paper
2022
Post-processing & calibration
Applications & impacts Application study
CNN / U-NetClassical ML (trees, GP, linear, kernels)3–15 days Journal
2022-09-01
012
Sep 2022
Chen Zhang, Zachary Brodeur, Scott Steinschneider et al.
Water Resources Research
CNNs on GEFS precipitation fields for 1–14 day Sacramento precipitation occurrence; skill matches bias-corrected ensemble mean but cost-tunable thresholds help water management.
Leveraging Spatial Patterns in Precipitation Forecasts Using Deep Learning to Support Regional Water Management
In one sentence. CNNs on GEFS precipitation fields for 1–14 day Sacramento precipitation occurrence; skill matches bias-corrected ensemble mean but cost-tunable thresholds help water management.
Labels
- Topic
- Post-processing & calibration, Applications & impacts
- Type
- Application study
- Method
- CNN / U-Net, Classical ML (trees, GP, linear, kernels)
- Time scale
- 3–15 days
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1029/2021wr031910 OpenAlex:W4296558750
- Added
- 2026-10-22
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