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Uncertainty in the ocean–atmosphere feedbacks associated with ENSO in the reanalysis products

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Abstract

The evolution of El Niño-Southern Oscillation (ENSO) variability can be characterized by various ocean–atmosphere feedbacks, for example, the influence of ENSO related sea surface temperature (SST) variability on the low-level wind and surface heat fluxes in the equatorial tropical Pacific, which in turn affects the evolution of the SST. An analysis of these feedbacks requires physically consistent observational data sets. Availability of various reanalysis data sets produced during the last 15 years provides such an opportunity. A consolidated estimate of ocean surface fluxes based on multiple reanalyses also helps understand biases in ENSO predictions and simulations from climate models. In this paper, the intensity and the spatial structure of ocean–atmosphere feedback terms (precipitation, surface wind stress, and ocean surface heat flux) associated with ENSO are evaluated for six different reanalysis products. The analysis provides an estimate for the feedback terms that could be used for model validation studies. The analysis includes the robustness of the estimate across different reanalyses. Results show that one of the “coupled” reanalysis among the six investigated is closer to the ensemble mean of the results, suggesting that the coupled data assimilation may have the potential to better capture the overall atmosphere–ocean feedback processes associated with ENSO than the uncoupled ones.

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Acknowledgments

We appreciate the comments of Drs. Wanqiu Wang, Yan Xue, D. G. DeWitt, and two reviewers. Thanks also go to Dr. Li Zhang for managing the reanalysis data sets at CPC.

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Authors and Affiliations

  1. Climate Prediction Center, NCEP/NWS/NOAA, 5200 Auth Road (Suite 605), Camp Springs, MD, 20746, USA

    Arun Kumar & Zeng-Zhen Hu

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  1. Arun Kumar
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  2. Zeng-Zhen Hu
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Correspondence to Arun Kumar.

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Kumar, A., Hu, ZZ. Uncertainty in the ocean–atmosphere feedbacks associated with ENSO in the reanalysis products. Clim Dyn 39, 575–588 (2012). https://doi.org/10.1007/s00382-011-1104-3

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  • DOI: https://doi.org/10.1007/s00382-011-1104-3

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