def _setup_remappers(self): # {{{
"""
Set up the remappers for remapping from the MPAS to the comparison
grids.
"""
# Authors
# -------
# Xylar Asay-Davis
config = self.config
# make reamppers
mappingFilePrefix = 'map'
self.remappers = {}
for comparisonGridName in self.comparisonDescriptors:
comparisonDescriptor = \
self.comparisonDescriptors[comparisonGridName]
self.comparisonGridName = comparisonDescriptor.meshName
mpasDescriptor = MpasMeshDescriptor(self.restartFileName,
meshName=config.get(
'input', 'mpasMeshName'))
self.mpasMeshName = mpasDescriptor.meshName
self.remappers[comparisonGridName] = get_remapper(
config=config,
sourceDescriptor=mpasDescriptor,
comparisonDescriptor=comparisonDescriptor,
mappingFilePrefix=mappingFilePrefix,
method=config.get('climatology', 'mpasInterpolationMethod'),
logger=self.logger)
def make_analysis_polar_map(config, mesh_name, projection):
# {{{
mesh_filename = '../mesh.nc'
upperProj = projection[0].upper() + projection[1:]
inDescriptor = MpasMeshDescriptor(mesh_filename, mesh_name)
comparisonStereoWidth = config.getfloat(
'mapping_analysis', 'comparison{}StereoWidth'.format(upperProj))
comparisonStereoResolution = config.getfloat(
'mapping_analysis', 'comparison{}StereoResolution'.format(upperProj))
outDescriptor = get_polar_descriptor(Lx=comparisonStereoWidth,
Ly=comparisonStereoWidth,
dx=comparisonStereoResolution,
dy=comparisonStereoResolution,
projection=projection)
outGridName = '{}x{}km_{}km_{}_stereo'.format(comparisonStereoWidth,
comparisonStereoWidth,
comparisonStereoResolution,
upperProj)
mappingFileName = 'map_{}_to_{}_bilinear.nc'.format(mesh_name, outGridName)
remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
mpiTasks = config.getint('main', 'nprocs')
remapper.build_mapping_file(method='bilinear',
mpiTasks=mpiTasks,
tempdir='.')
def setup_mpas_remapper(self, config):
mpasMeshFileName = '{}/mpasMesh.nc'.format(self.datadir)
comparisonDescriptor = \
get_comparison_descriptor(config, comparisonGridName='latlon')
mpasDescriptor = MpasMeshDescriptor(
mpasMeshFileName, meshName=config.get('input', 'mpasMeshName'))
remapper = get_remapper(
config=config, sourceDescriptor=mpasDescriptor,
comparisonDescriptor=comparisonDescriptor,
mappingFilePrefix='map', method=config.get(
'climatology', 'mpasInterpolationMethod'))
return remapper
def _make_analysis_lat_lon_map(config, mesh_name, cores, logger):
mesh_filename = 'restart.nc'
inDescriptor = MpasMeshDescriptor(mesh_filename, mesh_name)
comparisonLatResolution = config.getfloat('files_for_e3sm',
'comparisonLatResolution')
comparisonLonResolution = config.getfloat('files_for_e3sm',
'comparisonLonResolution')
# modify the resolution of the global lat-lon grid as desired
outDescriptor = get_lat_lon_descriptor(dLon=comparisonLatResolution,
dLat=comparisonLonResolution)
outGridName = outDescriptor.meshName
_make_mapping_file(mesh_name, outGridName, inDescriptor, outDescriptor,
cores, config, logger)
def make_analysis_lat_lon_map(config, mesh_name):
# {{{
mesh_filename = '../mesh.nc'
inDescriptor = MpasMeshDescriptor(mesh_filename, mesh_name)
comparisonLatResolution = config.getfloat('mapping_analysis',
'comparisonLatResolution')
comparisonLonResolution = config.getfloat('mapping_analysis',
'comparisonLonResolution')
# modify the resolution of the global lat-lon grid as desired
outDescriptor = get_lat_lon_descriptor(dLon=comparisonLatResolution,
dLat=comparisonLonResolution)
outGridName = outDescriptor.meshName
mappingFileName = 'map_{}_to_{}_bilinear.nc'.format(mesh_name, outGridName)
remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
mpiTasks = config.getint('main', 'nprocs')
remapper.build_mapping_file(method='bilinear', mpiTasks=mpiTasks,
tempdir='.')
def _make_analysis_polar_map(config, mesh_name, projection, cores, logger):
mesh_filename = 'restart.nc'
upperProj = projection[0].upper() + projection[1:]
inDescriptor = MpasMeshDescriptor(mesh_filename, mesh_name)
comparisonStereoWidth = config.getfloat(
'files_for_e3sm', 'comparison{}StereoWidth'.format(upperProj))
comparisonStereoResolution = config.getfloat(
'files_for_e3sm', 'comparison{}StereoResolution'.format(upperProj))
outDescriptor = get_polar_descriptor(Lx=comparisonStereoWidth,
Ly=comparisonStereoWidth,
dx=comparisonStereoResolution,
dy=comparisonStereoResolution,
projection=projection)
outGridName = '{}x{}km_{}km_{}_stereo'.format(
comparisonStereoWidth, comparisonStereoWidth,
comparisonStereoResolution, upperProj)
_make_mapping_file(mesh_name, outGridName, inDescriptor, outDescriptor,
cores, config, logger)
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) # }}}
def get_mpas_descriptor(self):
mpasMeshFileName = str(self.datadir.join('mpasMesh.nc'))
timeSeriesFileName = str(self.datadir.join('timeSeries.0002-01-01.nc'))
descriptor = MpasMeshDescriptor(mpasMeshFileName, meshName='oQU240')
return (descriptor, mpasMeshFileName, timeSeriesFileName)
resolution.
'''
import xarray
from pyremap import MpasMeshDescriptor, Remapper, get_polar_descriptor
# replace with the MPAS mesh name
inGridName = 'oQU240'
# replace with the path to the desired mesh or restart file
# As an example, use:
# https://web.lcrc.anl.gov/public/e3sm/inputdata/ocn/mpas-o/oQU240/ocean.QU.240km.151209.nc
inGridFileName = 'ocean.QU.240km.151209.nc'
inDescriptor = MpasMeshDescriptor(inGridFileName, inGridName)
# modify the size and resolution of the Antarctic grid as desired
outDescriptor = get_polar_descriptor(Lx=6000.,
Ly=6000.,
dx=10.,
dy=10.,
projection='antarctic')
outGridName = outDescriptor.meshName
mappingFileName = 'map_{}_to_{}_conserve.nc'.format(inGridName, outGridName)
remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
# conservative remapping with 4 MPI tasks (using mpirun)
remapper.build_mapping_file(method='conserve', mpiTasks=4)