资源环境科技发展态势分析平台

In this study, IASI ozone-sensitive channels have been assimilated in 1D-Var data assimilation combined with realistic ozone background coming from a MOCAGE (Modele de Chimie Atmospherique a Grande Echelle) Chemistry Transport Model (CTM) as a first stage of coupling between Numerical Weather Prediction (NWP) and MOCAGE CTM at Meteo-France for global model ARPEGE (Action de Recherche Petite Echelle Grande Echelle). To evaluate the impact of ozone-sensitive channels on analyses, databases of 161 temperatures, humidity, and ozone radiosondes across the globe during a 1-year period have been considered. Ozone forecast from MOCAGE CTM was evaluated with radiosondes and used as input for the Radiative Transfer Model (RTM) RTTOV. Statistics of IASI observations minus simulations show that the use of ozone from MOCAGE CTM allows to better simulate IASI ozone-sensitive channels. The Desroziers method is used to diagnose observation error covariance matrix and estimate realistic ozone observation standard errors taking into account cross-correlations between IASI channels. The background error covariance matrix for ozone is estimated using radiosondes. A control run assimilating 123 IASI operational channels is compared to an experiment which assimilates, in addition, 15 IASI ozone-sensitive channels. Results show potential benefits of IASI ozone-sensitive channels combined with realistic ozone from MOCAGE CTM to improve temperature, humidity and ozone analyses simultaneously. This work is an encouraging first step for the enhancing of the coupling between the global model ARPEGE and MOCAGE CTM.