Modeling Satellite Correlations of Aerosol Optical Depth Versus Cloud Optical Depth Over Megacities

Stanford University, Stanford CA

Investigators

Abstract

This project seeks to gain a better understanding of aerosol/cloud interactions and the effects of these on global temperatures. The research is based on investigating satellite measurements of the thickness of aerosols (small particles) and clouds in the atmosphere over several global megacities. Data from a prior study over 2 megacities suggest that as the thickness of aerosols increases in the atmosphere, the density of clouds tends also to increase to a point, but then begins to decrease. Since satellite data can show correlations but not cause and effect, and models can show cause/effect, a computer model will be used in this project to simulate the relationship between clouds and aerosols over three megacities. The results will help to improve the ability of computer models to predict global climate change. This research focuses on the investigating satellite measurements of aerosol optical depth (AOD) and cloud optical depth (COD) over several megacities to assess the relative importance of different types of aerosol feedbacks on clouds. Previously a boomerang curve was identified (an increase then a decrease of COD with increasing AOD) where the increase in COD at low AOD is believed to be due to microphysical (indirect) effects and a decrease in COD at high AOD is thought to be due to radiative effects (cloud absorption effects and the semidirect effect). The project consists of three tasks: 1) complete the satellite retrieval worked performed for the first part of the project over one more megacity region, New Delhi India; 2) use a nested global-through-local 3-D model (GATOR-GCMOM) to determine whether the boomerang curves found in the satellite data can be attributed to absorbing aerosols; and 3) run a 24-year global baseline simulation and sensitivity simulations examining the separate effects of fossil-fuel soot, solid biofuel soot and gases, biomass burning soot and gases, methane, and all anthropogenic components on global climate, accounting for indirect effects, semi-direct effect, and the cloud absorption effect. To evaluate the significance of the model results, a two-sided t-test for unequal sample sizes of unequal variance will be used to determine whether the computer modeled difference in a given parameter between a baseline simulation and a sensitivity simulation is statistically significant relative to chaotic variation in a climate model.