paper
2020
Post-processing & calibration
Extremes & hazards New model or method
Classical ML (trees, GP, linear, kernels)Climate projections / centennialColumbia University (LEAP, Lamont-Doherty) Journal
2020-12-28
026
Dec 2020
Jinkai Tan, Sheng Chen, Chia‐Ying Lee et al.
International Journal of Climatology
Columbia University (LEAP, Lamont-Doherty)
A machine-learning bias correction for a 25-km regional climate model raises simulated violent typhoon frequency from zero to match observations and projects increases under warming.
Projected changes of typhoon intensity in a regional climate model: Development of a machine learning bias correction scheme
In one sentence. A machine-learning bias correction for a 25-km regional climate model raises simulated violent typhoon frequency from zero to match observations and projects increases under warming.
Labels
- Topic
- Post-processing & calibration, Extremes & hazards
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Climate projections / centennial
- Domain
- Regional
- Data
- ERA5 / reanalysis, CMIP / climate model output
- Status
- Research
- Identifiers
- DOI:10.1002/joc.6987 OpenAlex:W3117541273
- Added
- 2026-10-22
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