HR: 11:20h
AN: A12A-05    [Abstracts]
TI: Combined use of MODIS, MISR, CERES, and a data assimilation method for estimating aerosol climate forcing over Saharan regions
AU: * Zhang, J
EM: jzhang@atmos.und.edu
AF: Dept. of Atmospheric science, University of North Dakota, 4149 University Avenue Stop 9006, Grand Forks, ND 58202-9006,
AU: Reid, J S
AF: Naval Research Laboratory, Marine Meteorology Division, 7 Grace Hopper Ave., Stop 2, Monterey, CA 93943-5502,
AU: Hyer, E J
AF: Naval Research Laboratory, Marine Meteorology Division, 7 Grace Hopper Ave., Stop 2, Monterey, CA 93943-5502,
AU: Westphal, D L
AF: Naval Research Laboratory, Marine Meteorology Division, 7 Grace Hopper Ave., Stop 2, Monterey, CA 93943-5502,
AU: Hsu, C
AF: NASA Goddard Space Flight Center, Code 613.2 NASA/GSFC, Greenbelt, MD 20771,
AU: Christopher, S A
AF: University of Alabama in Huntsville, 320 Sparkman Drive, NSSTC, Huntsville, AL 35806,
AU: Kahn, R A
AF: NASA Goddard Space Flight Center, Code 613.2 NASA/GSFC, Greenbelt, MD 20771,
AB: Advanced satellite aerosol optical depth retrievals and datasets now allow the scientific community an unprecedented volume of observations of the global aerosol distribution. Each algorithm has advantages and disadvantages, and no single dataset can boast top performance everywhere over the globe. Furthermore, satellite aerosol retrievals, to varying degree, are limited to cloud free skies, and thus are subject to clear-sky bias and other contextual biases. For this study, we developed a multi-sensor aerosol optical depth analysis over Saharan regions by assimilating MODIS and MISR aerosol products into NRL Aerosol Analysis and Prediction System (NAAPS) using a recently developed aerosol data assimilation package (NAVDAS-AP). Studies showed that the new aerosol data assimilation system allows for very accurate modeling of larger aerosol features. Using the aerosol optical depth analysis developed from this study, we estimated aerosol climate forcing over Saharan regions. The aerosol climate forcing values derived from this study were compared with measurement- based aerosol forcing estimates. Contextual and clear sky biases that are associated with the measurement- based forcing estimates are also examined.
DE: 3315 Data assimilation
DE: 3360 Remote sensing
DE: 4801 Aerosols (0305, 4906)
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting