时间关联误差对土壤湿度估算的影响

o evaluate the impacts of 2-type time correlated error models on the estimates of soil moisture profiles by assimilating the near-surface soil moisture measurements into NOAH land surface model (LSM),a series of observation system simulation experiments were carried out by using a combination technique of the ensemble square root filter (EnSRF) and state augmentation, in which both the model states and model errors were updated at the same time. It was shown that EnSRF could not successfully estimate the soil moisture profiles if a large model bias was directly ignored in the process of data assimilation and on the contrary, the soil moisture estimates had a large improvement if the model errors were corrected. Further sensitive tests showed that the values of parameters in the error model, the magnitudes of observational errors and the time intervals for updating data would influence the estimates, Affected by the used method, the error model required to be known beforehand in practical application.