Evaluation of WRF Cumulus Parameterization Schemes for the Hot Climate of Sudan Emphasizing Crop Growing Seasons

Abstract

High spatiotemporal resolution climate data are essential for climate-related impact studies. The Weather Research and Forecasting (WRF) model is widely used to downscale climate data for different regions with regional-specific physics configurations. This study aimed to identify robust configurations of the WRF model, especially cumulus parameterization schemes, for different climatic zones of Sudan. We focused on wet season (June–September) rainfall and dry season (November–February) temperature, which are determinants of summer crop and irrigated wheat yields, respectively. Downscaling experiments were carried out to compare the following schemes: Betts–Miller–Janjic (BMJ), improved Kain–Fritch (KFT), modified Tiedtke (TDK), and Grell–Freitas (GF). Results revealed that the BMJ performed better for wet season rainfall in the hyper-arid and arid zones; KFT performed better for rainfall in July and August in the semi-arid zone where most summer crops are cultivated. For dry season temperature, the BMJ and TDK outperformed the other schemes in all three zones, except that the GF performed best for the minimum temperature in December and January in the arid zone, where irrigated wheat is produced, and in the semi-arid zone. Specific parameterization schemes therefore need to be selected for specific seasons and climatic zones of Sudan.