paper
2020
Post-processing & calibration
New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2020-12-30
008
Dec 2020
(주)에코브레인 신사업개발팀, Chul-Min Ko, Yeong Yun Jeong et al.
Journal of Climate Research
XGBoost with probability matching post-processes LENS and Dong-Nae forecasts, improving Korean heavy-rainfall QPF skill over 14 events.
A Study on Hydrological Rainfall Adjustment using Machine Learning and Probability Matching Method during Heavy Rainfall Season
In one sentence. XGBoost with probability matching post-processes LENS and Dong-Nae forecasts, improving Korean heavy-rainfall QPF skill over 14 events.
Labels
- Topic
- Post-processing & calibration
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...), Radar, Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.14383/cri.2020.15.4.257 OpenAlex:W3134409327
- Added
- 2026-10-22
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