TY - JOUR
T1 - Evaluation of the Performance of the WRF Model in a Hyper-Arid Environment
T2 - A Sensitivity Study
AU - Abida, Rachid
AU - Addad, Yacine
AU - Francis, Diana
AU - Temimi, Marouane
AU - Nelli, Narendra
AU - Fonseca, Ricardo
AU - Nesterov, Oleksandr
AU - Bosc, Emmanuel
N1 - Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/6
Y1 - 2022/6
N2 - Accurate simulation of boundary layer surface meteorological parameters is essential to achieve good forecasting of weather and atmospheric dispersion. This paper is devoted to a model sensitivity study over a coastal hyper-arid region in the western desert of the United Arab Emirates. This region hosts the Barakah Nuclear Power Plant (BNPP), making it vital to correctly simulate local weather conditions for emergency response in case of an accidental release. We conducted a series of high-resolution WRF model simulations using different combinations of physical schemes for the months January 2019 and June 2019. The simulated results were verified against in-situ meteorological surface measurements available offshore, nearshore, and inland at 12 stations. Several statistical metrics were calculated to rank the performance of the different simulations and a near-to-optimal set of physics options that enhance the performance of a WRF model over different locations in this region has been selected. Additionally, we found that the WRF model performed better in inland locations compared to offshore or nearshore locations, suggesting the important role of dynamical SSTs in mesoscale models. Moreover, morning periods were better simulated than evening ones. The impact of nudging towards station observations resulted in an overall reduction in model errors by 5–15%, which was more marked at offshore and nearshore locations. The sensitivity to grid cell resolution indicated that a spatial resolution of 1 km led to better performance compared to coarser spatial resolutions, highlighting the advantage of high-resolution simulations in which the mesoscale coastal circulation is better resolved.
AB - Accurate simulation of boundary layer surface meteorological parameters is essential to achieve good forecasting of weather and atmospheric dispersion. This paper is devoted to a model sensitivity study over a coastal hyper-arid region in the western desert of the United Arab Emirates. This region hosts the Barakah Nuclear Power Plant (BNPP), making it vital to correctly simulate local weather conditions for emergency response in case of an accidental release. We conducted a series of high-resolution WRF model simulations using different combinations of physical schemes for the months January 2019 and June 2019. The simulated results were verified against in-situ meteorological surface measurements available offshore, nearshore, and inland at 12 stations. Several statistical metrics were calculated to rank the performance of the different simulations and a near-to-optimal set of physics options that enhance the performance of a WRF model over different locations in this region has been selected. Additionally, we found that the WRF model performed better in inland locations compared to offshore or nearshore locations, suggesting the important role of dynamical SSTs in mesoscale models. Moreover, morning periods were better simulated than evening ones. The impact of nudging towards station observations resulted in an overall reduction in model errors by 5–15%, which was more marked at offshore and nearshore locations. The sensitivity to grid cell resolution indicated that a spatial resolution of 1 km led to better performance compared to coarser spatial resolutions, highlighting the advantage of high-resolution simulations in which the mesoscale coastal circulation is better resolved.
KW - Barakah nuclear power plant
KW - WRF model
KW - hyper-arid region
KW - physical parametrizations
KW - station nudging
KW - statistical evaluation
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U2 - 10.3390/atmos13060985
DO - 10.3390/atmos13060985
M3 - Article
AN - SCOPUS:85132821033
VL - 13
JO - Atmosphere
JF - Atmosphere
IS - 6
M1 - 985
ER -