泸州极端大风和大气污染物可预报性及相关性浅析

Predictability and Correlation Analysis of Extreme Strong Winds and Atmospheric Pollutants in Luzhou

利用2022年4月27—28日多源观测、污染物浓度及模式资料,分析了大风成因、中尺度对流系统特征和大气污染物浓度变化特征及IPM-EMNGS模式可预报性。结果表明,高低空低值系统相互配合、层结不稳定、较好的能量条件、浅薄的湿层厚度、较大的垂直风切变,有利于出现大风天气;各污染物浓度随天气有明显变化,晴热天气持续时各污染物浓度持续上升,而在大风过境后,PM_(10)、SO_(2)、NO_(2)、O_(3)浓度明显下降,降雨后PM_(2.5)和PM_(10)下降幅度明显,说明大部分污染物的稀释、扩散、清除与大风、降雨有明显相关,而PM_(2.5)和PM_(10)则对降雨更为敏感。且IPM-EMNGS模式对于大范围空气质量变化预报有指示意义,特别是AQI和O_(3)敏感性较好。

Based on the multi-source observation data,pollutant concentration data,and model data from April 27-28,2022,the causes of strong winds,characteristics of mesoscale convective systems,changes in atmospheric pollutant concentrations and the predictability of the IPM-EMNGS model were analyzed.The results show that the coordination of high-low altitude and low value systems,unstable stratification,good energy condition,shallow wet layer thickness,and large vertical wind shear are conducive to the occurrence of gale weather.The concentrations of various pollutants vary significantly with the weather.During the hot and sunny weather,the concentrations of various pollutants continue to rise.After strong winds pass,the concentrations of PM_(10),SO_(2),NO_(2),and O_(3) decrease significantly.After rainfall,the decrease of PM_(2.5) and PM_(10) is significant,indicating that the dilution,diffusion,and removal of most pollutants are significantly related to strong winds and rainfall,while PM_(2.5) and PM_(10) are more sensitive to rainfall.The IPM-EMNGS model has indicative significance for predicting large-scale air quality changes,especially with good sensitivity to AQI and O_(3).