paper
2021
Post-processing & calibration
Sub-seasonal to seasonal New model or method
Classical ML (trees, GP, linear, kernels)2 weeks–2 monthsNOAA (incl. GFDL, PSL, GSL, NCEP/EMC) Journal
2021-01-20
047
Jan 2021
Yun Long Fan, Vladimir M. Krasnopolsky, Huug van den Dool et al.
Weather and Forecasting
NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)
Neural networks post-process NCEP CFS week-3–4 precipitation and 2-m temperature forecasts, improving skill over multiple linear regression correction.
Using Artificial Neural Networks to Improve CFS Week-3–4 Precipitation and 2-m Air Temperature Forecasts
In one sentence. Neural networks post-process NCEP CFS week-3–4 precipitation and 2-m temperature forecasts, improving skill over multiple linear regression correction.
Labels
- Topic
- Post-processing & calibration, Sub-seasonal to seasonal
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 2 weeks–2 months
- Domain
- Global
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1175/waf-d-20-0014.1 OpenAlex:W3122954327
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.