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Four dimensional variational assimilation of MIPAS stratospheric trace gas observations into the SACADA global chemistry circulation model
Jörg Schwinger(1)and Hendrik Elbern(1)
(1)
University of Cologne,
Aachener Straße 201-209,
50931 Köln,
Germany
Abstract
Stratospheric trace gas observations from space borne platforms such
as ENVISAT are by nature scattered in time and space. Thus a meaningful
analysis of the atmospheric chemical state derived from these data
involves the application of advanced spatio-temporal data assimilation
methods. Four dimensional variational (4D-Var) data assimilation provides a powerful technique to combine observations, statistical information,and three-dimensional chemistry circulation models delivering a "Best Linear Unbiased Estimate" (BLUE) of the stratosphere's chemical state.
A 4D-var data assimilation system intended for operational application has been developed by the AFO-2000 project consortium SACADA. The System has several novel features: Kernel of the system is a stratospheric global chemistry circulation model (GCCM) and its adjoint version. The German Weather Service global forecast model (GME) serves as an online meteorological driver, its icosahedral grid structure, the horizontal transport and the parallelisation strategy are adopted to the GCCM. The stratospheric chemistry module accounts for 148 gas phase and 7 heterogenous reactions between 43 stratospheric constituents.
MIPAS stratospheric trace gas profiles from selected periods each
covering six weeks in 2002 and 2003, have been assimilated into the new
SACADA-system. Due to the superior efficiency and parallel performance of the new system, the computationally demanding 4D-Var technique is able to produce near-real-time results, reducing the discrepancies
between observations and the model significantly while chemical consistency is maintained. Assimilated fields have been compared to independent data sets from the SAGE II and the HALOE instruments. The posteori statistical evaluation of quantities like observation minus analysis time series, provides a valuable means for the identification of possible inconsistencies between retrieved trace gas profiles and the current physical and chemical knowledge of stratospheric processes, which is encoded in the model. It is demonstrated that a 4D-Var system may be helpful to improve both, the atmosperic model and the trace gas profile retrieval process.
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