Climate Dynamics

, Volume 48, Issue 9–10, pp 3139–3160 | Cite as

Understanding the control of extratropical atmospheric variability on ENSO using a coupled data assimilation approach



The control of extratropical atmospheric variability on ENSO variability is studied in a coupled general circulation model (CGCM) utilizing an ensemble-based coupled data assimilation (CDA) method in the perfect-model framework. Assimilation is limited to the desired model components (e.g. atmosphere) and spatial areas (e.g. the extratropics) to study the ensemble-mean model response (e.g. tropical response to “observed” extratropical atmospheric variability). The CDA provides continuously “corrected” extratropical atmospheric forcing and boundary conditions for the tropics and the use of ensemble optimizes the observational forcing signal over internal variability in the model component or region without assimilation. The experiments demonstrate significant control of extratropical atmospheric forcing on ENSO variability in the CGCM. When atmospheric “observations” are assimilated only poleward of 20° in both hemispheres, most ENSO events in the “observation” are reproduced and the error of the Nino3.4 index is reduced by over 40 % compared to the ensemble control experiment that does not assimilate any observations. Further experiments with the assimilation in each hemisphere show that the forced ENSO variability is contributed roughly equally and independently by the Southern and Northern Hemisphere extratropical atmosphere. Further analyses of the ENSO events in the southern hemisphere forcing experiment reveal robust precursors in both the extratropical atmosphere over southeastern Pacific and equatorial Pacific thermocline, consistent with previous studies of the South Pacific Meridional Mode and the discharge-recharge paradigm, respectively. However, composite analyses based on each precursor show that neither precursor alone is sufficient to trigger ENSO onset by itself and therefore neither alone could serve as a reliable predictor. Additional experiments with northern hemisphere forcing, ocean assimilation or different latitudes are also performed.


ENSO Variability Precursors Coupled model dynamics Coupled data assimilation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Atmospheric and Oceanic Sciences, Nelson Institute Center for Climatic ResearchUniversity of Wisconsin-MadisonMadisonUSA
  2. 2.Laboratory for Climate, Ocean and Atmosphere StudiesPeking UniversityBeijingChina
  3. 3.Department of Atmospheric and Oceanic Science and Earth System Science Interdisciplinary CenterUniversity of Maryland, College ParkCollege ParkUSA
  4. 4.Geophysical Fluid Dynamics Laboratory, NOAAPrincetonUSA
  5. 5.Mathematics and Computer Science DivisionArgonne National LaboratoryArgonneUSA

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