![]() Clim Dyn 17:213–218īourassa M, Hughes P, Smith S (2008) Surface turbulent flux product comparison. Bull Am Meteor Soc 90:645–656īoer GJ, Lambert S (2001) Second-order space–time climate difference statistics. doi: 10.1029/2004JD004536īerry DI, Kent EC (2009) A new air–sea interaction gridded dataset from ICOADS with uncertainty estimates. J Clim 8:3067–3083īengtsson L, Hagemann S, Hodges KI (2004) Can climate trends be calculated from reanalysis data? J Geophys Res 109:D11111. J Atmos Sci 55:477–493īattisti D, Bhatt U, Alexander M (1995) A modeling study of the interannual variability in the wintertime North Atlantic ocean. J Phys Oceanogr 25:122–137īarsugli JJ, Battisti DS (1998) The basic effects of atmosphere–ocean thermal coupling on midlatitude variability. Heat flux feedback dominates over the atmospheric forcing and heat flux damps SST anomalies on average at northern Pacific mid-latitudes and southern Atlantic mid-latitudes while the reverse occurs in the SPCZ and northern Atlantic mid-latitudes.ĪchutaRao KM, Sperber KR (2006) ENSO simulation in coupled ocean–atmosphere models: are the current models better? Clim Dyn 27:1–15Īlexander MA, Deser C (1995) A mechanism for the recurrence of wintertime midlatitude SST anomalies. The SST-heat flux covariance is decomposed into components associated with surface heat flux feedback and atmospheric forcing processes. Model resolution shows no relationship with the heat flux feedback parameters obtained from model results. The mean model feedback parameter has the best pattern correlation and the smallest mean square difference compared to the reanalysis-based values, although spatial variances are weak. The magnitudes of the annual and seasonal feedback parameters are slightly weaker in most models compared to the reanalysis-based estimates. The heat flux feedback strengthens in winter and fall and weakens in spring and summer. The latter are also areas with large inter-model differences. The strongest feedback is found at mid-latitudes in both hemispheres, with the largest values occurring in the western and central portions of the oceans with extensions to higher latitudes. ![]() Feedback is generally negative and is dominated by the turbulent component. The heat flux feedback parameter is determined from the lagged cross-covariances together with the auto-covariance of SST. Lagged covariances are broadly similar in the two reanalyses and among the models, implying that heat flux feedback is also similar. Common covariance features are seen in all climate models in the tropics and the subtropics, while covariances differ considerably among models at northern mid-latitudes, where weak values of the ensemble mean are seen. The upward heat fluxes are positively correlated with the SST anomalies in the tropics, the northern Pacific mid-latitudes, and over the Gulf Stream, and negatively correlated in the northern subtropics and the SPCZ region. The covariance patterns of SST and heat flux are broadly similar in the two reanalyses. The connection between the variability of heat flux (including its radiative and turbulent components) and that of SST is investigated using the NCEP-NCAR and ERA-40 reanalyses and the CMIP3 multi-model collection of climate simulations. The generation and dissipation of SST anomalies is mediated by the covariability of SST and surface heat fluxes.
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