paper
2022
Post-processing & calibration
Probabilistic & ensemble forecasting New model or method
CNN / U-Net3–15 daysNSF NCAR / UCAR Journal
2022-04-04
051
Apr 2022
Yingkai Sha, David John Gagne, Gregory West et al.
Monthly Weather Review
NSF NCAR / UCAR
Hybrid analog-ensemble and CNN post-processing of GEFS precipitation raises CRPSS about 10% over quantile-mapped baseline out to 7 days in British Columbia.
A hybrid analog-ensemble, convolutional-neural-network method for post-processing precipitation forecasts
In one sentence. Hybrid analog-ensemble and CNN post-processing of GEFS precipitation raises CRPSS about 10% over quantile-mapped baseline out to 7 days in British Columbia.
Labels
- Topic
- Post-processing & calibration, Probabilistic & ensemble forecasting
- Type
- New model or method
- Method
- CNN / U-Net
- Time scale
- 3–15 days
- Domain
- Regional
- Data
- ERA5 / reanalysis, NWP analysis or forecasts (IFS, GFS, ...), Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1175/mwr-d-21-0154.1 OpenAlex:W4225553680
- Added
- 2026-10-22
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