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  • 1
    Publication Date: 2018-10-12
    Description: Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 31 (2018): 2771-2796, doi:10.1175/JCLI-D-17-0061.1.
    Description: The Generalized Equilibrium Feedback Analysis (GEFA) is used to distinguish the influence of the Oyashio Extension (OE) and the Kuroshio Extension (KE) variability on the atmosphere from 1979 to 2014 from that of the main SST variability modes, using seasonal mean anomalies. Remote SST anomalies are associated with each single oceanic regressor, but the multivariate approach efficiently confines their SST footprints. In autumn [October–December (OND)], the OE meridional shifts are followed by a North Pacific Oscillation (NPO)-like signal. The OE influence is not investigated in winter [December–February (DJF)] because of multicollinearity, but a robust response with a strong signal over the Bering Sea is found in late winter/early spring [February–April (FMA)], a northeastward strengthening of the Aleutian low following a northward OE shift. A robust response to the KE variability is found in autumn, but not in winter and late winter when the KE SST footprint becomes increasingly small and noisy as regressors are added in GEFA. In autumn, a positive PDO is followed by a northward strengthening of the Aleutian low and a southward shift of the storm track in the central Pacific, reflecting the surface heat flux footprint in the central Pacific. In winter, the PDO shifts the maximum baroclinicity and storm track southward, the response strongly tilts westward with height in the North Pacific, and there is a negative NAO-like teleconnection. In late winter, the North Pacific NPO-like response to the PDO interferes negatively with the response to the OE and is only detected when the OE is represented in GEFA. A different PDO influence on the atmospheric circulation is found from 1958 to 1977.
    Description: This research has received funding from the European Union 7th Framework Program (FP7 2007-2013) under Grant Agreement 308299 (NACLIM) and from NSF Grants AGS CLD 1035423 and OCE PO 1242989.
    Keywords: Atmosphere-ocean interaction ; Boundary currents ; Pacific decadal oscillation ; Atmosphere-ocean interaction ; Empirical orthogonal functions ; Regression analysis
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2018-05-16
    Description: Author Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 30 (2017): 9871-9895, doi:10.1175/JCLI-D-17-0009.1.
    Description: Two large ensembles (LEs) of historical climate simulations are used to compare how various statistical methods estimate the sea surface temperature (SST) changes due to anthropogenic and other external forcing, and how their removal affects the internally generated Atlantic multidecadal oscillation (AMO), Pacific decadal oscillation (PDO), and the SST footprint of the Atlantic meridional overturning circulation (AMOC). Removing the forced SST signal by subtracting the global mean SST (GM) or a linear regression on it (REGR) leads to large errors in the Pacific. Multidimensional ensemble empirical mode decomposition (MEEMD) and quadratic detrending only efficiently remove the forced SST signal in one LE, and cannot separate the short-term response to volcanic eruptions from natural SST variations. Removing a linear trend works poorly. Two methods based on linear inverse modeling (LIM), one where the leading LIM mode represents the forced signal and another using an optimal perturbation filter (LIMopt), perform consistently well. However, the first two LIM modes are sometimes needed to represent the forced signal, so the more robust LIMopt is recommended. In both LEs, the natural AMO variability seems largely driven by the AMOC in the subpolar North Atlantic, but not in the subtropics and tropics, and the scatter in the AMOC–AMO correlation is large between individual ensemble members. In three observational SST reconstructions for 1900–2015, linear and quadratic detrending, MEEMD, and GM yield somewhat different AMO behavior, and REGR yields smaller PDO amplitudes. Based on LIMopt, only about 30% of the AMO variability is internally generated, as opposed to more than 90% for the PDO. The natural SST variability contribution to global warming hiatus is discussed.
    Description: Support from the NOAA Climate Program Office Climate Variability and Predictability program (NA13OAR4310139), NSF EaSM2 (OCE-84298900), the European Community Horizon 2020 Framework under Grant Agreement 727852 (Blue-Action), and the ANR MORDICUS project (ANR-13-SENV-0002-02) is gratefully acknowledged.
    Description: 2018-05-16
    Keywords: Pattern detection ; Decadal variability ; Multidecadal variability ; Pacific decadal oscillation ; Trends
    Repository Name: Woods Hole Open Access Server
    Type: Article
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