Non-Gaussian ensemble-mean update in the ensemble Kalman filter: experiments with an intermediate AGCM
In our previous work, impacts of removing covariance localization are investigated by increasing the ensemble size up to 10240 with an intermediate atmospheric general circulation model (AGCM) known as the SPEEDY (T30/L7) model and an ensemble Kalman filter (EnKF). Although the analysis accuracy without localization was greatly improved, the improvement in the tropical regions was relatively small. In fact, we found that the non-Gaussian PDF such as bimodality frequently appeared in the tropical regions, and that the spatial patterns of the occurrences of the non-Gaussian PDF corresponded well to that of the analysis error. To improve the analysis accuracy in the regions with frequent non-Gaussian PDF, we apply a particle filtering approach for the ensemble-mean update in the EnKF. This presentation will include the most recent results up to the time of the symposium.
Dr. Keiichi Kondo Meteorological Research Institute