paper
2023
Applications & impacts
Local & station forecasting Application study
Classical ML (trees, GP, linear, kernels)3–15 days Journal
2023-01-01
008
Jan 2023
Alessandro Brunovich Cavalli, Alexander Ivanovich Belolyubtsev, Anna Vladislavovna Belkova et al.
SCIENTIFIC LIFE
A neural ML method predicts pentad water-surface evaporation for rice fields from forecast temperature, wind and precipitation, aimed at medium-term agricultural planning.
PREDICTION OF EVAPORATION FROM THE WATER SURFACE USING MACHINE LEARNING
In one sentence. A neural ML method predicts pentad water-surface evaporation for rice fields from forecast temperature, wind and precipitation, aimed at medium-term agricultural planning.
Labels
- Topic
- Applications & impacts, Local & station forecasting
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 3–15 days
- Domain
- Local / station
- Data
- NWP analysis or forecasts (IFS, GFS, ...), Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.35679/1991-9476-2023-18-5-686-695 OpenAlex:W4403184327
- Added
- 2026-10-22
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