Detection of Changepoints in Ocean Time Series
The aim of this thesis is to analyze climate time series for abrupt changes. The time series are based on data provided by simulations of the Earth System Model GFDL ESM2M and consist of a historical period and a Representative Concentration Pathway (RCP8.5) period, where high emissions of greenhous...
| Main Authors: | , , |
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| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Zenodo
2020
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5281/zenodo.4564623 https://zenodo.org/record/4564623 |
| Summary: | The aim of this thesis is to analyze climate time series for abrupt changes. The time series are based on data provided by simulations of the Earth System Model GFDL ESM2M and consist of a historical period and a Representative Concentration Pathway (RCP8.5) period, where high emissions of greenhouse gases are assumed. The annual means of the four ocean variables sea surface temperature, sea ice concentration, net primary production of phytoplankton, and surface partial CO2 pressure are analyzed for abrupt changes. The analysis is based on the R package EnvCpt, which is designed to detect structural changes in climate and environment time series. Using post-processing R scripts, the EnvCpt output is filtered and presented in three different spatial plots. Several regions showing abrupt changes either caused by long-term shifts throughout the historical period or caused by changes due to the RCP8.5 period could be identified. The results are compared to the ones obtained by Drijfhout et al. (2015), who also analyzed climate time series for abrupt changes. With toy data, some limitations of EnvCpt are recognized and some recommendations for the use of EnvCpt are given. |
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