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Climatic Change

, Volume 116, Issue 3–4, pp 789–803 | Cite as

Analysis of trends and sudden changes in long-term environmental data from King George Island (Antarctica): relationships between global climatic oscillations and local system response

  • A. Valeria Bers
  • Fernando Momo
  • Irene R. Schloss
  • Doris Abele
Article

Abstract

The Western Antarctic Peninsula is one of the most rapidly warming regions on earth. It is therefore important to analyze long-term trends and inter-annual patterns of change in major environmental parameters to understand the process underlying climate change in Western Antarctica. Since many polar long-term data series are fragmented and cannot be analysed with common time series analysis tools, we present statistical approaches that can deal with missing values. We applied U-statistics after Pettit and Buishand to detect abrupt changes, dynamic factor analysis to detect functional relationships, and additive modelling to detect patterns in time related to climatic cycles such as the Southern Annular Mode and El Niño Southern Oscillation in a long-term environmental data set from King George Island (WAP), covering 20 years. Our results not only reveal sudden changes for sea surface temperature and salinity, but also clear patterns in all investigated variables (sea surface temperature, salinity, suspended particulate matter and Chlorophyll a) that can directly be related to climatic cycles. Our results complement previous findings on climate related changes in the King George Island Region and provide insight into the environmental conditions and climatic drivers of system change in the study area. Hence, our statistical analyses may prove valuable for other polar environmental data sets and contribute to a better understanding of the regional variability of climate change and its impact on coastal systems.

Keywords

Generalize Additive Modeling Southern Annular Mode Suspended Particulate Matter Concentration Climatic Driver Western Antarctic Peninsula 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This study is part of the IMCOAST program, which is part of the PolarClimate program of the European Research Council within the ERA-Net Europolar. This particular subproject was funded by the German Federal Ministry of Education and Research (BMBF, ref. no. 03F0617A). We thank the Servicio Meteorológico Nacional of the Argentine Air Force for providing the air temperature data and IAA, DNA and AWI for supporting 20 years of cooperative field work at Carlini Station-Dallmann laboratory.

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • A. Valeria Bers
    • 1
  • Fernando Momo
    • 2
  • Irene R. Schloss
    • 3
    • 4
    • 5
  • Doris Abele
    • 1
  1. 1.Alfred Wegener Institute for Polar and Marine ResearchBremerhavenGermany
  2. 2.Institute of SciencesNational University of General SarmientoBuenos AiresArgentina
  3. 3.Instituto Antártico ArgentinoCiudad Autónoma de Buenos AiresArgentina
  4. 4.CONICETBuenos AiresArgentina
  5. 5.Institut des sciences de la mer de RimouskiQuébecCanada

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