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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Published in:Nonlinear Processes in Geophysics
Main Authors: Mudelsee, M, Scholz, D, Rothlisberger, R, Fleitmann, Dominik, Mangini, A, Wolff, E.W.
Format: Article in Journal/Newspaper
Language:unknown
Published: European Geosciences Union 2009
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Online Access:https://centaur.reading.ac.uk/30495/
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spelling 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
institution Open Polar
collection CentAUR: Central Archive at the University of Reading
op_collection_id 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
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