Improving GEOS-Chem Model Tropospheric Ozone through Assimilation of Pseudo Tropospheric Emission Spectrometer Profile Retrievals

  • Authors:

  • Kumaresh Singh;Paul Eller;Adrian Sandu;Kevin Bowman;Dylan Jones;Meemong Lee

  • Affiliations:

  • Department of Computer Science, Virginia Tech, Blacksburg VA 24060;Department of Computer Science, Virginia Tech, Blacksburg VA 24060;Department of Computer Science, Virginia Tech, Blacksburg VA 24060;NASA Jet Propulsion Laboratory, Padadena, USA CA 91109;Department of Physics, University of Toronto, Toronto, Canada;NASA Jet Propulsion Laboratory, Padadena, USA CA 91109

  • Venue:
  • ICCS 2009 Proceedings of the 9th International Conference on Computational Science
  • Year:
  • 2009

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Abstract

4D-variational or adjoint-based data assimilation provides a powerful means for integrating observations with models to estimate an optimal atmospheric state and to characterize the sensitivity of that state to the processes controlling it.In this paper we present the improvement of 2006 summer time distribution of global tropospheric ozone through assimilation of pseudo profile retrievals from the Tropospheric Emission Spectrometer (TES) into the GEOS-Chem global chemical transport model based on a recently-developed adjoint model of GEOS-Chem v7. We are the first to construct an adjoint of the linearized ozone parameterization (linoz) scheme that can be of very high importance in quantifying the amount of tropospheric ozone due to upper boundary exchanges. Tests conducted at various geographical levels show that the mismatch between adjoint values and their finite difference approximations could be up to 87% if linoz module adjoint is not used, leading to a divergence in the quasi-Newton approximation algorithm (L-BFGS) during data assimilation. We also present performance improvements in this adjoint model in terms of memory usage and speed. With the parallelization of each science process adjoint subroutine and sub-optimal combination of checkpoints and recalculations, the improved adjoint model is as efficient as the forward GEOS-Chem model.