A package focus on fecth open-source global numerical weather prediction product in a elegant way.
The following data sources are supported.
✔︎ Deutscher Wetterdientst - ICON
✔︎ European Centre for Medium-Range Weather Forecasts - OPER / ENFO
✔︎ Canadian Meteorological Center - GEM / GEPS
The following data sources support is coming. 🚀🚀🚀
❏ National Oceanic and Atmospheric Adminstration - GFS
❏ Met Office - MOGREPS (not open-source anymore)
maesters-nwp depends on cdo. And as cdo is not supported on Windows platform, maesters-nwp fail to install on Windows.
conda install -c conda-forge maesters-nwpconda install -c conda-forge cdo curl- Install maesters-nwp
pip install maesters-nwpfrom maesters import Maester
# instantiate with source, product, batch (batch start time), hour (predict hour from bacth start time)
ec = Maester(source='ecmwf', product='oper', batch='2022-08-22 12:00',hour=[6,30],varname='TP_SFC')
# or instantiate with source, product, date (predict time), batch (use newest bacth if batch is not given)
ec = Maester(source='ecmwf', product='oper', date='2022-08-23 18:00', varname='TMP_SFC')
# get xarray object
ec.xarray()
# or only download (if lcoal_dir is not given, default download to current dir)
ec.download(local_dir='./')
# or operation download all data of the newest batch, default download to $HOME/data/{source}/{product}/{batch:%Y%m%d%H0000}
ec.operation(local_dir='./')
# more usage examples in example/example.ipynb| Source | Variable |
|---|---|
| ecmwf | variables |
| dwd | variables |
| cmc | variables |
P1: pyporj instal fail on M1 chip
S1:
brew install proj
pip install pyprojIf this package give helps to your research or work, it will be a enjoyable thing to the contributors of this package. And if you are willing to cite the contribution of this package in your publication, you can find the DOI information at https://doi.org/10.5281/zenodo.6796046.