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Statistical ensemble postprocessing for precipitation forecasting during the West African Monsoon

Vogel, Peter; Gneiting, Tilmann; Knippertz, Peter ORCID iD icon; Fink, Andreas H.; Schlüter, Andreas


Precipitation forecasts for one up to several days are of high socioeconomic importance for agriculturally dominated societies in West Africa. In this contribution, we evaluate the performance of operational European Centre for Medium-Range Weather Forecasts (ECWMF) raw ensemble and statistically postprocessed against climatological precipitation forecasts for accumulation periods of 1 to 5 days for the monsoon periods (May to mid-October) from 2007 to 2014. We use Bayesian Model Averaging (BMA) and Ensemble Model Output Statistics (EMOS) as state-of-the-art postprocessing methods and verify against station and gridded Tropical Rainfall Measuring Mission (TRMM) observations. Based on a subset of past forecast-observation-pairs, statistical postprocessing corrects ensemble forecasts for biases and dispersion errors. For the midlatitudes, statistical postprocessing has demonstrated its added value for a wide range of meteorological quantities and this contribution is the first to apply it to precipitation forecasts over West Africa, where the high degree of convective organization at the mesoscale makes precipitation forecasts particularly challenging. ... mehr

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Institut für Stochastik (STOCH)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Vortrag
Publikationsjahr 2017
Sprache Englisch
Identifikator KITopen-ID: 1000077204
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Veranstaltung European Geosciences Union General Assembly 2017, Vienna, Austria, 23rd - 28th April 2017
Bemerkung zur Veröffentlichung Geophysical Research Abstracts, 19(2017) EGU2017-14208
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