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blaylockbk / Herbie

Download numerical weather prediction datasets (HRRR, RAP, GFS, IFS, etc.) from NOMADS, NODD partners (Amazon, Google, Microsoft), ECMWF open data, and the University of Utah Pando Archive System.
https://herbie.readthedocs.io/
MIT License
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Update ECMWF serchStrin_help #307

Closed williamhobbs closed 5 months ago

williamhobbs commented 5 months ago

I think this needs to be updated now that ECMWF makes more parameters available. For example, 100 meter (metre) wind.

https://github.com/blaylockbk/Herbie/blob/f31d06c79264639131caf0491230c9d2f392b34e/herbie/help.py#L57-L102

blaylockbk commented 5 months ago

I don't see the 100-m wind product. Can you point me to it?

williamhobbs commented 5 months ago

If I run 

H=Herbie('2024-4-18 ', model='ifs', product='oper', fxx=39)
H.inventory().param.unique()

it returns:

array(['tp', 'cape', '10v', 'gh', 'u', 'v', 'r', '100v', 't', '100u',
       'skt', 'ssrd', 'sp', 'st', 'swvl1', 'msl', 'swvl2', '10u', '2d',
       'swvl4', '2t', 'stl4', 'swvl3', 'stl2', 'stl3', 'ssr', 'w', 'tcwv',
       'q', 'lsm', 'strd', 'd', 'str', 'vo', 'ro', 'asn', 'ttr'],
      dtype=object)

Not sure if that's the cleanest way to do it, but it includes 100u and 100v. ssrd is also new and useful.

Edit to add:

Here's an announcement on new data: https://www.ecmwf.int/en/about/media-centre/news/2024/ecmwf-releases-much-larger-open-dataset.

See https://www.ecmwf.int/en/forecasts/datasets/open-data, which can be compared with the archived version of that page from last year: https://web.archive.org/web/20230324011508/https://www.ecmwf.int/en/forecasts/datasets/open-data.

blaylockbk commented 5 months ago

Ah gotcha. I was looking at a date older than the new dataset. Thanks.

blaylockbk commented 5 months ago

I updated some examples in https://github.com/blaylockbk/Herbie/commit/3201f13ce4cf84ff878772634d3a0c743ba069bc. Thanks for the suggestion.