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Statistical Forecasting of Tropical Rainfall Based on Spatio-Temporal Correlations and Equatorial Waves

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

Abstract:
Despite their high socio-economic importance, forecasts of tropical rainfall on a synoptic timescale are still poor. Due to the complex nature of convection, numerical weather prediction (NWP) models struggle to deliver reliable and accurate predictions of rainfall for the tropics. For example, in a previous study, we have shown that a simple probabilistic climatology based on past observations at a given location and a given day outperforms raw ensemble precipitation forecasts from several NWP centers over West Africa. Even after the application of state-of-the-art statistical post-processing, forecasts have at best moderate skill compared to climatology. Here, we propose a new statistical method for the prediction of tropical rainfall using spatio-temporal correlations of rainfall as well as the phasing and intensity of convectively coupled equatorial waves, which have been shown to govern predictability of tropical precipitation on the synoptic timescale.

The focus of this study is on predictions of the occurrence of precipitation and the probability of precipitation exceeding medium and high precipitation rates. The analyzed ... mehr


Zugehörige Institution(en) am KIT Fakultät für Physik (PHYSIK)
Institut für Meteorologie und Klimaforschung - Forschungsbereich Troposphäre (IMK-TRO)
Publikationstyp Poster
Jahr 2018
Sprache Englisch
Identifikator KITopen ID: 1000085046
HGF-Programm 12.01.02; LK 01
Erschienen in American Meteorological Society, 33rd Conference on Hurricanes and Tropical Meteorology, Ponte Vedra, FL, USA, 16 - 20 April 2018
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