Improving the prediction of heavy rainfall with rapid-update dual-resolution hybrid En3DVar assimilation of all-sky AHI infrared water vapor radiances

Abstract

The Advanced Himawari Imager (AHI) on board Himawari-8 provides continuous high-resolution observations of severe weather phenomena in space and time, providing a good data source for the rapidly updated cycling data assimilation in numerical weather prediction (NWP). In this study, the all-sky AHI water vapor infrared radiances were rapidly assimilated using a dual-resolution hybrid EnVar method to introduce the flow-dependent ensemble information with a reduced ensemble cost in a case study. Considering the greatly increased computational costs for all-sky radiance data assimilation, the sensitivity of the all-sky radiance data assimilation to the resolution of ensemble error covariance as well as the cycling frequency using dual-resolution EnVar was investigated. The impact of all-sky radiance data assimilation using the dual-resolution hybrid EnVar was then compared to the clear-sky radiance data assimilation.From the case study, it was found that the dual-resolution hybrid EnVar and the full-resolution hybrid EnVar generally performed comparable for the all-sky assimilation of the AHI water vapor radiances in this study. Both show great advantages over 3DVar in analyses and forecasts with different leading time for model state variables. However, the former cost much fewer computational resources with only a tiny loss of the accuracy. For the assimilation frequency of all-sky radiances using the dual-resolution hybrid EnVar, it was found that the half-hourly and hourly test both obtain the better results than the other two (namely the 10-minutely test and 3-hourly test). The former two have the comparable performances in rainfall forecast although the half-hourly test is better. Finally, in the dual-resolution hybrid EnVar framework, the all-sky AHI radiance assimilation impact was studied versus the clear-sky radiances as well as the conventional observations in a case study. The results present a generally positive improvement of the rainfall forecast with the larger rainfall thresholds, caused by the assimilation of the cloud-influenced AHI water vapor radiances.