Development of a Global Validation Package for Satellite Oceanic Aerosol Optical Thickness Retrieval Based on AERONET Observations and Its Application to NOAA/NESDIS Operational Aerosol Retrievals

Abstract

In this paper, a global validation package for satellite aerosol optical thickness retrieval using the Aerosol Robotic Network (AERONET) observations as ground truth is described. To standardize the validation procedure, the optimum time–space match-up window, the ensemble statistical analysis method, the best selection of AERONET channels, and the numerical scheme used to interpolate/extrapolate these observations to satellite channels have been identified through sensitivity studies. The package is shown to be a unique tool for more objective validation and intercomparison of satellite aerosol retrievals, helping to satisfy an increasingly important requirement of the satellite aerosol remote sensing community. Results of applying the package to the second-generation operational aerosol observational data (AEROBS) from the NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) in 1998 and to the same year aerosol observation data [Clouds and the Earth's Radiant Energy System-Single Scanner Foodprint version 4 (CERES-SSF4)] from the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanner (VIRS) are presented as examples of global validation. The usefulness of the package for identifying improvements to the aerosol optical thickness τ retrieval algorithm is also demonstrated. The principal causes of systematic errors in the current National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite, Data, and Information Service (NESDIS) operational aerosol optical thickness retrieval algorithm have been identified and can be reduced significantly, if the correction and adjustment suggested from the global validation are adopted. Random error in the τ retrieval is identified to be a major source of error on deriving the effective Ångström wavelength exponent α and may be associated with regional differences in aerosol particles, which are not accounted for in the current second-generation operational algorithm. Adjustments to the nonaerosol and aerosol radiative transfer model parameters that reduce systematic errors in τ retrievals are suggested for consideration in the next-generation algorithm. Basic features that should be included in the next-generation algorithm to reduce random error in τ retrievals and the resulting error in the effective Ångström wavelength exponent have also been discussed. Compared to the AERONET observation, the NOAA-14 AVHRR (AEROBS) τ values for mean conditions are biased high by 0.05 and 0.08, with random errors of 0.08 and 0.05, at 0.63 and 0.83 μm, respectively. Correspondingly, the TRMM VIRS (CERES-SSF4) values for mean conditions are biased high by 0.06 and 0.02, with random errors of 0.06 and 0.04 at 0.63 and 1.61 μm, respectively. After corrections and adjustments to the retrieval algorithm, the biases in both channels of AVHRR and VIRS are reduced significantly to values close to zero, although random error is almost unchanged. The α exponent derived directly from the aerosol optical thicknesses (τs) has been shown to be poorly correlated both before and after adjustments, indicating that random error in the τ measurement (possibly related to aerosol model parameter variations or cloud–surface reflectance contamination) needs to be reduced.