The retrospective prediction of El Niño-southern oscillation from 1881 to 2000 by a hybrid coupled model: (I) Sea surface temperature assimilation with ensemble Kalman filter |
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| Authors: | Ziwang Deng Youmin Tang Xiaobing Zhou |
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| Institution: | 1. Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, Prince George, BC, V2N 4Z9, Canada
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| Abstract: | In this study, we assimilated sea surface temperature (SST) data of the past 120 years into an oceanic general circulation model (OGCM) for El Niño-southern oscillation (ENSO) retrospective predictions using ensemble Kalman filter (EnKF). It was found that the ensemble covariance matrix in EnKF can act as a time-variant transfer operator to project the SST corrections onto the subsurface temperatures effectively when initial perturbations of ensemble were constructed using vertically coherent random fields. As such the increments of subsurface temperatures can be obtained via the transfer operator during assimilation cycles. The results show that the SST assimilation improves the model simulation skills significantly, not only for the SST anomalies over the whole assimilated domain, but also for the subsurface temperature anomalies of the upper 100 m over the tropical Pacific off the equator. Along the equator, the improvement of the assimilation is confined within the mixing layer because strong upwelling motions there prevent the downward transfer of SST information. The retrospective prediction skills of ENSO over the past 120 years from 1881 to 2000 were significantly improved by the SST assimilation at all leads of 1–12 months, especially for the 3–6 months leads, compared with those initialized by the control run without assimilation. The skilful predictions by the assimilation allow us to further study ENSO predictability using this coupled model. |
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