Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 3
Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1615-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-1615-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 3
Model experiment description paper
 | 
19 Mar 2021
Model experiment description paper |  | 19 Mar 2021

Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates

Oliver Branch, Thomas Schwitalla, Marouane Temimi, Ricardo Fonseca, Narendra Nelli, Michael Weston, Josipa Milovac, and Volker Wulfmeyer

Data sets

Verification datasets for publication "Seasonal and diurnal performance of daily forecasts with WRF-NOAHMP over the United Arab Emirates" [Data set] Oliver Branch, Volker Wulfmeyer, Thomas Schwitalla, Marouane Temimi, Ricardo Fonseca, Narendra Nelli, and Josipa Milovac https://doi.org/10.5281/zenodo.3894544

MET tools statistics dataset used for publication "Seasonal and diurnal performance of daily forecasts with WRF-NOAHMP over the United Arab Emirates" [Data set] Oliver Branch, Volker Wulfmeyer, Thomas Schwitalla, Marouane Temimi, Ricardo Fonseca, Narendra Nelli, and Josipa Milovac https://doi.org/10.5281/zenodo.4004195

Model code and software

Scripts for publication "Seasonal and diurnal performance of daily forecasts with WRF-NOAHMP over the United Arab Emirates" Oliver Branch, Volker Wulfmeyer, Thomas Schwitalla, Marouane Temimi, Ricardo Fonseca, Narendra Nelli, and Josipa Milovac https://doi.org/10.5281/zenodo.3894491

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Short summary
Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates where extreme events like heat waves, flash floods, and dust storms are becoming more severe. This study employs a high-resolution simulation with the WRF-NOAHMP model, and the output is compared with seasonal observation data from 50 weather stations. This type of verification is vital to identify model deficiencies and improve forecasting systems for arid regions.
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