Sensitivity study of WRF simulations over tanzania for extreme events during wet and dry seasons

Abubakar Lungo, Sangil Kim, Meiyan Jiang, Giphil Cho, Yongkuk Kim

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Precipitation prediction is important to help mitigate the effects of drought and floods on various social and economic activities. This research is to improve the forecasting skill over Tanzania by providing suitable combinations of physical parameterization schemes and horizontal grid spacing of the Weather Research Forecasting (WRF) model for daily forecasting over Tanzania. The performance of different schemes on the precipitation systems during the wet and dry seasons over Tanzania is evaluated such that the sensitivity tests was performed for the WRF model at different horizontal resolutions, and for different physical parameterization schemes (convective and cloud microphysics). The results showed that the improved grid spacing was better at completing forecasts during the wet season, but had little significant impacts during the dry season. Model simulations with combinations of Lin et al. microphysics and the multiscale Kain-Fritsch scheme showed greater success during the both seasons; therefore, these combinations were recommended for Tanzania to resolve weather systems during the wet and dry season simulations, respectively.

Original languageEnglish
Article number459
JournalAtmosphere
Volume11
Issue number5
DOIs
StatePublished - 1 May 2020

Keywords

  • Dry season
  • Heavy rainfall
  • Precipitation forecasting
  • Precipitation forecasting
  • Tanzania
  • Wet season
  • WRF model

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