An Improved Coupled Model for ENSO Prediction and Implications for Ocean Initialization. Part I: The Ocean Data Assimilation System

David W. Behringer National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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Ming Ji National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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Ants Leetmaa National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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Abstract

An improved forecast system has been developed for El Niño–Southern Oscillation (ENSO) prediction at the National Centers for Environmental Prediction. Improvements have been made both to the ocean data assimilation system and to the coupled ocean–atmosphere forecast model. In Part I of a two-part paper the authors describe the new assimilation system. The important changes are 1) the incorporation of vertical variation in the first-guess error variance that concentrates temperature corrections in the thermocline and 2) the overall reduction in the magnitude of the estimated first-guess error. The new system was used to produce a set of retrospective ocean analyses for 1980–95. The new analyses are less noisy than their earlier counterparts and compare more favorably with independent measurements of temperature, currents, and sea surface height variability. Part II of this work presents the results of using these analyses to initialize the coupled forecast model for ENSO prediction.

Corresponding author address: Dr. Ming Ji, Climate Modeling Branch, National Centers for Environmental Prediction, 5200 Auth Road, Rm. 807, Camp Springs, MD 20746.

Abstract

An improved forecast system has been developed for El Niño–Southern Oscillation (ENSO) prediction at the National Centers for Environmental Prediction. Improvements have been made both to the ocean data assimilation system and to the coupled ocean–atmosphere forecast model. In Part I of a two-part paper the authors describe the new assimilation system. The important changes are 1) the incorporation of vertical variation in the first-guess error variance that concentrates temperature corrections in the thermocline and 2) the overall reduction in the magnitude of the estimated first-guess error. The new system was used to produce a set of retrospective ocean analyses for 1980–95. The new analyses are less noisy than their earlier counterparts and compare more favorably with independent measurements of temperature, currents, and sea surface height variability. Part II of this work presents the results of using these analyses to initialize the coupled forecast model for ENSO prediction.

Corresponding author address: Dr. Ming Ji, Climate Modeling Branch, National Centers for Environmental Prediction, 5200 Auth Road, Rm. 807, Camp Springs, MD 20746.

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