paper
2020
Post-processing & calibration
Sub-seasonal to seasonal New model or method
Classical ML (trees, GP, linear, kernels)CNN / U-Net2 weeks–2 monthsNOAA (incl. GFDL, PSL, GSL, NCEP/EMC) Journal
2020-08-01
051
Aug 2020
Michael Scheuerer, Matthew B. Switanek, Rochelle P. Worsnop et al.
Monthly Weather Review
NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)
Neural networks postprocess ECMWF reforecasts into probabilistic 7-day California precipitation outlooks out to week 4, beating a state-of-the-art method, though week 3-4 skill stays low.
Using Artificial Neural Networks for Generating Probabilistic Subseasonal Precipitation Forecasts over California
In one sentence. Neural networks postprocess ECMWF reforecasts into probabilistic 7-day California precipitation outlooks out to week 4, beating a state-of-the-art method, though week 3-4 skill stays low.
Labels
- Topic
- Post-processing & calibration, Sub-seasonal to seasonal
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels), CNN / U-Net
- Time scale
- 2 weeks–2 months
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1175/mwr-d-20-0096.1 OpenAlex:W3046652087
- Added
- 2026-10-22
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