ML4WX

Hybrid physics-ML & parameterization

Using deep learning to emulate and accelerate a radiative-transfer model

Ryan Lagerquist, David D. Turner, Imme Ebert‐Uphoff, Jebb Q. Stewart, Venita Hagerty

Journal of Atmospheric and Oceanic Technology · · NOAA (incl. GFDL, PSL, GSL, NCEP/EMC), Colorado State University (incl. CIRA)

PaperPDF

In one sentence. Knowledge-guided U-Net++ emulates the RRTM shortwave radiation scheme for NWP, running about 10^4 times faster with good tropical generalization.

Labels

Topic
Hybrid physics-ML & parameterization
Type
New model or method
Method
CNN / U-Net
Domain
Global
Data
Other
Status
Pre-operational / experimental
Identifiers
DOI:10.1175/jtech-d-21-0007.1 OpenAlex:W3186737891
Added
2026-10-22

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