论文信息 - Improving Global Chemical Simulations WithVariational Assimilation Of GOME Data

Improving Global Chemical Simulations WithVariational Assimilation Of GOME Data

Data assimilation, which plays an important role in the analysis of atmospheric data, in particular in Numerical Weather Prediction (NWP), is increasingly being used to analyze photochemical data. This paper presents how MOCAGE CTM simulations of global ozone have been improved using a variational assimilation scheme. The analysis of the retrieved ozone profiles from the GOME nadirviewing spectrometer increases the quality of MOCAGE forecasts in terms of ozone profiles and total columns.

S. Massart | S. Massart

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