paper
2023
Hybrid physics-ML & parameterization
New model or method
CNN / U-NetColorado State University (incl. CIRA)NOAA (incl. GFDL, PSL, GSL, NCEP/EMC) Other
2023-05-04
055
May 2023
Ryan Lagerquist, David D. Turner, Imme Ebert‐Uphoff et al.
preprint
Colorado State University (incl. CIRA), NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)
Neural networks emulate the full shortwave and longwave RRTM radiation scheme for GFSv16, running 6579x and 96x faster than the original with near-zero bias.
Hybrid physics-ML & parameterization
Estimating full longwave and shortwave radiative transfer with neural
In one sentence. Neural networks emulate the full shortwave and longwave RRTM radiation scheme for GFSv16, running 6579x and 96x faster than the original with near-zero bias.
Labels
- Topic
- Hybrid physics-ML & parameterization
- Type
- New model or method
- Method
- CNN / U-Net
- Domain
- Global
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Pre-operational / experimental
- Identifiers
- DOI:10.22541/essoar.168319865.58439449/v1 OpenAlex:W4368372152
- Added
- 2026-10-22
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