HR: 0800h
AN: A41A-0022    [Abstracts]
TI: Monitoring of Tropospheric Emission Spectrometer Ozone Data by Assimilation of EOS-Aura Data
AU: * Wargan, K
EM: wargan@gmao.gsfc.nasa.gov
AF: NASA/GMAO, Goddard Space Flight Center Code 610.1, Greenbelt, MD 20771 United States
AU: * Wargan, K
EM: wargan@gmao.gsfc.nasa.gov
AF: SAIC, 4600 Powder Mill Road 400, Beltsville, MD 207052675 United States
AU: Bowman, K
EM: Kevin.Bowman@jpl.nasa.gov
AF: NASA/JPL, 4800 Oak Grove Drive, Pasadena, CA 91109 United States
AU: Stajner, I
EM: istajner@gmao.gsfc.nasa.gov
AF: NASA/GMAO, Goddard Space Flight Center Code 610.1, Greenbelt, MD 20771 United States
AU: Stajner, I
EM: istajner@gmao.gsfc.nasa.gov
AF: SAIC, 4600 Powder Mill Road 400, Beltsville, MD 207052675 United States
AU: Pawson, S
EM: pawson@gmao.gsfc.nasa.gov
AF: NASA/GMAO, Goddard Space Flight Center Code 610.1, Greenbelt, MD 20771 United States
AU: Worden, J
A41A-0022 AF: NASA/JPL, 4800 Oak Grove Drive, Pasadena, CA 91109 United States
AU: Osterman, G
A41A-0022 AF: NASA/JPL, 4800 Oak Grove Drive, Pasadena, CA 91109 United States
AB: The Tropospheric Emission Spectrometer (TES) onboard the Aura satellite provides vertical profile estimates of trace gases such as ozone and carbon monoxide, in both the troposphere and stratosphere. Combining TES data OMI total column ozone and MLS stratospheric ozone profile will provide a comprehensive global view of the vertical structure of ozone in the atmosphere. Use of these three data types in a global Ozone Data Assimilation System (ODAS) will produce a key assimilated data product for use in studies on pollution transport, radiative forcing, and chemical forecasting. In this work we present the first steps made toward assimilation of TES ozone data into the ODAS developed at NASA's Global Modeling and Assimilation Office (GMAO). This ODAS currently blends short-term (15 minutes to 3 hours) ozone forecasts with observations from satellite borne sensors such as SBUV, OMI, and MLS. We present comparisons of TES data against an assimilation that includes OMI and MLS data in a "monitoring" mode, which is an important pre-requisite for including TES data directly into the assimilation. Critical to this monitoring is the formalism necessary to assimilate TES data, especially the development of a non-linear observation operator that accounts for the a priori information used in the retrievals, including averaging kernels. Various statistics of ``observation minus forecast'' (O-F) differences are calculated and investigated, in order to quantify the differences between TES ozone and assimilated OMI+MLS ozone profiles. This approach facilitates the identification of biases, as well as to predict areas of likely impacts that TES will have on ODAS. In addition, the results will be discussed in the context of the work needed to develop suitable error covariance models for TES data in the full assimilation system.
DE: 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE
SC: Atmospheric Sciences [A]
MN: Fall Meeting 2005