| Autor: |
Hector Chikoore, Mary-Jane M. Bopape, Thando Ndarana, Tshimbiluni P. Muofhe, Morne Gijben, Rendani B. Munyai, Tshilidzi C. Manyanya, Robert Maisha |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Weather and Climate Extremes, Vol 33, Iss , Pp 100327- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2212-0947 |
| DOI: |
10.1016/j.wace.2021.100327 |
| Popis: |
An extreme sub-daily precipitation event produced about 300 mm of rainfall in less than 4 h overnight from 13–14 February 2019 resulting in high floods in Thohoyandou, a small town northeast of South Africa. We employed station, radar, satellite and reanalysis datasets to investigate the rainfall, circulation and thermodynamic fields and understand the meteorological structure of the extreme event via a multiscale analysis. The large-scale synoptic environment was characterized by a mid-tropospheric tropical-temperate trough and attendant cloud band coupled to a surface high ridging over the southeast coast of the country. We found that whilst heavy rainfall (>50 mm/24 h) was widespread ahead of the upper trough, extreme amounts (∼100 mm/h) were localized due to a cloudburst. A small perturbation to the favorable large scale mid-tropospheric environment also contributed to localized heavy rainfall. The south-north pressure gradient was steepened by a surface low over southern Mozambique resulting in enhanced moisture fluxes deriving from the southwest Indian Ocean. The interaction of prevailing surface winds and a low-level jet with the steep topography of the adjacent Soutpansberg Mountain Range enhanced low-level convergence and lifting in the area. We also show that the highest rainfalls were uphill of the location of flooding which was contained in a poorly drained valley. Whereas the Unified Model forecasts appeared accurate for the large-scale pattern of heavy rainfall in the area, the rainfall peak was generally underestimated, whilst the timing of extreme rainfall was delayed in the 18Z simulation, which is used by forecasters operationally. Our findings contribute to understanding the occurrence of extreme weather events over northeastern South Africa and also how models treat them, towards natural disaster risk reduction. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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