paper
2018
Nowcasting
Observations & remote sensing New model or method
Classical ML (trees, GP, linear, kernels)0–6 h Journal
2018-02-12
008
Feb 2018
Yan Ji
DEStech Transactions on Computer Science and Engineering
Neural networks trained on CINRAD radar reflectivity and gauges nowcast Wuhan rain intensity, reaching over 50% accuracy at 36-minute lead for 5 dBZ.
Short-term Precipitation Prediction Based on a Neural Network Method from Radar Observations
In one sentence. Neural networks trained on CINRAD radar reflectivity and gauges nowcast Wuhan rain intensity, reaching over 50% accuracy at 36-minute lead for 5 dBZ.
Labels
- Topic
- Nowcasting, Observations & remote sensing
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 0–6 h
- Domain
- Local / station
- Data
- Radar, Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.12783/dtcse/aiie2017/18223 OpenAlex:W2791404987
- Added
- 2026-10-22
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