For more than a decade, studies have shown that remote sensing of aerosols from space provide a valuable mean for measuring the spatial distribution of aerosol physical and optical properties from both regional and global perspectives. Satellite aerosol retrievals have been used in many applications from aerosol climate forcing to air quality studies as well as for the correction of a number of land and ocean products. Recently, space observation has advanced to a level where it is possible to integrate near real time satellite aerosol retrievals with numerical models to improve aerosol forecasting. However, although studies have shown that the assimilation of satellite meteorological observations into numerical weather prediction models improves the accuracy of numerical weather forecasts (especially over regions with few conventional observations), the successful assimilation for aerosol forecasting remains an unsolved research topic. This is in part because satellite aerosol datasets can at times be more uncertain than the models themselves. This is especially true in regions with cirrus clouds, coastal waters and complicated land features. Objective analyses of the true benefits and uncertainties of such data have yet to be performed.

Currently the MODerate-resolution Imaging Spectroradiometers (MODIS) level II aerosol product (MOD04/MYD04) is the best aerosol optical depth product for near real time aerosol data assimilation. Using one year's worth of data we evaluated MODIS level 2 aerosol product over the global oceans. Our research is further extended to study the error matrix and error variance of MODIS level 2 aerosol products that is associated with observing conditions. Regional differences in the efficacy of aerosol optical depth estimates are explored and in part related to aerosol microphysics as well as other retrieval phenomenon. Using the error statistics in heterogeneous environments, we also estimated the impact of MODIS errors on aerosol direct forcing that is derived from the combining of the Clouds and the Earth's Radiant Energy System (CERES) and MODIS aerosol product. Lastly, preliminary results are shown for assimilating of MODIS aerosol optical depth retrievals into the Navy Aerosol Analysis and Prediction System (NAAPS) for near real time aerosol forecasting.

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