Indian Institute of Tropical Meteorology (IITM), Ministry of Earth Sciences, Pune, India.
Meteorological Centre Ranchi, India Meteorological Department, Ministry of Earth Sciences, Ranchi, India.
Environ Monit Assess. 2023 Apr 13;195(5):560. doi: 10.1007/s10661-023-10987-3.
The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM by a chemical transport model.
化学输送模式的能力,以模拟准确的气象和化学过程,取决于物理参数化和气象输入数据的质量,如初始/边界条件。在这项研究中,天气研究和预测模型与化学(WRF-Chem)相结合,用于测试 PM 预测对行星边界层(PBL)参数化方案(YSU、MYJ、MYNN、ACM2 和 Boulac)和气象初始/边界条件(FNL、ERA-Interim、GDAS 和 NCMRWF)的敏感性,在冬季期间(2017 年 12 月至 2018 年 1 月)在印度-恒河平原(德里、旁遮普邦、哈里亚纳邦、北方邦和拉贾斯坦邦)。目的是选择用于模拟 PM 的模型配置,该模型显示出最低的误差,并与观测数据最好地吻合。使用来自 ERA 和 GDAS 数据集的初始/边界条件和本地 PBL 参数化(MYJ 和 MYNN)获得了最佳结果。还发现 PM 浓度对初始/边界条件变化的敏感性相对较低,但相反,对 PBL 方案变化的敏感性更强。此外,模拟 PM 对 PBL 方案选择的敏感性在一天中污染时间(傍晚至清晨)期间更强,而对气象输入数据的选择的敏感性在一天中更均匀和温和。这项工作表明了在未来空气质量模拟中,初始/边界条件数据集和 PBL 参数化方案选择方面的最佳模型设置。它还强调了选择 PBL 方案而不是气象数据集对化学输送模型模拟的 PM 的重要性。