HR: 08:20h
AN: A11E-02 INVITED    [Abstracts]
TI: merging the strengths of different remote sensing techniques for global aerosol data-sets
AU: * Kinne, S
EM: stefan.kinne@zmaw.de
AF: Max-Planck-Institute for Meteorology, Bundesstrasse 53, Hamburg, 20146, Germany
AB: Adequate global distributions of aerosol properties are essential for quality estimate of the aerosol impact on climate. With new aerosol dedicated space sensors during the last decade, regional, seasonal and vertical distributions of aerosol, many different (complementary and/or redundant) aerosol data-sets are offered. Even for the most important aerosol property (the aerosol optical depth AOD) differences among sensor retrievals are commonly on the order of the retrieved value. This is explained in part by retrieval differences, as they are tied to specific sensor capabilities and in part by necessary a-priori assumptions (e.g. aerosol absorption, background reflection). In other words, satellite retrievals have different regional and seasonal strengths. Or alternatively, weaknesses often do not allow for globally (and temporarily) complete coverage. Thus, the overall goal is to combine strengths of individual retrievals to yield a product superior to any single retrieval in accuracy and/or spatial and temporal coverage. The overall concept is to select a particular space-retrieval superiority based on statistical (e.g. bias, error) comparisons to quality references (e.g. statistics from sun-/sky-photometry) and to combine individual regional and seasonal choices into data composites. Space sensors participants for tropospheric aerosol data-sets considered in this study are multi-annual monthly statistics offered by MODIS (collection 5), MISR, TOMS, POLDER and several AVHRR retrievals, while AERONET data represent the quality reference. In addition, to the retrieval composites also improved composites are offered, in which quality references are directly forced (or merged) into the satellite sensor composites for improved accuracy (since even the ‘best' performing satellite retrieval is usually still biased with respect to the quality reference). New global aerosol property composite products tied to measurements are presented and discussed (also in the context of individual sensor products).
DE: 0305 Aerosols and particles (0345, 4801, 4906)
DE: 0345 Pollution: urban and regional (0305, 0478, 4251)
DE: 0520 Data analysis: algorithms and implementation
DE: 3311 Clouds and aerosols
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting