Physical Basis, Premises, and Self-Consistency Checks of Aerosol Retrievals from TRMM VIRS

Abstract

This paper outlines the processing stream for aerosol retrievals over oceans from the visible and infrared scanner [VIRS; a five-channel radiometer similar to the National Oceanic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (AVHRR)] aboard the Tropical Rainfall Measuring Mission (TRMM) satellite, launched in November 1997. Emphasis is on 1) the applying the previously developed AVHRR second-generation aerosol retrieval algorithm to VIRS data to derive an aerosol parameter, indicative of particle size; 2) removing the unwanted “thermal leak” signal in the 1.61-μm channel; 3) giving examples of the first aerosol retrievals from space at this wavelength; and 4) assessing the accuracy of the retrievals with theoretical error analyses and empirical self- and interconsistency checks. Aerosol optical depths τA1 and τA2 are retrieved from reflected solar radiances in VIRS channels 1 and 2 centered at wavelengths λ1 = 0.63 and λ2 = 1.61 μm, using two independent lookup tables. When τA1 and τA2 exceed a certain threshold τAmin an effective Ångström exponent α related to particle size is derived as α = −ln(τA1/τA2)/ln(λ1/λ2). Channel 2 is contaminated by a thermal leak, originating from a secondary spectral response peak centered at ∼5.2 μm. If uncorrected, it leads to errors in τA2 of 100% or more. To minimize this error, nighttime VIRS “dark” radiances in channel 2 have been related empirically to radiances in channels 4 and 5 (10.8 and 12 μm, respectively), and view angle through regression analyses. The reflected component in channel-2 daytime measurements is estimated by subtracting the empirically derived thermal component from the total signal and is used in the retrieval of τA2. Theoretical error analysis is used to identify the limitations of the VIRS retrieval algorithm, whereas actual retrievals are preliminarily evaluated using a set of specially developed empirical checks. The checks show, on average, a high degree of self- and interconsistency but also identify problems with the retrievals, the most noteworthy being trends in retrieved optical depths with viewing and illumination angles. These problems will be tackled in the next-generation aerosol retrieval algorithm.