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IMPROVING ASSET OZONE ANALYSES WITH MULTI-SENSORS ASSIMILATION

Data assimilation has became an useful tool to reanalyse atmospheric fields. The assimilation produces 4dimensional, quality controlled fields that can offer many advantages, compared to sparse observations, in exploring physical phenomena. During the recent Framework 5 Assimilation of Envisat Data (ASSET) project, an intercomparison was made of ozone analyses from several assimilation systems. These analyses were produced for the same period July to November 2003 and the majority of them assimilated stratospheric ozone observations from only one source, usually the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) or the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). To improve on the quality of the ozone analyses produced by the ASSET intercomparison, we want to assimilate additional ozone data into three assimilation systems: Meteo-France, Met Office and KNMI. In order to make the best possible use of the data, we propose to correct the data according to a model derived from several ASSET analyses. This approach is illustrated using the Submillimetre Radiometer (SMR) data. The ultimate goal of this work is to show how the addition of pertinent information to an assimilation system can increase the quality of the analysed fields compared to independent data.