Toward unified satellite climatology of aerosol properties. 3. MODIS versus...

The core information for this publication's citation.: 
Mishchenko, M., L. Liu, I. Geogdzhayev, L. D. Travis, B. Cairns, and A. Lacis (2010), Toward unified satellite climatology of aerosol properties. 3. MODIS versus MISR versus AERONET, J. Quant. Spectrosc. Radiat. Transfer, 111, 540-552, doi:10.1016/j.jqsrt.2009.11.003.
Abstract: 

We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(MODIS) +AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

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Research Program: 
Radiation Science Program (RSP)
Mission: 
EOS