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Long-Term Trends, Variability and Extremes of In Situ Sea Surface Temperature Measured Along the Eastern Adriatic Coast and its Relationship to Hemispheric Processes

  • Branka Grbec
  • Frano Matić
  • Gordana Beg Paklar
  • Mira Morović
  • Ružica Popović
  • Ivica Vilibić
Article
  • 70 Downloads

Abstract

This paper examines long-term series of in situ sea surface temperature (SST) data measured at nine coastal and one open sea stations along the eastern Adriatic Sea for the period 1959–2015. Monthly and yearly averages were used to document SST trends and variability, while clustering and connections to hemispheric indices were achieved by applying the Principal Component Analysis (PCA) and Self-Organizing Maps (SOM) method. Both PCA and SOM revealed the dominance of temporal changes with respect to the effects of spatial differences in SST anomalies, indicating the prevalence of hemispheric processes over local dynamics, such as bora wind spatial inhomogeneity. SST extremes were connected with blocking atmospheric patterns. A substantial warming between 1979 and 2015, in total exceeding 1 °C, was preceded by a period with a negative SST trend, implying strong multidecadal variability in the Adriatic. The strongest connection was found between yearly SST and the East Atlantic (EA) pattern, while North Atlantic Oscillation (NAO) and East Atlantic/West Russia (EAWR) patterns were found to also affect February SST values. Quantification of the Adriatic SST and their connection to hemispheric indices allow for more precise projections of future SST, considered to be rather important for Adriatic thermohaline circulation, biogeochemistry and fisheries, and sensitive to ongoing climate change.

Keywords

Sea surface temperature teleconnection indices self-organizing maps PCA trend long-time series 

Notes

Acknowledgements

This work has been supported in part by Croatian Science Foundation under the Projects IP-2014-09-3606 (MARIPLAN), IP-2014-06-1955 (ADIOS) and by ViLab group (http://www.izor.hr/web/guest/virtual-laboratory). The SOM Toolbox version 2.0 for Matlab was developed by E. Alhoniemi, J. Himberg, J. Parhankangas, and J. Vesanto at the Helsinki University of Technology, Finland, and is available at http://www.cis.hut.fi/projects/somtoolbox.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Physical Oceanography LaboratoryInstitute of Oceanography and FisheriesSplitCroatia
  2. 2.Meteorological and Hydrological ServiceMarine Meteorological CenterSplitCroatia

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