气溶胶
数据同化
环境科学
气象学
激光雷达
卫星
同化(音韵学)
遥感
薄雾
大气科学
地质学
地理
航空航天工程
工程类
语言学
哲学
作者
Ting Yang,Hongyi Li,Haibo Wang,Youwen Sun,Xi Chen,Futing Wang,Lei Xu,Zifa Wang
标识
DOI:10.1016/j.jes.2022.04.012
摘要
Observations and numerical models are mainly used to investigate the spatiotemporal distribution and vertical structure characteristics of aerosols to understand aerosol pollution and its effects. However, the limitations of observations and the uncertainties of numerical models bias aerosol calculations and predictions. Data assimilation combines observations and numerical models to improve the accuracy of the initial, analytical fields of models and promote the development of atmospheric aerosol pollution research. Numerous studies have been conducted to integrate multi-source data, such as aerosol optical depth and aerosol extinction coefficient profile, into various chemical transport models using various data assimilation algorithms and have achieved good assimilation results. The definition of data assimilation and the main algorithms will be briefly presented, and the progress of aerosol assimilation according to two types of aerosol data, namely, aerosol optical depth and extinction coefficient, will be presented. The application of vertical aerosol data assimilation, as well as the future trends and challenges of aerosol data assimilation, will be further analysed.
科研通智能强力驱动
Strongly Powered by AbleSci AI