def get_observation_descriptor(self, fileName): # {{{
'''
get a MeshDescriptor for the observation grid
Parameters
----------
fileName : str
observation file name describing the source grid
Returns
-------
obsDescriptor : ``MeshDescriptor``
The descriptor for the observation grid
'''
# Authors
# -------
# Xylar Asay-Davis
# create a descriptor of the observation grid using the x/y polar
# stereographic coordinates
projection = get_antarctic_stereographic_projection()
obsDescriptor = ProjectionGridDescriptor.read(projection,
fileName=fileName,
xVarName='x',
yVarName='y')
return obsDescriptor # }}}
def get_stereographic_array_descriptor(self):
# projection for BEDMAP2 and other common Antarctic data sets
projection = pyproj.Proj('+proj=stere +lat_ts=-71.0 +lat_0=-90 '
'+lon_0=0.0 +k_0=1.0 +x_0=0.0 +y_0=0.0 '
'+ellps=WGS84')
# a square 61x61 cell map with 100 km resolution and
xMax = 3000e3
res = 100e3
nx = 2 * int(xMax / res) + 1
x = numpy.linspace(-xMax, xMax, nx)
meshName = '{}km_Antarctic_stereo'.format(int(res * 1e-3))
descriptor = ProjectionGridDescriptor.create(projection, x, x,
meshName)
return descriptor
def _get_arctic_stereographic_comparison_descriptor(config): # {{{
"""
Get a descriptor of an Arctic stereographic comparison grid, used for
remapping and determining the grid name
Parameters
----------
config : instance of ``MpasAnalysisConfigParser``
Contains configuration options
Returns
-------
descriptor : ``ProjectionGridDescriptor`` object
A descriptor of the Arctic comparison grid
"""
# Authors
# -------
# Milena Veneziani
climSection = 'climatology'
comparisonStereoWidth = config.getfloat(climSection,
'comparisonArcticStereoWidth')
comparisonStereoResolution = config.getfloat(
climSection, 'comparisonArcticStereoResolution')
projection = get_arctic_stereographic_projection()
xMax = 0.5 * comparisonStereoWidth * 1e3
nx = int(comparisonStereoWidth / comparisonStereoResolution) + 1
x = numpy.linspace(-xMax, xMax, nx)
meshName = '{}x{}km_{}km_Arctic_stereo'.format(comparisonStereoWidth,
comparisonStereoWidth,
comparisonStereoResolution)
descriptor = ProjectionGridDescriptor.create(projection, x, x, meshName)
return descriptor # }}}
def remap_rignot(inFileName,
meshFileName,
meshName,
outFileName,
mappingDirectory='.',
method='conserve',
renormalizationThreshold=None,
inVarName='melt_actual',
mpiTasks=1):
# {{{
"""
Remap the Rignot et al. (2013) melt rates at 1 km resolution to an MPAS
mesh
Parameters
----------
inFileName : str
The original Rignot et al. (2013) melt rates
meshFileName : str
The MPAS mesh
meshName : str
The name of the mesh (e.g. oEC60to30wISC), used in the name of the
mapping file
outFileName : str
The melt rates interpolated to the MPAS mesh with ocean sensible heat
fluxes added on (assuming insulating ice)
mappingDirectory : str
The directory where the mapping file should be stored (if it is to be
computed) or where it already exists (if not)
method : {'bilinear', 'neareststod', 'conserve'}, optional
The method of interpolation used, see documentation for
`ESMF_RegridWeightGen` for details.
renormalizationThreshold : float, optional
The minimum weight of a denstination cell after remapping, below
which it is masked out, or ``None`` for no renormalization and
masking.
inVarName : {'melt_actual', 'melt_steadystate'}
Whether to use the melt rate for the time period covered in Rignot et
al. (2013) with observed thinning/thickening or the melt rates that
would be required if ice shelves were in steady state.
mpiTasks : int, optional
The number of MPI tasks to use to compute the mapping file
"""
ds = xr.open_dataset(inFileName)
lx = np.abs(1e-3 * (ds.xaxis.values[-1] - ds.xaxis.values[0]))
ly = np.abs(1e-3 * (ds.yaxis.values[-1] - ds.yaxis.values[0]))
inGridName = '{}x{}km_1.0km_Antarctic_stereo'.format(lx, ly)
projection = pyproj.Proj('+proj=stere +lat_ts=-71.0 +lat_0=-90 +lon_0=0.0 '
'+k_0=1.0 +x_0=0.0 +y_0=0.0 +ellps=WGS84')
inDescriptor = ProjectionGridDescriptor.read(projection,
inFileName,
xVarName='xaxis',
yVarName='yaxis',
meshName=inGridName)
# convert to the units and variable names expected in MPAS-O
rho_fw = 1000.
s_per_yr = 365. * 24. * 60. * 60.
latent_heat_of_fusion = 3.337e5
ds['prescribedLandIceFreshwaterFlux'] = ds[inVarName] * rho_fw / s_per_yr
ds['prescribedLandIceHeatFlux'] = (latent_heat_of_fusion *
ds['prescribedLandIceFreshwaterFlux'])
ds = ds.drop_vars(['melt_actual', 'melt_steadystate', 'lon', 'lat'])
outDescriptor = MpasMeshDescriptor(meshFileName, meshName)
mappingFileName = '{}/map_{}_to_{}.nc'.format(mappingDirectory, inGridName,
meshName)
remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
remapper.build_mapping_file(method=method, mpiTasks=mpiTasks)
dsRemap = remapper.remap(ds,
renormalizationThreshold=renormalizationThreshold)
for field in [
'prescribedLandIceFreshwaterFlux', 'prescribedLandIceHeatFlux'
]:
# zero out the field where it's currently NaN
dsRemap[field] = dsRemap[field].where(dsRemap[field].nonnull(), 0.)
dsRemap.attrs['history'] = ' '.join(sys.argv)
write_netcdf(dsRemap, outFileName) # }}}
if args.method not in ['bilinear', 'neareststod', 'conserve']:
raise ValueError('Unexpected method {}'.format(args.method))
dsIn = xarray.open_dataset(args.inFileName)
x = dsIn.x.values
y = dsIn.y.values
dx = int((x[1] - x[0]) / 1000.)
Lx = int((x[-1] - x[0]) / 1000.)
Ly = int((y[-1] - y[0]) / 1000.)
inMeshName = '{}x{}km_{}km_Antarctic_stereo'.format(Lx, Ly, dx)
projection = get_antarctic_stereographic_projection()
inDescriptor = ProjectionGridDescriptor.create(projection, x, y, inMeshName)
outRes = args.resolution * 1e3
nxOut = int((x[-1] - x[0]) / outRes + 0.5) + 1
nyOut = int((y[-1] - y[0]) / outRes + 0.5) + 1
xOut = x[0] + outRes * numpy.arange(nxOut)
yOut = y[0] + outRes * numpy.arange(nyOut)
outMeshName = '{}x{}km_{}km_Antarctic_stereo'.format(Lx, Ly, args.resolution)
outDescriptor = ProjectionGridDescriptor.create(projection, xOut, yOut,
outMeshName)
mappingFileName = 'map_{}_to_{}_{}.nc'.format(inMeshName, outMeshName,
