The University of Cologne chemistry transport model EURAD and its four-dimensional variational data assimilation implementation is applied to a suite of measurement campaigns for analysing optimal chemical state evolution and flux estimates by inversion. In BERLIOZ and VERTIKO, interest is placed on atmospheric boundary layer processes, while for CONTRACE and SPURT upper troposphere and tropopause height levels are focussed. In order to achieve a high analysis skill, some new key features needed to be developed and added to the model setup. The spatial spreading of introduced observational information can now be conducted by means of a generalised background error covariance matrix. It has been made available as a flexible operator, allowin...
To improve the representation of the atmospheric ozone field given by some observations or a numeric...
Chemical state analyses of the atmosphere based on data assimilation may be degraded by inconsistent...
L'assimilation de données permet de combiner d'une manière optimale un modèle numérique décrivant l'...
The use of models to analyse the complex atmospheric processes deals with a lot of uncertainties of ...
A four-dimensional variational data assimilation system for stratospheric trace gas observations has...
In recent years high resolution data have become available due to the deployment of satellite born i...
A novel stratospheric chemical data assimilation system has been developed and applied to Environmen...
A four-dimensional variational data assimilation system for stratospheric trace gas observations has...
The research activity presented in this manuscript deals with the implementation of a methodology to...
The chemistry transport model system EURAD-IM and its variational data assimilation module are appli...
A four-dimensional variational (4D-Var) data assimilation system for inverse modelling of atmospheri...
Data assimilation combines in an optimal way a numerical model describing the evolution of the atmos...
International audienceThis study aims to assess the potential and limits of an advanced inversion me...
Pollutants in the atmosphere, such as nitrogen oxides and particulate matter, pose a threat to the e...
Data assimilation in geophysical sciences aims at optimally estimating the state of the system or so...
To improve the representation of the atmospheric ozone field given by some observations or a numeric...
Chemical state analyses of the atmosphere based on data assimilation may be degraded by inconsistent...
L'assimilation de données permet de combiner d'une manière optimale un modèle numérique décrivant l'...
The use of models to analyse the complex atmospheric processes deals with a lot of uncertainties of ...
A four-dimensional variational data assimilation system for stratospheric trace gas observations has...
In recent years high resolution data have become available due to the deployment of satellite born i...
A novel stratospheric chemical data assimilation system has been developed and applied to Environmen...
A four-dimensional variational data assimilation system for stratospheric trace gas observations has...
The research activity presented in this manuscript deals with the implementation of a methodology to...
The chemistry transport model system EURAD-IM and its variational data assimilation module are appli...
A four-dimensional variational (4D-Var) data assimilation system for inverse modelling of atmospheri...
Data assimilation combines in an optimal way a numerical model describing the evolution of the atmos...
International audienceThis study aims to assess the potential and limits of an advanced inversion me...
Pollutants in the atmosphere, such as nitrogen oxides and particulate matter, pose a threat to the e...
Data assimilation in geophysical sciences aims at optimally estimating the state of the system or so...
To improve the representation of the atmospheric ozone field given by some observations or a numeric...
Chemical state analyses of the atmosphere based on data assimilation may be degraded by inconsistent...
L'assimilation de données permet de combiner d'une manière optimale un modèle numérique décrivant l'...