Experimental Implementation of an Ensemble Adjustment Filter for an Intermediate ENSO Model

Abstract The assimilation of sea surface temperature (SST) anomalies into a coupled ocean–atmosphere model of the tropical Pacific is investigated using an ensemble adjustment Kalman filter (EAKF). The intermediate coupled model used here is the operational version of the Zebiak–Cane model, called LDEO5. The assimilation is applied as a means of estimating the true state of the system in the presence of incomplete observations of the state. In the first part of this study assimilation is performed under the “perfect model” assumption, where SST observations are synthetically derived from a trajectory of the model. The focus is on how and why changes in the filter parameters (ensemble size, covariance localization, and covariance inflation) affect the quality of the analysis. It is shown that isotropic covariance localization does not benefit the analysis even when a small number of ensemble members are used. These results suggest that destruction of the “balance” between variables caused by localization i...

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