Improving global rainfall forecasting with a weather type approach in Japan
| Autor: | Jean-Francois Vuillaume, Srikantha Herath |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
010504 meteorology & atmospheric sciences
Meteorology Mean squared error 0208 environmental biotechnology 02 engineering and technology Wind direction Numerical weather prediction 01 natural sciences 020801 environmental engineering Root mean square Prognostic chart Anticyclone Climatology Cyclone Environmental science Tropical cyclone forecast model 0105 earth and related environmental sciences Water Science and Technology |
| Zdroj: | Hydrological Sciences Journal. 62:167-181 |
| ISSN: | 2150-3435 0262-6667 |
| Popis: | An automated version of the weather type classification scheme was performed over Japan to characterize daily circulation conditions. A daily gridded field of mean sea-level pressure (MSLP) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis dataset (ERA-interim) and the THORPEX Interactive Grand Global Ensemble (TIGGE) daily forecast dataset were used. The weather type is advantageous as it provides an opportunity to improve global rainfall prediction by refining statistical bias correction. We distinguished 11 weather types: anticyclone, cyclone, hybrid and eight purely wind directions. The results indicate that the main weather types contributing to the total volume of rainfall are cyclone, hybrid, purely westerly and northwest winds. A gamma-based bias correction decreases the global rainfall forecast root mean square by 10%, while specific weather type gamma bias correction accounts for 5–10% root mean square error reduction, with a total decrease of errors up to a... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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