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Application of probabilistic precipitation forecasts from a deterministic model towards increasing the lead-time of flash flood forecasts in South Africa


E Poolman
H Rautenbach
C Vogel

Abstract

Flash floods are some of the most devastating weather-related hazards in South Africa. The South African Flash Flood Guidance (SAFFG) system is a hydro-meteorological modelling system that provides forecasts for the next 1 to 6 h of potential flash floods in support of the flash flood warning system of the South African Weather Service (SAWS). The aim of this paper is to investigate the increase in the lead-time of flash flood warnings of the SAFFG using probabilistic precipitation forecasts generated by the deterministic Unified Model (UM) from the United Kingdom Met Office and run by the South African Weather Service (SAWS). As a first step, calculations of bias-corrected, basin-averaged rainfall from the UM model are provided. An ensemble set of 30 adjacent basins is then identified as ensemble members for each basin (the target basin), from which probabilistic rainfall information is calculated for the target basin covering the extended forecast period. By comparing this probabilistic rainfall forecast with the expected Flash Flood Guidance (FFG) of each basin, an outlook of potential flash flooding is provided. The procedure is applied to a real flash flood event and the ensemble-based rainfall forecasts are verified against rainfall estimated by the SAFFG system. The approach described here is shown to be able to deal with the uncertainties associated with UM rainfall forecasts, particularly regarding location and onset-time of convection. The flash flood outlook for the 18-h extended forecast period investigated was also able to capture the location of the flash flood event and showed its ability to provide additional lead-time for flash flood warnings to disaster managers.

Keywords: deterministic model ensembles, disasters, early warnings, flash floods, flash flood guidance, numerical weather prediction


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eISSN: 1816-7950
print ISSN: 0378-4738