lat/lon and local-cartesian regridding
Project description
regridcart Regridding lat/lon to local Cartesian coordinates
This package takes care of regridding data defined with latitude/longitude
coordinates onto a local Cartesian grid of a fixed resolution. To use it you
simply define the domain you want to regrid onto and then call the resample
method.
Usage
import regridcart as rc
import xaray as xr
da_src = xr.open_dataarray("...")
target_domain = rc.LocalCartesianDomain(
central_latitude=lat0,
central_longitude=lon0,
l_meridional=1000.0e3,
l_zonal=3000.0e3,
)
dx = 1.0e3 # new resoluion 1km
da_regridded = rc.resample(target_domain, da=da_src, dx=dx)
The provided data-array is assumed to have latitude/longitude coordinates defined by one of the following:
latandloncoordinates along which the data is aligned, i.e.latandlonare given as 1D arrayslatandlonare given as auxilliary variables so that the data isn't aligned along the lat/lon directions, but rather thelatandlonof every datapoint is given- the data-array has projection information defined in a CF-compliant
manner using the
grid_mappingattribute (http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/build/ch05s06.html) - the data-array was loaded from a raster-file using
rioxarray.open_rasterioso that the projection information is available viada.rio.crs
The package also implements cropping (rc.crop_field_to_domain), plotting
domain outline (domain.plot_outline) and can also with data already on a
Cartesian grid with rc.CartesianDomain. See
notebooks/examples.ipynb for detailed examples.
Installation
regridcart can be installed with pip from pypi, but it
relies on cartopy and xesmf which in turn rely on proj and emsf, these
can most easily be installed with
conda:
conda install xarray cartopy xesmf -c conda-forge
pip install regridcart
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