The impact of ensemble filter definition on the assimilation of temperature profiles in the tropical Pacific
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The traditional analysis scheme in the Ensemble Kalman Filter (EnKF) uses a stochastic perturbation or randomization of the measurements which ensures a correct variance in the updated ensemble. An alternative so called deterministic analysis algorithm is based on a square-root formulation where the perturbation of measurements is avoided. Experiments with simple models have indicated that ensemble collapse is likely to occur when deterministic filters are applied to nonlinear problems. In this paper the properties of stochastic and deterministic ensemble analysis algorithms are evaluated in an identical-twin experiment using an ocean general circulation model. In particular, the implications of the use of deterministic ensemble square-root filters (EnSRF) for ensemble distribution are investigated. An explanation is presented for the observed collapse, and a simple solution based on randomization of the analysis ensemble anomalies is examined. A 1-year assimilation run with this improved EnSRF is found to produce Gaussian distributions, similar to the Ensemble Kalman Filter.