12 January 2024 Exploring impacts of aerosol on convective clouds using satellite remote sensing and machine learning
Jiaqin Mi, Yuanjian Yang, Shuxue Zhou, Xiaoyan Ma, Siying Wei
Author Affiliations +
Abstract

Aerosol–cloud–precipitation interaction is currently a research hotspot that is challenging but also one of the most prominent sources of uncertainty affecting climate change. We have identified 1082 mesoscale convective systems (MCSs) over eastern China from April to September in 2016 and 2017. Overall, the occurrence frequency and MCS area increased when altitude increased, as demonstrated by the t-test at 95% confidence. More MCSs appeared and matured fully, although they moved slowly, in a selected urban agglomeration area compared to a selected rural area, owing to the urbanization impact. With an increase in the concentration of particulate matter with particle size below 10 μm (PM10) averaged by the first 3 h of MCS initiations, the cloud top brightness temperature and MCS area decreased, resulting in weakened precipitation intensity and a smaller MCS area. The t-test was passed with 90% confidence, confirming this finding. In addition, high-humidity circumstances can produce enough water vapor to support the creation of many higher and deeper MCSs.

© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE)
Jiaqin Mi, Yuanjian Yang, Shuxue Zhou, Xiaoyan Ma, and Siying Wei "Exploring impacts of aerosol on convective clouds using satellite remote sensing and machine learning," Journal of Applied Remote Sensing 18(1), 012007 (12 January 2024). https://doi.org/10.1117/1.JRS.18.012007
Received: 1 May 2023; Accepted: 20 October 2023; Published: 12 January 2024
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KEYWORDS
Clouds

Aerosols

Atmospheric modeling

Data modeling

Air quality

Meteorology

Environmental monitoring

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