June 30, 2020 Other Open Access

Severin Kaderli; Thomas L. Frölicher; Friedrich Burger

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        <foaf:name>Severin Kaderli</foaf:name>
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        <foaf:name>Thomas L. Frölicher</foaf:name>
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        <foaf:name>Friedrich Burger</foaf:name>
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    <dct:title>Detection of Changepoints in Ocean Time Series</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2020-06-30</dct:issued>
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    <dct:description>&lt;p&gt;The aim of this thesis is to analyze climate time series for abrupt changes.&lt;br&gt; The time series are based on data provided by simulations of the Earth&lt;br&gt; System Model GFDL ESM2M and consist of a historical period and&lt;br&gt; a Representative Concentration Pathway (RCP8.5) period, where high&lt;br&gt; emissions of greenhouse gases are assumed. The annual means of the&lt;br&gt; four ocean variables sea surface temperature, sea ice concentration, net&lt;br&gt; primary production of phytoplankton, and surface partial CO2 pressure&lt;br&gt; are analyzed for abrupt changes. The analysis is based on the R package&lt;br&gt; EnvCpt, which is designed to detect structural changes in climate and&lt;br&gt; environment time series. Using post-processing R scripts, the EnvCpt&lt;br&gt; output is filtered and presented in three different spatial plots. Several regions&lt;br&gt; showing abrupt changes either caused by long-term shifts throughout&lt;br&gt; the historical period or caused by changes due to the RCP8.5 period&lt;br&gt; could be identified. The results are compared to the ones obtained by&lt;br&gt; Drijfhout et al. (2015), who also analyzed climate time series for abrupt&lt;br&gt; changes. With toy data, some limitations of EnvCpt are recognized and&lt;br&gt; some recommendations for the use of EnvCpt are given.&lt;/p&gt;</dct:description>
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