paper
2022
Nowcasting
Local & station forecasting New model or method
Classical ML (trees, GP, linear, kernels)0–6 h Journal
2022-01-01
008
Jan 2022
Nita H. Shah, Bipasha Paul Shukla, Anupam Priamvada
Journal of Engineering Science and Technology Review
Random Forest and XGBoost ensembles trained on automatic weather station data predict 2-4 hour rainfall occurrence with about 80% accuracy.
Ensemble-based Model for Rainfall Nowcasting using Automatic Weather Station Data
In one sentence. Random Forest and XGBoost ensembles trained on automatic weather station data predict 2-4 hour rainfall occurrence with about 80% accuracy.
Labels
- Topic
- Nowcasting, Local & station forecasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 0–6 h
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.25103/jestr.154.16 OpenAlex:W4296504865
- Added
- 2026-10-22
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