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Discussion papers | Copyright
https://doi.org/10.5194/nhess-2018-226
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 11 Sep 2018

Research article | 11 Sep 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Analysis of an Extreme Weather Event in a Hyper Arid Region Using WRF-Hydro Coupling, Station, and Satellite data

Youssef Wehbe1,2, Marouane Temimi1, Michael Weston1, Naira Chaouch1, Oliver Branch3, Thomas Schwitalla3, Volker Wulfmeyer3, and Abdulla Al Mandous2 Youssef Wehbe et al.
  • 1Department of Civil Infrastructure and Environmental Engineering, Masdar Institute, Khalifa University of Science and Technology, Masdar City, P.O. Box 54224 Abu Dhabi, United Arab Emirates
  • 2Department of Research, Development and Training, National Center of Meteorology (NCM), P.O. Box 4815, Abu Dhabi, United Arab Emirates
  • 3Institute of Physics and Meteorology, University of Hohenheim, Garbenstraße 30, D-70599 Stuttgart, Germany

Abstract. This study investigates an extreme weather event that impacted the United Arab Emirates (UAE) in March 2016 using the Weather Research and Forecasting (WRF) model version 3.7.1 coupled with its hydrological modeling extension package (Hydro). Six-hourly forecasted forcing records at 0.5o spatial resolution, obtained from the NCEP Global Forecast System (GFS), are used to drive the three nested downscaling domains of both standalone WRF and coupled WRF/WRF-Hydro configurations for the recent flood-triggering storm. Ground and satellite observations over the UAE are employed to validate the model results. Precipitation, soil moisture, and cloud fraction retrievals from GPM (30-minute, 0.1o product), AMSR2 (daily, 0.1o product), and MODIS (daily, 5km product), respectively, are used to assess the model output. The Pearson correlation coefficient (PCC), relative bias (rBIAS) and root-mean-square error (RMSE) are used as performance measures. Results show reductions of 24% and 13% in RMSE and rBIAS measures, respectively, in precipitation forecasts from the coupled WRF/WRF-Hydro model configuration, when compared to standalone WRF. The coupled system also shows improvements in global radiation forecasts, with reductions of 45% and 12% for RMSE and rBIAS, respectively. Moreover, WRF-Hydro was able to simulate the spatial distribution of soil moisture reasonably well across the study domain when compared to AMSR2 satellite soil moisture estimates, despite a noticeable dry/wet bias in areas where soil moisture is high/low. The demonstrated improvement, at the local scale, implies that WRF-Hydro coupling may enhance hydrologic forecasts and flash flood guidance systems in the region.

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Short summary
This article is expected to be of great interest to the broad geoscience community. The work builds on current regional climate modelling, numerical weather prediction, and hydrological modelling applications in the Arabian Peninsula – a hyper-arid environment with a vulnerable infrastructure to frequent extreme weather and flood events.
This article is expected to be of great interest to the broad geoscience community. The work...
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