652 Evaluation of the Performance of the WRF Model over the United Arab Emirates

Tuesday, 14 January 2020
Hall B (Boston Convention and Exhibition Center)
Ricardo Morais Fonseca, Khalifa Univ. of Science and Technology, Abu Dhabi, United Arab Emirates; and M. Temimi, M. Weston, N. R. Nelli, M. S. Thota, and V. Valappil

Handout (2.3 MB)

The Weather Research and Forecasting (WRF) model version 3.7.1 is run over the United Arab Emirates (UAE), a hyper-arid country located in the Middle East, with the default and an improved representation of the soil texture and land-use data. The model is set up in a two nest configuration, with a 12 km grid comprising the entire Arabian Gulf and surrounding regions, and a 4 km grid that includes the whole of the UAE. The WRF simulations are initialized every day at 06UTC and run for 72h, with the first 6h discarded as model spin-up.

When evaluated against in-situ weather station data at 35 sites over the country, the model's air temperature predictions are found to be more skillful when a more realistic representation of the surface properties is considered. This is the case both in the inland desert, and in coastal cities like Dubai. However, the impact on other near-surface fields such as the water vapour mixing ratio, relative humidity, and horizontal wind speed, is rather small. With both configurations, a comparison of the model forecasts with eddy-covariance measurements from a field campaign at Al Ain, revealed a tendency to underestimate the net short-wave radiation flux at the surface, which can be explained by an over-prediction of the observed albedo. The WRF forecasts are also assessed against twice-daily radiosonde profiles at Abu Dhabi's International Airport, and microwave radiometer temperature profiles at Masdar Institute in Abu Dhabi. The analysis conducted here highlights the importance of properly representing the surface properties in numerical simulations in particular in hyper-arid regions such as the UAE.

Supplementary URL: https://earth.masdar.ac.ae/

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