paper
2021
Downscaling & super-resolution
Extremes & hazards New model or method
Classical ML (trees, GP, linear, kernels)Climate projections / centennial Other
2021-10-29
008
Oct 2021
Wenpeng Zhao, Tsuyoshi Kinouchi
preprint
An artificial neural network disaggregates 3-hourly rainfall to hourly extreme rainfall for Cambodia using ERA5 covariates, reaching R2 of 0.93.
Downscaling & super-resolution
A Rainfall Disaggregation Scheme for Generating Fine Time-scale Extreme Rainfall under Climate Change
In one sentence. An artificial neural network disaggregates 3-hourly rainfall to hourly extreme rainfall for Cambodia using ERA5 covariates, reaching R2 of 0.93.
Labels
- Topic
- Downscaling & super-resolution, Extremes & hazards
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Climate projections / centennial
- Domain
- Regional
- Data
- ERA5 / reanalysis, Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1002/essoar.10508538.1 OpenAlex:W3208997047
- Added
- 2026-10-22
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