Task 252

Improving AOD retrieval over ocean from MODIS

Principal Investigator(s):

Jaehwa Lee


N. Christina Hsu

Last Updated:

October 26, 2012 15:26:16

Description of Problem

Aerosols exert a significant impact on climate change and air quality. These small airborne particles regulate the radiation budget through their direct and indirect effects (IPCC, 2007), or more specifically, by scattering and absorbing radiation and by modifying the microphysics of clouds. In the sense that aerosol shows highly variable spatial and temporal properties, the observations made from satellite, such as Moderate Resolution Spectroradiometer (MODIS) aboard the Terra and Aqua satellites, provide an unprecedented opportunity to investigate aerosol properties (AOP). However, a recent validation by Remer et al. (2008) showed underestimation of aerosol optical depth (AOD) over the ocean from Aqua-MODIS for high AOD case in particular. To resolve this issue, this study aims to improve AOD accuracy using new aerosol models archived by integrating Aerosol Robotic Network (AERONET) inversion data (Dubovik and King, 2000; Dubovik et al., 2006) and a tri-axial ellipsoidal dust database data (Meng et al., 2010).

Scientific Objectives and Approach

Simulation of satellite-observed top-of-atmosphere (TOA) reflectance using a radiative transfer model (RTM) requires aerosol characteristics such as spectral refractive indices, size distribution, and nonsphericity when resolving nonspherical particles. Otherwise, spectral AOD, SSA, and phase function, which are derived from the aforementioned aerosol properties, are required instead. Thus, long-term AERONET inversion data that provides the aforementioned AOP for the globe can be used to simulate the satellite signal for various aerosol types. To create improved aerosol model based on AERONET retrievals, the aerosol models are first classified using fine-mode fraction (FMF) and single scattering albedo (SSA). Then, each aerosol model is further categorized as a function of AOD. Since the AERONET inversion data provide AOP for wavelengths ranging from 440 nm to 1020 nm, while the MODIS observations cover the wavelengths from 470 nm to 2120 nm, the wavelength range is extended using the tri-axial ellipsoidal dust database data.


The new aerosol models improve correlation between AERONET-observed AOD and MODIS-retrieved AOD compared to the MODIS Collection 5 products with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85, respectively, for the MODIS operational algorithm. Moreover, use of the new algorithms increases the percentage of data within an expected error of ±(0.03 + 0.05 × AOD) from 62% to 64% overall and from 39% to 51% for AOD > 0.3.