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Test results for trend extraction algorithms (Table S1)

Also known as: Global trends in wind speed and wave height, table S1
Swinburne University of Technology
Alexander V. Babanin (Owned by) Stefan Zieger (Owned by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://hdl.handle.net/1959.3/194837&rft.title=Test results for trend extraction algorithms (Table S1)&rft.identifier=http://hdl.handle.net/1959.3/194837&rft.publisher=Swinburne University of Technology&rft.description=Studies of climate change typically consider measurements or predictions of temperature over extended periods of time. Climate, however, is much more than temperature. Over the oceans, changes in wind speed and the surface gravity waves generated by such winds play an important role. We used a 23-year database of calibrated and validated satellite altimeter measurements to investigate global changes in oceanic wind speed and wave height over this period. This table contains test results for several different trend extraction algorithms: linear regression; linear plus seasonal; Mann-Kendall test; Seasonal Kendall test and Singular Spectrum Analysis. The target value for the trend in this test is 0.5 x 10^2 units/yr. Singular Spectrum Analysis (SSA) was used to 'filter' the time series. The trend of the filtered time series was then determined using the MK test. The confidence limits are for this filtered time series.This work draws on a 23-year database of calibrated and validated satellite altimeter measurements to investigate global changes in oceanic wind speed and wave height over this period. This is important work towards increasing global knowledge about climate change, as well as working towards one of the national priorities for research.&rft.creator=Alexander V. Babanin&rft.creator=Stefan Zieger&rft.date=2011&rft.relation=http://dx.doi.org/10.1126/science.1197219&rft.relation=http://www.sciencemag.org/content/332/6028/451/suppl/DC1&rft_subject=OCEANOGRAPHY&rft_subject=EARTH SCIENCES&rft_subject=Singular Spectrum Analysis&rft_subject=CLIMATE AND CLIMATE CHANGE&rft_subject=ENVIRONMENT&rft_subject=Global trends&rft_subject=Oceanic wind speed&rft_subject=Climate change&rft_subject=Surface gravity waves&rft_subject=Wave height&rft.type=dataset&rft.language=English Access the data
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Copyright © 2011 The authors.

This dataset will be available for download 6 months after publication of the results (October 2011) in accordance with this policy. For more information, please consult the journal's website or contact the authors.

Full description

Studies of climate change typically consider measurements or predictions of temperature over extended periods of time. Climate, however, is much more than temperature. Over the oceans, changes in wind speed and the surface gravity waves generated by such winds play an important role. We used a 23-year database of calibrated and validated satellite altimeter measurements to investigate global changes in oceanic wind speed and wave height over this period. This table contains test results for several different trend extraction algorithms: linear regression; linear plus seasonal; Mann-Kendall test; Seasonal Kendall test and Singular Spectrum Analysis. The target value for the trend in this test is 0.5 x 10^2 units/yr. Singular Spectrum Analysis (SSA) was used to 'filter' the time series. The trend of the filtered time series was then determined using the MK test. The confidence limits are for this filtered time series.

Significance statement

This work draws on a 23-year database of calibrated and validated satellite altimeter measurements to investigate global changes in oceanic wind speed and wave height over this period. This is important work towards increasing global knowledge about climate change, as well as working towards one of the national priorities for research.

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Climate and Climate Change | Climate change | Earth Sciences | Environment | Global trends | Oceanography | Oceanic wind speed | Singular Spectrum Analysis | Surface gravity waves | Wave height |

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