Climate spectrum estimation in the presence of timescale errors.
We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistenc...
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2009
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ftunivreading:oai:centaur.reading.ac.uk:30495 2024-09-15T18:12:01+00:00 Climate spectrum estimation in the presence of timescale errors. Mudelsee, M Scholz, D Rothlisberger, R Fleitmann, Dominik Mangini, A Wolff, E.W. 2009 https://centaur.reading.ac.uk/30495/ unknown European Geosciences Union Mudelsee, M., Scholz, D., Rothlisberger, R., Fleitmann, D. <https://centaur.reading.ac.uk/view/creators/90004859.html>, Mangini, A. and Wolff, E.W. (2009) Climate spectrum estimation in the presence of timescale errors. Nonlinear Processes in Geophysics, 16 (1). pp. 43-56. ISSN 1607-7946 doi: https://doi.org/10.5194/npg-16-43-2009 <https://doi.org/10.5194/npg-16-43-2009> Article PeerReviewed 2009 ftunivreading https://doi.org/10.5194/npg-16-43-2009 2024-06-25T14:53:30Z We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation. Article in Journal/Newspaper ice core CentAUR: Central Archive at the University of Reading Nonlinear Processes in Geophysics 16 1 43 56 |
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Open Polar |
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CentAUR: Central Archive at the University of Reading |
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ftunivreading |
language |
unknown |
description |
We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation. |
format |
Article in Journal/Newspaper |
author |
Mudelsee, M Scholz, D Rothlisberger, R Fleitmann, Dominik Mangini, A Wolff, E.W. |
spellingShingle |
Mudelsee, M Scholz, D Rothlisberger, R Fleitmann, Dominik Mangini, A Wolff, E.W. Climate spectrum estimation in the presence of timescale errors. |
author_facet |
Mudelsee, M Scholz, D Rothlisberger, R Fleitmann, Dominik Mangini, A Wolff, E.W. |
author_sort |
Mudelsee, M |
title |
Climate spectrum estimation in the presence of timescale errors. |
title_short |
Climate spectrum estimation in the presence of timescale errors. |
title_full |
Climate spectrum estimation in the presence of timescale errors. |
title_fullStr |
Climate spectrum estimation in the presence of timescale errors. |
title_full_unstemmed |
Climate spectrum estimation in the presence of timescale errors. |
title_sort |
climate spectrum estimation in the presence of timescale errors. |
publisher |
European Geosciences Union |
publishDate |
2009 |
url |
https://centaur.reading.ac.uk/30495/ |
genre |
ice core |
genre_facet |
ice core |
op_relation |
Mudelsee, M., Scholz, D., Rothlisberger, R., Fleitmann, D. <https://centaur.reading.ac.uk/view/creators/90004859.html>, Mangini, A. and Wolff, E.W. (2009) Climate spectrum estimation in the presence of timescale errors. Nonlinear Processes in Geophysics, 16 (1). pp. 43-56. ISSN 1607-7946 doi: https://doi.org/10.5194/npg-16-43-2009 <https://doi.org/10.5194/npg-16-43-2009> |
op_doi |
https://doi.org/10.5194/npg-16-43-2009 |
container_title |
Nonlinear Processes in Geophysics |
container_volume |
16 |
container_issue |
1 |
container_start_page |
43 |
op_container_end_page |
56 |
_version_ |
1810449597105963008 |