paper
2023
Extremes & hazards
Climate analysis & attribution New model or method
Classical ML (trees, GP, linear, kernels)Seasonal to annual Journal
2023-01-13
012
Jan 2023
Chandrani Chatterjee, Joyjit Mandal, Saurabh Das
International Journal of Climatology
Random forest regionalizes India into seven lightning climatologies and predicts seasonal lightning density from CAPE and humidity, with R² of 0.81 in monsoon.
A machine learning approach for prediction of seasonal lightning density in different lightning regions of India
In one sentence. Random forest regionalizes India into seven lightning climatologies and predicts seasonal lightning density from CAPE and humidity, with R² of 0.81 in monsoon.
Labels
- Topic
- Extremes & hazards, Climate analysis & attribution
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Seasonal to annual
- Domain
- Regional
- Data
- ERA5 / reanalysis, Other
- Status
- Research
- Identifiers
- DOI:10.1002/joc.8005 OpenAlex:W4316041049
- Added
- 2026-10-22
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