A model-based examination of multivariate physical modes in the Gulf of Alaska
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A model-based examination of multivariate physical modes in the Gulf of Alaska
  • Published Date:

    2016

  • Source:
    Deep-Sea Research Part Ii-Topical Studies in Oceanography, 132, 68-89.
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A model-based examination of multivariate physical modes in the Gulf of Alaska
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  • Personal Author:
  • Description:
    We use multivariate output from a hydrodynamic model of the Gulf of Alaska (GOA) to explore the covariance among its physical state and air/sea fluxes. We attempt to summarize this coupled variability using a limited set of patterns, and examine their correlation to three large-scale climate indices relevant to the Northeast Pacific. This analysis is focused on perturbations from monthly climatology of the following attributes of the GOA: sea surface temperature, sea surface height, mixed layer depth, sea surface salinity, latent heat flux, sensible heat flux, shortwave irradiance, net long wave irradiance, currents at 40 m depth, and wind stress. We identified two multivariate modes, both substantially correlated with the Pacific Decadal Oscillation (PDO) and Multivariate El Nino (MEI) indices on interannual timescales, which together account for similar to 30% of the total normalized variance of the perturbation time series. These two modes indicate the following covarying events during periods of positive PDO/MEI: (1) anomalously warm, wet and windy conditions (typically in winter), with elevated coastal SSH, followed 2-5 months later by (2) reduced cloud cover, with emerging shelf-break eddies. Similar modes are found when the analysis is performed separately on the eastern and western GOA; in general, modal amplitudes appear stronger in the western GOA. (C) 2016 Elsevier Ltd All rights reserved.
  • DOI:
    https://doi.org/10.1016/j.dsr2.2016.04.005
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA10OAR4320148
  • Collection(s):
    NOAA Cooperative Institutes
    Office of Oceanic and Atmospheric Research (OAR)
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