Abstract. This study presents a comprehensive evaluation of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in simulating meteorological parameters and concentrations of gaseous pollutants across the United Arab Emirates (UAE) for the months of June and December 2018, representing the contrasting climatic conditions of summer and winter. The assessment of WRF-Chem performance involved comparisons with ground-based observations for meteorological parameters and satellite retrievals from the TROPOspheric Monitoring Instrument (TROPOMI) for gaseous pollutants. The assessment of gaseous pollutants using the WRF-Chem model revealed distinct patterns in the estimation of pollutant levels across different areas and seasons. The comparison with TROPOMI column concentration revealed the model's strengths in simulating tropospheric NO₂ and total O₃ spatio-temporal patterns, although it had deficiencies in modelling the total CO column concentrations. The model exhibited a strong correlation with TROPOMI retrievals, with correlation coefficients ranging between 0.71 and 0.95 for summer and 0.86 to 0.94 for winter among these gaseous pollutants. It tended to slightly overestimate NO₂ levels, with a higher discrepancy observed in summer (0.24 x 10¹⁵ molecules/cm²) compared to winter (0.19 x 10¹⁵ molecules/cm²). When comparing WRF-Chem to TROPOMI-CO data, the discrepancies were more pronounced, showing an overestimation of 0.48 x 10¹⁸ molecules/cm² in summer and a significant underestimation of 1.13 x 10¹⁸ molecules/cm² in winter. The model consistently underestimated ozone levels in both seasons, by 0.15 x 10¹⁸ and 0.20 x 10¹⁸ molecules/cm², respectively. Meteorological evaluations revealed the model's tendency to underestimate the 2-m temperature in summer and overestimate it in winter, with mean biases ranging from -2.17 to +1.19 °C and a Root Mean Square Error in the range of 0.8 to 5.9 °C among the stations. The model showed enhanced performance for the 10-m wind speed and downward shortwave radiation flux, reflecting advancements over previous studies. Therefore, the WRF-Chem model effectively simulates key meteorological parameters and pollutants over the UAE, demonstrating significant regional-scale prediction skills. Areas for further model refinement are also identified and discussed. Integrating model predictions with satellite and ground-based data is emphasized for advancing air quality monitoring and enhancing predictive accuracy of atmospheric pollutants in this region.

中文翻译：

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阿拉伯联合酋长国气态污染物 WRF-Chem 性能评估

摘要。本研究对天气研究和预报模型与化学 (WRF-Chem) 相结合进行了综合评估，模拟了 2018 年 6 月和 12 月阿拉伯联合酋长国 (UAE) 的气象参数和气态污染物浓度，代表了对比夏季和冬季的气候条件。 WRF-Chem 性能的评估包括与地面气象参数观测结果的比较以及 TROPOspheric 监测仪器 (TROPOMI) 气态污染物卫星反演结果的比较。使用 WRF-Chem 模型对气态污染物的评估揭示了不同地区和季节污染物水平估算的不同模式。与TROPOMI柱浓度的比较揭示了该模型在模拟对流层NO ₂和总O ₃时空格局方面的优势，尽管它在模拟总CO柱浓度方面存在缺陷。该模型与 TROPOMI 反演表现出很强的相关性，这些气态污染物夏季相关系数在 0.71 至 0.95 之间，冬季在 0.86 至 0.94 之间。它倾向于稍微高估 NO _{2水平，与冬季（0.19 x 10} ¹⁵分子/cm ²）相比，夏季（0.24 x 10 ¹⁵分子/cm ² ）观察到的差异更大。将 WRF-Chem 与 TROPOMI-CO 数据进行比较时，差异更加明显，夏季高估了 0.48 x 10 ¹⁸分子/cm ² ，冬季显着低估了 1.13 x 10 ¹⁸分子/cm ² 。该模型始终低估了两个季节的臭氧水平，分别低估了 0.15 x 10 ¹⁸和 0.20 x 10 ¹⁸分子/cm ²。气象评估显示，该模型在夏季低估 2 米温度，在冬季高估 2 米温度，平均偏差范围为 -2.17 至 +1.19 °C，均方根误差范围为 0.8 至 5.9 °C。站。该模型显示出 10 米风速和向下短波辐射通量的增强性能，反映了较之前研究的进步。因此，WRF-Chem 模型有效地模拟了阿联酋的关键气象参数和污染物，展示了重要的区域尺度预测能力。还确定并讨论了进一步完善模型的领域。强调将模型预测与卫星和地面数据相结合，以推进该地区的空气质量监测并提高大气污染物的预测准确性。