Displaced Ensemble Variational Assimilation Method to Incorporate Microwave Imager Brightness Temperatures into a Cloud-resolving Model

Kazumasa AONASHI, Hisaki EITO
2011 Journal of the Meteorological Society of Japan  
We developed a data assimilation method that incorporates the microwave imager (MWI) brightness temperatures (TBs) into the cloud-resolving model (CRM) developed by the Japan Meteorological Agency (JMANHM). This method consisted of a displacement error correction scheme and an Ensemble-based variational assimilation scheme. In the displacement error correction scheme, we obtained the optimum displacement that maximized the conditional probability of TB observation given the displaced CRM
more » ... isplaced CRM variables. In the assimilation scheme, we derived a cost function in the displaced Ensemble forecast error subspace. Then, we obtained the analyses of CRM variables by non-linear minimization of the cost function. We applied this method to assimilate TMI (TRMM Microwave Imager) low-frequency TBs (10, 19, and 21 GHz with vertical polarization) for a Typhoon case around Okinawa (9 th June 2004). The results of the assimilation experiments showed that the assimilation of TMI TBs alleviated the large-scale displacement errors and improved the CRM forecasts.
doi:10.2151/jmsj.2011-301 fatcat:gpegeohl65bhpnvzklbmbfxqg4