paper
2021
Post-processing & calibration
NowcastingExtremes & hazards New model or method
CNN / U-Net0–6 h Preprint
2021-01-01
012
Jan 2021
Jason Stock, Anderson, Charles, Ebert-Uphoff, Imme et al.
Digital Collections of Colorado (Colorado State University)
Neural networks combine RAP forecasts, surface analyses and GOES-16 satellite data to correct temperature and moisture profiles for severe weather nowcasting.
Using machine learning to improve vertical profiles of temperature and moisture for severe weather nowcasting
In one sentence. Neural networks combine RAP forecasts, surface analyses and GOES-16 satellite data to correct temperature and moisture profiles for severe weather nowcasting.
Labels
- Topic
- Post-processing & calibration, Nowcasting, Extremes & hazards
- Type
- New model or method
- Method
- CNN / U-Net
- Time scale
- 0–6 h
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...), Satellite, Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.25675/3.04699 OpenAlex:W3197335227
- Added
- 2026-10-22
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