paper
2020
Post-processing & calibration
Nowcasting New model or method
Classical ML (trees, GP, linear, kernels)0–6 hNOAA (incl. GFDL, PSL, GSL, NCEP/EMC)University of Oklahoma (AI2ES) Journal
2020-02-25
047
Feb 2020
Shawn L. Handler, Heather Dawn Reeves, Amy McGovern
Weather and Forecasting
NOAA (incl. GFDL, PSL, GSL, NCEP/EMC), University of Oklahoma (AI2ES)
Random forest on HRRR surface fields produces gridded CONUS probabilistic subfreezing road temperature forecasts, with a 2-h Brier skill score of 0.66.
Development of a Probabilistic Subfreezing Road Temperature Nowcast and Forecast Using Machine Learning
In one sentence. Random forest on HRRR surface fields produces gridded CONUS probabilistic subfreezing road temperature forecasts, with a 2-h Brier skill score of 0.66.
Labels
- Topic
- Post-processing & calibration, Nowcasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 0–6 h
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...), Station / in-situ
- Status
- Pre-operational / experimental
- Identifiers
- DOI:10.1175/waf-d-19-0159.1 OpenAlex:W3007591951
- Added
- 2026-10-22
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