paper
2019
Extremes & hazards
Post-processing & calibration New model or method
Other6 h–3 daysNSF NCAR / UCAR Journal
2019-06-05
051
Jun 2019
Kirkwood A. Cloud, Brian J. Reich, Christopher M. Rozoff et al.
Weather and Forecasting
NSF NCAR / UCAR
Feed-forward network on HWRF output beats operational intensity guidance at 24–57 h in cross-validation and quadruples rapid-intensification hits.
A Feed Forward Neural Network Based on Model Output Statistics for Short-Term Hurricane Intensity Prediction
In one sentence. Feed-forward network on HWRF output beats operational intensity guidance at 24–57 h in cross-validation and quadruples rapid-intensification hits.
Labels
- Topic
- Extremes & hazards, Post-processing & calibration
- Type
- New model or method
- Method
- Other
- Time scale
- 6 h–3 days
- Domain
- Global
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Pre-operational / experimental
- Identifiers
- DOI:10.1175/waf-d-18-0173.1 OpenAlex:W2948119210
- Added
- 2026-10-22
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