Abstract

Abstract. The Cloud-Aerosol Transport System (CATS) lidar, on board the International Space Station (ISS), provides a new opportunity for studying aerosol vertical distributions, especially the diurnal variations, from space observations. In this study, we investigate the seasonal variations and diurnal cycles in the vertical aerosol extinction coefficients (AECs) over East Asia by taking advantage of 32 months of continuous and uniform aerosol measurements from the CATS lidar. Over the Tibetan Plateau, a belt of AECs at approximately 6 km between 30 and 38∘ N persistently exists in all seasons with an obvious seasonal variation. In summer, the aerosols at 6 km are identified as a mixture of both anthropogenic aerosols transported from India and coarse dust particles from Asian dust sources. In addition, the high AECs up to 8 km in summer over the Tibetan Plateau are caused by smoke aerosols from thermal dynamic processes. In fall and winter, the northern slope of the plateau is continuously influenced by both dust aerosols and polluted aerosols transported upslope from cities located at lower elevations in northwestern Asia. The diurnal variation in AECs in North China is mainly related to the diurnal variations in the transported dust and local polluted aerosols. Below 2 km, the AEC profiles in North China at 06:00 and 12:00 CST (China standard time) are significantly higher than those at 00:00 and 18:00 CST, reaching a maximum at midday. The aerosol vertical profiles over the Tarim Desert region in summer have obvious diurnal variations, and the AECs at 12:00 and 18:00 CST are significantly higher than those at 00:00 and 06:00 CST, which are induced by the strong diurnal variations in near-surface wind speeds. In addition, the peak in the AEC profiles has a significant seasonal variation, which is mainly determined by the boundary layer height.

Highlights

  • Knowledge of aerosol optical properties, such as the aerosol optical thickness (AOT) and their vertical distributions, is critical for estimating the effects of aerosol particles on air quality, radiative forcing, and their related impacts on climate (Liu et al, 2011, 2014; Myhre et al, 2013; Ramanathan et al, 2001; Sato et al, 2018; Sato and Suzuki, 2019; Yan and Wang, 2020)

  • MODIS AOTs are systematically higher than Cloud-Aerosol Transport System (CATS) AOTs over East Asia, both CATS and MODIS AOTs yield similar spatial patterns of heavy aerosol loadings clustered in northwestern China, eastern China, and northern India

  • As 1064 nm measurements are less sensitive to fine-mode aerosols, such as smoke and pollutant aerosols, compared with coarse aerosols, such as dust aerosols, the CATS has some difficulty catching the seasonal variations in AOTs in eastern China, which are controlled by fine particles

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Summary

Introduction

Knowledge of aerosol optical properties, such as the aerosol optical thickness (AOT) and their vertical distributions, is critical for estimating the effects of aerosol particles on air quality, radiative forcing, and their related impacts on climate (Liu et al, 2011, 2014; Myhre et al, 2013; Ramanathan et al, 2001; Sato et al, 2018; Sato and Suzuki, 2019; Yan and Wang, 2020). The Cloud-Aerosol Transport System (CATS) lidar is installed on board the International Space Station (ISS) and observes with a nearly 3 d repeat cycle (McGill et al, 2015). It can provide a new opportunity for studying diurnal variations in aerosol vertical distributions from space observations at the global scale. It is imperative to provide insights into the seasonal variations and diurnal cycles of the aerosol vertical features across East Asia. In this paper, we present the results of the analysis of temporal–spatial distributions of AOTs and the aerosol extinction coefficients (AECs) observed by CATS collected from 2015 to 2017 over East Asia.

Selected regions
Datasets
Seasonal variations in AOTs in East Asia
Meridional cross sections of AECs and ADRs over selected regions
North China
Tibetan Plateau
Tarim Basin
Seasonal and diurnal variations in AEC profiles over selected regions
Summary and conclusions
Full Text
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