omask_interp==0] = 0
print 'Removing isolated ice shelf cells'
imask_interp = remove_isolated_cells(imask_interp)
draft_interp[imask_interp==0] = 0
if grounded_iceberg:
bathy_interp, omask_interp = add_grounded_iceberg(rtopo_file, lon, lat, bathy_interp, omask_interp)
print 'Plotting'
if use_gebco:
# Remesh the grid, using the full latitude array
lon_2d, lat_2d = np.meshgrid(lon, lat)
plot_tmp_domain(lon_2d, lat_2d, bathy_interp, title='Bathymetry (m)')
plot_tmp_domain(lon_2d, lat_2d, draft_interp, title='Ice shelf draft (m)')
plot_tmp_domain(lon_2d, lat_2d, draft_interp - bathy_interp, title='Water column thickness (m)')
plot_tmp_domain(lon_2d, lat_2d, omask_interp, title='Ocean mask')
plot_tmp_domain(lon_2d, lat_2d, imask_interp, title='Ice mask')
# Write to NetCDF file (at cell centres not edges!)
ncfile = NCfile_basiclatlon(nc_out, 0.5*(lon[1:] + lon[:-1]), 0.5*(lat[1:] + lat[:-1]))
ncfile.add_variable('bathy', bathy_interp, units='m')
ncfile.add_variable('draft', draft_interp, units='m')
ncfile.add_variable('omask', omask_interp)
ncfile.add_variable('imask', imask_interp)
ncfile.close()
print 'The results have been written into ' + nc_out
print 'Take a look at this file and make whatever edits you would like to the mask (eg removing everything west of the peninsula; you can use edit_mask if you like)'
print "Then set your vertical layer thicknesses in a plain-text file, one value per line (make sure they clear the deepest bathymetry of " + str(abs(np.amin(bathy_interp))) + " m), and run remove_grid_problems"