对流层臭氧卫星遥感反演综述

Tropospheric Ozone Retrieval from Satellite Remote Sensing—A Review

臭氧是地球大气中最重要的痕量气体之一,在气候变化和生态环境中均扮演着至关重要的角色。对流层臭氧作为光化学烟雾的重要成分之一,其浓度变化与人类活动息息相关。基于卫星遥感技术监测对流层臭氧浓度可以帮助我们更好地发现和定量解释对流层臭氧在不同季节、不同时刻以及不同区域的变化特征,探讨臭氧在对流层中的成因机制。随着卫星遥感技术的全面发展,臭氧遥感产品(例如臭氧总量、廓线等)无论在产品精度或是时空分辨率方面均取得了显著进步,然而,由于受较弱卫星信号与复杂下垫面的影响,对流层臭氧遥感产品精度仍无法满足目前对流层大气成分的精细化科学应用研究。主要围绕对流层臭氧卫星遥感,回顾和分析了臭氧卫星遥感载荷的发展历程和现状,结果表明国内外已基于不同谱段(紫外—可见光、热红外和太赫兹)实现了全球及区域臭氧的时空分布探测;讨论了基于不同技术遥感反演算法(直接与间接反演、多波段联合反演、天底—临边协同反演、基于机器学习技术的创新算法等)的特点及适用性,分析表明算法精度的提升包括从复杂大气背景下的辐射传输模拟、基于地面观测的先验信息优化以及仪器定标与信噪比等多方面的工作;展望了卫星遥感在全球和区域尺度提供可靠对流层臭氧观测数据的应用前景,为对流层臭氧污染的形成机理、人类活动与气候变化如何影响对流层臭氧浓度变化等方面的研究提供关键数据支撑。

Ozone is among the most important trace gases in Earth's atmosphere and plays a crucial role in both climate change and ecology. Tropospheric ozone is an important component of photochemical smog, and its variations are closely related to human activity. Monitoring of tropospheric ozone based on satellite remote sensing can help us better understand and quantitatively explain the characteristics of tropospheric ozone changes in different seasons, times, and regions, and explore the mechanism of ozone generation in the troposphere. With the comprehensive development of satellite remote sensing techniques, ozone remote sensing products(e.g., total ozone, profiles, etc.) have improved significantly in terms of accuracy and spatiotemporal resolution. However,the accuracy of tropospheric ozone products is still not sufficient for the current scientific application of the atmospheric composition of the troposphere due to the weak satellite signals and complexity of the subsurface.This review focuses on satellite remote sensing of tropospheric ozone. It outlines and analyzes the development history and current status of ozone satellite remote sensing payloads and discusses the characteristics and applicability of remote sensing retrieval algorithms based on different technologies(direct and indirect retrieval,multiband joint retrieval, collaborated nadir-limb retrieval, and innovative algorithms based on machine learning techniques). It further discusses the application of satellite remote sensing for the provision of reliable tropospheric ozone observation data at the global and regional scales. Overall, this review envisions the application of satellite remote sensing for providing reliable tropospheric ozone observations at the global and regional scales.