准确确定臭氧在区域到洲际尺度上的时空变化对于空气质量研究至关重要。在本研究中,对从现代研究和应用回顾性分析中检索到的柱状臭氧总量(TCO)的长期(2009-2020年)网格化数据集(0.5°×0.625°)进行了首次系统评估和分析,对印度地区的版本2(MERRA-2TCO)进行了评估。MERRA-2TCO首先通过观测值(IMDTCO)进行验证,然后进一步与大气红外测深仪(AIRSTCO)卫星数据集进行比较。为了进行深入的比较和统计分析,数据集被分成七个不同的区域,即,喜马拉雅西部(WH),东北(NE),中北部(NC),西北(西北),印度西半岛(WPI),印度东半岛(EPI),印度南半岛(SPI)。描述性统计(NMSE,FB,R,FA2和d)揭示了MERRA-2TCO与德里的IMDTCO与NMSE(0.0013)的显着相关性,FB(-0.029)和瓦拉纳西NMSE(0.0008),FB(-0.014)。简单线性回归分析的结果表明,两个城市的TCO趋势值每十年增加0.31%和0.44%,分别。在印度不同地区,MERRA-2TCO与AIRSTCO的比较显示出0.62-0.87的显着相关性。此外,为了支持布鲁尔的流通模式,观察到柱状臭氧从低(SPI)到高(WH)纬度区域的增加转移。我们的结果表明,MERRA-2臭氧数据集可以有效地用于印度的臭氧空气质量研究,并且这种分析可能会加强对独立,高品质,和一致的臭氧测量,不确定性小。
Accurately determining the spatiotemporal variability of ozone on a regional to intercontinental scale is essential for air quality studies. In the present study, a first systematic evaluation and analysis of long-term (2009-2020) gridded datasets (0.5° × 0.625°) of total columnar ozone (TCO) retrieved from Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2TCO) is evaluated for the Indian region. The MERRA-2TCO is first validated with observations (IMDTCO) and then further compared with the Atmospheric Infrared Sounder (AIRSTCO) satellite datasets. For an in-depth comparison and statistical analysis, the dataset has been segregated into seven distinct regions, i.e., Western Himalaya (WH), North East (NE), North Central (NC), North West (NW), West Peninsula India (WPI), East Peninsula India (EPI), and South Peninsula India (SPI). Descriptive statistics (NMSE, FB, R, FA2, and d) reveals a significant correlation of MERRA-2TCO against IMDTCO for Delhi with NMSE (0.0013), FB (- 0.029) and Varanasi NMSE (0.0008), FB (- 0.014). The results of simple linear regression analysis show an increasing TCO trend value of 0.31% and 0.44% per decade in both the cities, respectively. A comparison of MERRA-2TCO with AIRSTCO shows a significant correlation of 0.62-0.87 in different regions of India. Furthermore, in support of Brewer\'s circulation pattern, an increasing shift of columnar ozone from low (SPI) to high (WH) latitudinal regions is observed. Our results show that the MERRA-2 ozone dataset can be effectively used for ozone air quality studies over India and this analysis may strengthen the need for independent, high-quality, and consistent ozone measurements with small uncertainties.