A Weighted Average Soil Moisture Assimilation Experiment Based on Ensemble Kalman Filter

The arithmetic average of the ensemble members is usually taken as the final assimilation result of Ensemble Kalman Filter(EnKF).In this study,the weighted average of the forecasting ensembles was used as the assimilated result of EnKF.The dispersion of the ensemble members was considered as the weighting factor.After the EnKF has analyzed and updated each ensemble member,the weighted average of the ensemble members was adopted as the final forecasting results.Since the relationship between the dispersion of ensemble members and the forecast errors was significant,taking the dispersion of the ensemble members as the weighting factor was reasonable.This approach was examined based on a soil moisture assimilation experiment,which assimilated the in situ measurements of the surface soil moisture with a distributed hydrologic soil vegetation model(DHSVM) using EnKF.The results of the weighted average were compared with the results of arithmetic average based on EnKF.This study indicates that the assimilation can be improved significantly using the weighted average of ensemble members.