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Stratospheric O3

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In a similar way the stratospheric NO2 slant column density, exactly for the SCIAMACHY overpass time, is derived from the stratospheric chemistry transport model ROSE at DLR-DFD. To avoid a bias, the modelled analyses are scaled to ‘clean conditions’ over the Pacific Ocean. The tropospheric NO2 slant column is then extracted by subtracting the modelled stratospheric slant column from the retrieved total slant column. Fig. 5-13 shows the resulting tropospheric NO2 distribution over Europe. The tropospheric NO2 distributions can be further improved by using NO2 profile shapes estimated by air quality models like EURAD. In this case also properties of clouds, aerosols and the surface have to be taken into account.


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fig. 5-13:

Mean tropospheric NO2 vertical column densities over Europe as derived from SCIAMACHY for August to October 2005 with the DLR-DFD assimilation approach. (Image: T. Erbertseder, DLR-DFD)

5.6.2 Stratospheric O3

Assimilated total column and stratospheric profile fields are ideally suited for applications such as scientific studies of the evolution of the ozone layer and of special events (e.g. ozone hole or low ozone episodes) or inter-comparisons with models (e.g. study of dynamical and chemical processes). Since assimilated fields are globally available, comparison with independent observations can be performed without space/time mismatches.

Stratospheric O3 is also of particular interest as it can be assimilated into operational weather forecasts and improves the model representation of stratospheric wind fields and thereby the quality of the forecast. Since forecast services are provided on short timescales, the availability of near-realtime O3 data is essential. Total columns of ozone can be derived from SCIAMACHY measured backscatter reflectivities in near-realtime (Eskes et al. 2005). These ozone columns serve as an input for the assimilation analysis and a subsequent forecast of how the stratospheric ozone layer will develop in the upcoming 9 days. The assimilation yields a complete picture of the global ozone distribution (see fig. 5-14). Within the error margins of both model and observations it is consistent with observations and our knowledge of atmospheric transport and chemistry (Eskes et al. 2002, Eskes et al. 2003). SCIAMACHY ozone columns are currently also assimilated operationally in the numerical weather prediction model of the ECMWF. Several centres use the ozone forecasts for UV radiation predictions.

To further analyse and quantify atmospheric processes such as ozone depletion or ozone loss rates, an optimal combination of models and asynoptic or heterogeneously distributed observations is essential. By using for example the ROSE transport model, SCIAMACHY observations of O3, NO2, OClO and BrO can be assimilated in order to derive a consistent global chemical analysis of the stratosphere.


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fig. 5-14:

A forecasted North Pole view of the assimilated total ozone column field for November 3rd, 2005 at 12:00 UTC based on SCIAMACHY data. (Image: KNMI/ESA)


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