Aerosol optical depth and surface reflectance retrieval over land using geostationary satellite data

In this paper, an analytical strategy is presented to retrieve jointly aerosol optical depth (AOD) and surface reflectance (R) from geostationary satellites. The new algorithm is based on a parameterization of the atmospheric radiative transfer model. Taking AOD and R as unknown parameters and based on some reasonable assumptions of AOD's spatial consistence and R's temporal invariance, both parameters of each pixel can be derived. Applying this algorithm to data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations on board Meteosat Second Generation (MSG), we obtain regional maps of AOD and R from two adjacent observations. Preliminary validation results by comparing our retrieved AOD with Aerosol Robotic Network (AERONET) data show good accuracy, and retrieved R is also reasonable. This method is potential to be applied in instantaneously monitoring aerosol spatio-temporal variation using geostationary satellite sensors with only one single visible channel and high-frequency observations.

1. INTRODUCTION

Atmospheric aerosols play a critical role in the global radiation balance, thus significantly impact climate change in both direct and indirect ways [1], [2]. However, they are not yet well understood, causing a major uncertainty in relevant researches. Due to aerosols' spatial and temporal nonuniformity, it's crucial to gain a knowledge of aerosols on a range of scales, for which satellite remote sensing is an ideal way [3]. Many algorithms have been exploited to monitor global aerosol properties by multi-wavelength, multi-angle, and polarimetric observations, making it possible to study aerosols' spatial distribution, temporal variation, intrinsic modes, vertical distribution, light absorption, and spectral characteristics [4].