EaKF based method for assimilating trace gas and primary aerosols in the GEOS-CHEM model: Preliminary Results

The availability of measurements of atmospheric chemical constituents from satellite platforms offers an opportunity to better understand changes in tropospheric chemical composition on a global scale through the integration of measurements with predictions from chemical transport models (CTMs). Such integrated approach also helps improve the ability of forecasts of CTMs and arrive at better public policy. We present a global atmospheric data assimilation platform integrating an atmospheric chemical transport model, GEOS-Chem v8-01-01, and a data assimilation package, Data Assimilation Research Testbed (DART), developed by the National Center for Atmospheric Research (NCAR). In this study, DART is incorporated to GEOS-Chem to create an ensemble adjusted Kalman Filters (EAKF)- enabled assimilation platform. Tropospheric carbon monoxide (CO) observation data from the Measurement Of Pollution In The Troposphere (MOPITT) is used in preliminary simulations. We run GEOS-Chem global-scale simulations with 2o by 2.5o resolutions for 2006 summer (Jun-July-August) with eighteen month (January 2005 to May 2006) spin-up simulations. For June 2006 benchmark runs, at the vertical level of 850 hPa, GEOS-Chem simulations show high CO concentrations over southwestern Africa, eastern China and U.S. without data assimilations. When comparing with MOPITT observation data, GEOS-Chem simulations show an underestimation in CO concentrations over the North America while overestimations are found over the Southwest Africa. The bias is likely resulted from emission estimates from those regions. We will present results from the EaKF enabled GEOS-Chem model assimilating the MOPPITT CO using twenty five member ensemble.