paper
2025
Applications & impacts
Post-processing & calibration Application study
Classical ML (trees, GP, linear, kernels)Climate projections / centennialChina Meteorological Administration (CMA)Fudan University (FuXi)Nanjing University of Information Science & Technology (NUIST)Tsinghua University (NowcastNet) Journal
2025-12-01
043
Dec 2025
Haixing Gong, Kan Yi, Dinghua Yang et al.
气象学报：英文版
China Meteorological Administration (CMA), Fudan University (FuXi), Nanjing University of Information Science & Technology (NUIST), Tsinghua University (NowcastNet)
Machine learning corrects mesoscale model estimates to improve offshore wind resource assessment over the Yellow Sea. Abstract unavailable; assessment based on title.
Machine Learning Improves Mesoscale Offshore Wind Resource Assessment over the Yellow Sea
In one sentence. Machine learning corrects mesoscale model estimates to improve offshore wind resource assessment over the Yellow Sea. Abstract unavailable; assessment based on title.
Labels
- Topic
- Applications & impacts, Post-processing & calibration
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Climate projections / centennial
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1007/s13351-025-5051-z OpenAlex:W7124762048
- Added
- 2026-10-22
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