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Skill of Global Raw and Postprocessed Ensemble Predictions of Rainfall over Northern Tropical Africa

Vogel, Peter; Knippertz, Peter; Gneiting, Tilmann; Fink, Andreas H.; Schlueter, Andreas

Accumulated precipitation forecasts are of high socioeconomic importance for agriculturally dominated societies in northern tropical Africa. In this study, we analyze the performance of nine operational global ensemble predic- tion systems (EPSs), which are part of the TIGGE dataset, for three regions in northern tropical Africa. Model predictions are assessed relative to climatology-based forecasts for 1 to 5-day accumulated precipitation during the monsoon seasons 2007–2014. To assess the full potential of raw ensemble forecasts across spatial scales, we apply state-of-the-art statistical postprocessing methods in form of Bayesian Model Averaging (BMA) and Ensem- ble Model Output Statistics (EMOS), and verify against station and spatially aggregated, satellite-based gridded observations. Raw ensemble forecasts are uncalibrated, unreliable and underperform relative to climatology, inde- pendently of region, accumulation time, monsoon season and ensemble. Differences between raw ensemble and climatological forecasts are large, and partly stem from poor prediction for low precipitation amounts. BMA and EMOS postprocessed forecasts ar ... mehr

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Forschungsbereich Troposphäre (IMK-TRO)
Publikationstyp Poster
Jahr 2018
Sprache Englisch
Identifikator KITopen-ID: 1000085043
HGF-Programm 12.01.02 (POF III, LK 01)
Veranstaltung European Geosciences Union General Assembly (2018), Wien, Österreich, 08.04.2018 – 13.04.2018
Bemerkung zur Veröffentlichung Geophysical Research Abstracts, 20 (2018) EGU2018-6773
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