Abstract
Abstract. New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the case of high AOD (AOD > 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the single-scattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and MODIS for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the MODIS Collection 5 data. Moreover, the percentage of data within an expected error of ± (0.03 + 0.05 × AOD) is increased from 62% to 64% for overall data and from 39% to 5% for AOD > 0.3. Errors in the retrieved AOD are further characterized with respect to the Ångström exponent (AE), scattering angle (Θ), SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.
Highlights
Aerosols exert a significant impact on climate change and air quality
The results generally show that the C005 aerosol models overestimate the TOA reflectance, i.e., underestimation of aerosol optical depth (AOD) with a given TOA reflectance, compared to the new aerosol models, and the overestimation tends to increase with AOD and absorptivity
The effects of the new aerosol models on AOD retrieval are evaluated by comparing the AODs from Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) data retrieved by the C005 and the test algorithm
Summary
Aerosols exert a significant impact on climate change and air quality. The small airborne particles regulate the radiation budget through both direct and indirect effects (IPCC, 2007), by scattering and absorbing radiation and by modifying cloud microphysics. The Geostationary Ocean Color Imager (GOCI), which observes spectral radiances centered at 412, 443, 490, 555, 660, 680, 745, and 865 nm from a geostationary orbit, has been used for hourly monitoring of AOD and to retrieve the fine-mode fraction (FMF) and aerosol types over East Asia (Lee et al, 2010b) With their wide spatial and spectral coverage, the observations made by the MODIS instruments aboard the Terra and Aqua satellites provide an unprecedented opportunity to infer AOPs. MODIS has 36 spectral bands ranging from 0.41 to 15 μm with three different spatial resolutions (250 m, 500 m, 1 km) and with 2300 km-wide swath coverage. The MODIS algorithms have been frequently updated to improve the quality of retrieved data by modifying cloud-masking processes, aerosol models, and the surface reflectance database (Remer et al, 2005; Levy et al, 2007a, b). The validation results are compared with those from the current operational algorithm to further characterize the effects of the new aerosol models
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