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. This study investigates an extreme weather event that impacted theUnited Arab Emirates (UAE) in March 2016, using the Weather Research andForecasting (WRF) model version 3.7.1 coupled with its hydrological modelingextension package (WRF-Hydro). Six-hourly forecasted forcing records at0.5∘ spatial resolution, obtained from the National Center for Environmental Prediction (NCEP) Global ForecastSystem (GFS), are used to drive the three nested downscaling domains of bothstandalone WRF and coupled WRF–WRF-Hydro configurations for the recentflood-triggering storm. Ground and satellite observations over the UAE areemployed to validate the model results. The model performance was assessedusing precipitation from the Global Precipitation Measurement (GPM) mission (30 min, 0.1∘ product), soil moisturefrom the Advanced Microwave Scanning Radiometer 2 (AMSR2; daily, 0.1∘ product) and the NOAA Soil Moisture Operational Products System (SMOPS; 6-hourly, 0.25∘ product), and cloud fraction retrievals from the Moderate Resolution Imaging Spectroradiometer Atmosphere product (MODATM; daily, 5 km product). The Pearson correlation coefficient (PCC), relativebias (rBIAS), and root-mean-square error (RMSE) are used as performancemeasures. Results show reductions of 24 % and 13 % in RMSE and rBIASmeasures, respectively, in precipitation forecasts from the coupledWRF–WRF-Hydro model configuration, when compared to standalone WRF. Thecoupled system also shows improvements in global radiation forecasts, withreductions of 45 % and 12 % for RMSE and rBIAS, respectively.Moreover, WRF-Hydro was able to simulate the spatial distribution of soilmoisture reasonably well across the study domain when compared to AMSR2-derived soilmoisture estimates, despite a noticeable dry and wet bias in areas where soilmoisture is high and low. Temporal and spatial variabilities of simulated soil moisture compare well to estimates from the NOAA SMOPS product, whichindicates the model's capability to simulate surface drainage. Finally, thecoupled model showed a shallower planetary boundary layer (PBL) compared to the standalone WRFsimulation, which is attributed to the effect of soil moisture feedback. Thedemonstrated improvement, at the local scale, implies that WRF-Hydro couplingmay enhance hydrological and meteorological forecasts in hyper-aridenvironments.

Analysis of an extreme weather event in a hyper-arid region using WRF-Hydro coupling, station, and satellite data