Abstract
AbstractObserving system simulation experiments (OSSEs) are performed to examine the impact of ozonesonde observations on a data assimilation system during a simulated satellite data gap during February 2003. Using the four‐dimensional variational chemical data assimilation system SACADA, the relative influence of launch rates and station coverage is investigated. Starting with the VINTERSOL/MATCH campaign, different network and sounding configurations are evaluated. To quantify the performance of assimilation experiments in the lower stratosphere, analysis skill and linear pattern correlation with respect to ERA‐Interim reference data are assessed for the 20 km altitude level. Using first‐guess and analysis minus observation error statistics, a priori error settings are tuned to optimise the assimilation of simulated and real‐world ozone soundings. In summary, it is found that, during satellite data gaps, ozonesonde data can have a significant positive impact on the mean analysis skill depending both on the number of observations and the network layout. A better distributed network based on the GAW system, with 28 stations and three soundings bi‐weekly, proves clearly superior to VINTERSOL/MATCH, showing a positive gain in skill of 0.26 compared to a free‐running model.
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