Satellite Detection of Effects of Absorbing Aerosols on Clouds over Urban Areas

点击翻译按钮获取中文摘要

This project will use satellite retrievals of aerosol optical depth versus cloud optical depth and cloud fraction to examine whether "boomerang" curves can be detected in three regions of the world that are sources of significant anthropogenic emissions from fossil fuels and/or solid biofuels. "Boomerang" refers to an increase followed by a decrease in cloud optical depth (COD) with increasing aerosol optical depth (AOD), which has been observed over Brazil where biomass burning is a dominant influence on atmospheric composition. The regions to be examined will include one urbanized region in China, one in India, and a third in Southern California. For each region, analyses of five years of satellite data will be carried out. The reason polluted urbanized regions will be targeted is because changes in COD and AOD should be more detectable than in non-urbanized regions. Nevertheless, the regions selected will be large enough to include rural as well as urban areas. As a result, differences between rural and urban areas can and will also be examined to determine whether microphysical or radiative effects dominate more in urban versus rural areas. Data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument onboard the Aqua satellite with overpasses at approximately 1:30 PM local time will be used. This instrument provides relatively high spatial resolution (250 to 500 meters) data with near global coverage on a daily basis. MODIS Swath Level 2 aerosol, cloud, water vapor, and stability products will be employed.The results will provide input for future modeling studies to reduce one of the greatest uncertainties surrounding the effects of aerosols on climate, that of absorbing aerosols on cloudiness. This will ultimately advance understanding of the effects of absorbing aerosol (particularly black carbon) on climate because the cloud absorption effect has been ignored in all international assessments to date. A graduate student will be trained through participation in the project.