SACADA

Synoptic Analysis of Chemical constituents by Advanced Data Assimilation

Project Description:

Data from existing and forthcoming earth observing satellites such as ENVISAT, EOS-AURA, METOP and others will provide unique possibilities of global measurements of stratospheric chemical species. As satellite data are scattered in time and space and restricted to a limited number of species, these measurements must be complemented by additional information sources to obtain a consistent, four-dimensional picture of chemical processes.

Advanced spatio-temporal data assimilation methods will provide a powerful technique to combine observations, statistical information, and three-dimensional chemistry models. With the inclusion of the respective error estimates, all sources of information can be synthesized to obtain a "Best Linear Unbiased Estimate" (BLUE) of the chemical state and its evolution.

The project SACADA is a collaboration between the following Departments:

• Rhenish Institute for Environmental Research (RIU) / University of Cologne
• German Remote Sensing Data Center (DFD) / DLR
• Institute for Algorithms and Scientific Computing (SCAI) / GMD
• Institute for Environmental Physics / University of Bremen
• Crista Project / University of Wuppertal
• Institute of Meteorology and Climate Research (IMK) / Forschungszentrum Karlsruhe

The objective of SACADA is the development of a comprehensive and efficient chemical data assimilation system for the synoptic analysis (satellite data level 2 to level 3 upgrade and constituent map production) of chemical constituents for routine operation at DLR. These gridded analyses will make value added satellite data accessible for a wide user community, giving an improved return of investment in environmental satellite technologies. The operation of a chemical data assimilation system serves to foster a comprehensive understanding of chemical processes on all time scales: anthropogenic pollution on a diurnal cycle, seasonal ozone destruction, and trends on climatological time scales. Results will be based on all available satellite data together with complex modelling, such that (i) best estimates of the chemical composition of the stratosphere (and partly upper troposphere) are provided, and (ii) thereby high quality input data can be made available for follow up investigations.

To this end the fulfillment of the following requirements is essential: 1. chemical consistency of the analysis products in terms of an approved stratospheric chemistry mechanism, 2. extension of the analyses to non-observed but chemically closely coupled species and stratospheric height profiles, 3. taking account of the identified error statistics of the underlying chemistry transport model during assimilation, 4. efficient and stable automated routine operation, and 5. cross validation of SCIAMACHY and MIPAS data obtained with special observation and retrieval methods.

Distributed over six groups, scheduled work packages comprise the development of

• Algorithms for four-dimensional variational data assimilation (4D-var) (RIU / University of Cologne)
• Error covariance statistics (German Remote Sensing Data Center / DLR),
• Implementation of efficient numerical methods (Institute for Algorithms and Scientific Computing / GMD),
• Analysis evaluation by transport diagnostic algorithms (University of Wuppertal),
• MIPAS sensor nonstandard observation dataset using special inversion methods (Forschungszentrum Karlsruhe, Sacada page)
• SCIAMACHY sensor dataset of solar/lunar occultation observations (University of Bremen)

Principal Investigator:

Hendrik Elbern

Contact:

Hendrik Elbern
Rheinisches Institut für Umweltforschung
Projekt EURAD
Aachener Straße 201-209
50931 Köln

This project is funded by: