paper
2005
Hybrid physics-ML & parameterization
Climate emulation New model or method
Classical ML (trees, GP, linear, kernels)NOAA (incl. GFDL, PSL, GSL, NCEP/EMC) Journal
★ Highlight 2005-05-01
069
May 2005
Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, Dmitry V. Chalikov
Monthly Weather Review
NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)
Neural network emulates CAM longwave radiation 50-80 times faster with near-identical 10-year climate simulations, an early ML physics emulation.
1
Hybrid physics-ML & parameterization★ HighlightClassic
New Approach to Calculation of Atmospheric Model Physics: Accurate and Fast Neural Network Emulation of Longwave Radiation in a Climate Model
Why it matters. Seminal NN emulation of CAM longwave radiation, 50-80x speedup with stable climate runs; foundational for ML physics emulation.
In one sentence. Neural network emulates CAM longwave radiation 50-80 times faster with near-identical 10-year climate simulations, an early ML physics emulation.
Labels
- Topic
- Hybrid physics-ML & parameterization, Climate emulation
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1175/mwr2923.1 OpenAlex:W2047421660
- Added
- 2026-10-22
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