"""Read ERA5 2D Wave Spectra NetCDF files"""
import numpy as np
import xarray as xr
from xarray.backends import BackendEntrypoint
from wavespectra.core.utils import create_frequencies
from wavespectra.core.attributes import attrs, set_spec_attributes
MAPPING = {
"time": attrs.TIMENAME,
"valid_time": attrs.TIMENAME,
"frequency": attrs.FREQNAME,
"frequencyNumber": attrs.FREQNAME,
"direction": attrs.DIRNAME,
"directionNumber": attrs.DIRNAME,
"d2fd": attrs.SPECNAME,
"longitude": attrs.LONNAME,
"latitude": attrs.LATNAME,
}
[docs]
def read_era5(filename_or_fileglob, chunks={}, f0=0.03453, df=1.1, as_site=False):
"""Read Spectra from ECMWF ERA5 netCDF format.
Args:
- filename_or_fileglob (str, list, filelike): filename, fileglob specifying multiple
files, or filelike object to read.
- chunks (dict): chunk sizes for dimensions in dataset. By default
dataset is loaded using single chunk for all dimensions (see
xr.open_mfdataset documentation).
- f0 (float): First frequency value in Hz (e.g., 0.03453)
- df (float): Multiplicative increment between frequencies.
- as_site (bool): If True locations are defined by 1D site dimension.
Returns:
- dset (SpecDataset): spectra dataset object read from netcdf file.
Note:
- This reader also supports ECMWF spectra from the operational forecast.
- Documentation describing how to construct the spectral grid can be found at
https://www.ecmwf.int/en/forecasts/documentation-and-support/2d-wave-spectra.
- If file is large to fit in memory, consider specifying chunks for
'time' and/or 'latitude/longitude' dims.
"""
dset = xr.open_dataset(filename_or_fileglob).chunk(chunks)
return from_era5(dset, f0=f0, df=df, as_site=as_site)
def from_era5(dset, f0=0.03453, df=1.1, as_site=False):
"""Format ERA5 netcdf dataset to receive wavespectra accessor.
Args:
- dset (xr.Dataset): Dataset created from a ERA5 netcdf file.
- f0 (float): First frequency value in Hz (e.g., 0.03453)
- df (float): Multiplicative increment between frequencies.
- as_site (bool): If True locations are defined by 1D site dimension.
Returns:
- Formated dataset with the SpecDataset accessor in the `spec` namespace.
"""
mapping = {k: v for k, v in MAPPING.items() if k != v and k in dset.variables}
dset = dset.rename(mapping).reset_coords(drop=True)
# Convert ERA5 format to wavespectra format
dset[attrs.SPECNAME] = 10 ** dset[attrs.SPECNAME] * np.pi / 180
dset[attrs.SPECNAME] = dset[attrs.SPECNAME].fillna(0)
# Assign the logarithmic frequency grid
dset[attrs.FREQNAME] = create_frequencies(f0, dset[attrs.FREQNAME].size, df)
# Assign the coming-from direction grid
dd = 360 / dset[attrs.DIRNAME].size
dset[attrs.DIRNAME] = ((np.arange(0, 360, dd) + dd / 2) + 180) % 360
# Stack lat/lon dimensions if as_site is True
if as_site:
dset = (
dset.stack(site=[attrs.LATNAME, attrs.LONNAME], create_index=False)
.reset_coords()
.transpose(attrs.TIMENAME, attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME)
)
# Setting standard attributes
set_spec_attributes(dset)
return dset
class ERA5BackendEntrypoint(BackendEntrypoint):
"""ERA5 backend engine."""
def open_dataset(
self,
filename_or_obj,
*,
drop_variables=None,
f0=0.03453,
df=1.1,
as_site=False,
):
return read_era5(filename_or_obj, f0=f0, df=df)
def guess_can_open(self, filename_or_obj):
return False
description = "Open ERA5 netcdf spectra files as a wavespectra dataset."
url = "https://github.com/wavespectra/wavespectra"
