Abstract
Abstract. Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates (UAE) where extreme events like heat waves, flash floods, and dust storms are severe. Hence, accurate forecasting of quantities like surface temperatures and humidity is very important. To date, there have been few seasonal-to-annual scale verification studies with WRF at high spatial and temporal resolution. This study employs a convection-permitting scale (2.7 km grid scale) simulation with WRF with Noah-MP, in daily forecast mode, from 1 January to 30 November 2015. WRF was verified using measurements of 2 m air temperature (T2 m), 2 m dew point (TD2 m), and 10 m wind speed (UV10 m) from 48 UAE WMO-compliant surface weather stations. Analysis was made of seasonal and diurnal performance within the desert, marine, and mountain regions of the UAE. Results show that WRF represents temperature (T2 m) quite adequately during the daytime with biases ≤+1 ∘C. There is, however, a nocturnal cold bias (−1 to −4 ∘C), which increases during hotter months in the desert and mountain regions. The marine region has the smallest T2 m biases (≤-0.75 ∘C). WRF performs well regarding TD2 m, with mean biases mostly ≤ 1 ∘C. TD2 m over the marine region is overestimated, though (0.75–1 ∘C), and nocturnal mountain TD2 m is underestimated (∼-2 ∘C). UV10 m performance on land still needs improvement, and biases can occasionally be large (1–2 m s−1). This performance tends to worsen during the hot months, particularly inland with peak biases reaching ∼ 3 m s−1. UV10 m is better simulated in the marine region (bias ≤ 1 m s−1). There is an apparent relationship between T2 m bias and UV10 m bias, which may indicate issues in simulation of the daytime sea breeze. TD2 m biases tend to be more independent. Studies such as these are vital for accurate assessment of WRF nowcasting performance and to identify model deficiencies. By combining sensitivity tests, process, and observational studies with seasonal verification, we can further improve forecasting systems for the UAE.
Highlights
Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates (UAE), to predict low-visibility events like fog and dust (e.g., Aldababseh and Temimi, 2017; Chaouch et al, 2017; Karagulian et al, 2019), and extreme events relating to storms and flash floods (Chowdhury et al, 2016; Wehbe et al, 2019), high temperatures, and droughts
Weather in the wider region is generally controlled by four predominant patterns, including troughs originating from the Atlantic and Mediterranean Sea in winter, locally forced convective storms over the UAE and Oman Al Hajar Mountains in summer, and the southerly summer monsoon and cyclones from the Arabian Sea during June and October (Bruintjes and Yates, 2003; Steinhoff et al, 2018)
The objective of this study was to run a series of daily forecasts with Weather Research and Forecasting (WRF) for the period 1 January to 30 November 2015, with a discarded 1-month spin-up run from 1 December 2014
Summary
Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates (UAE), to predict low-visibility events like fog and dust (e.g., Aldababseh and Temimi, 2017; Chaouch et al, 2017; Karagulian et al, 2019), and extreme events relating to storms and flash floods (Chowdhury et al, 2016; Wehbe et al, 2019), high temperatures, and droughts. These extreme events are expected to become more prevalent under a changing climate (Feng et al, 2014; Zhao et al, 2020). Branch et al.: A comparison of the WRF model with 48 surface weather stations
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