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Study Analyzes Seasonal and Diurnal Performance of Daily Forecasts with WRF

In arid regions like the United Arab Emirates (UAE), effective numerical weather forecasting is of great importance to ensure accurate prediction of low-visibility events like fog and dust and extreme weather events like heat waves, dust storms, droughts, flash floods, among others.

As these extreme events are expected to become more prevalent under a changing climate, it is vital to use regional weather forecasting and climate simulations with regional climate models (RCMs) to correctly forecast important quantities which characterize extreme events, especially surface temperatures, humidity, winds, and precipitation.

As a key step towards improving the forecasting systems for the UAE and other arid regions, Prof. Volker Wulfmeyer, a First Cycle Awardee of UAE Research Program for Rain Enhancement Science (UAEREP) and Managing Director and Chair of Physics and Meteorology at the Institute of Physics and Meteorology of the University of Hohenheim in Stuttgart, worked on a study to analyze the seasonal and diurnal performance of WRF within the desert, marine, and mountain regions of the UAE by employing a convection-permitting scale (2.7 km grid scale) simulation with the Weather Research and Forecasting (WRF) model in daily forecast mode.

Running from 1 January to 30 November 2015, the study aimed to assess the seasonal and diurnal performance of WRF both qualitatively and quantitatively in reproducing surface air temperature, dew point, and wind data from 48 WMO-compliant surface weather stations distributed across the UAE. It assessed the model performance in different areas of the country in three environments including the northern coastline and islands, inland lowland desert areas, and the Al Hajar Mountains in the east to investigate differences in performance due to expected differences in climate regimes.

Through ambitious simulations and robust verification, the study helped gain valuable insights into the regional climate and model performance, marking an important step towards more skillful weather forecasting with WRF with Noah-MP in the UAE.

It found that that WRF represents 2-meter surface temperature quite adequately during the daytime with biases less than +1 °C. The results also showed that the marine region has the smallest temperature biases (less than −0.75 °C), and wind speed is better simulated in the marine region (less than 1 m/s bias). It also revealed that the performance tends to worsen during the hot months, particularly inland with peak biases reaching ∼ 3 m/s.

Studies such as these are vital for accurate assessment of WRF nowcasting performance and to identify model deficiencies, particularly in under-studied arid environments such as the UAE.  

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