Articles | Volume 9, issue 10
https://doi.org/10.5194/gmd-9-3517-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-3517-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
30 Sep 2016
Model description paper |
| 30 Sep 2016
Astronomical component estimation (ACE v.1) by time-variant sinusoidal modeling
Analytical, Environmental, & Geo-Chemistry, Vrije Universiteit
Brussel, 1050 Brussels, Belgium
Miroslav Zivanovic
Department of Electrical and Electronic Engineering, Universidad
Pública de Navarra, 31006 Pamplona, Spain
David De Vleeschouwer
Analytical, Environmental, & Geo-Chemistry, Vrije Universiteit
Brussel, 1050 Brussels, Belgium
MARUM, Center for Marine Environmental Science, Leobener Strasse,
28359 Bremen, Germany
Philippe Claeys
Analytical, Environmental, & Geo-Chemistry, Vrije Universiteit
Brussel, 1050 Brussels, Belgium
Johan Schoukens
Department of Fundamental Electricity and Instrumentation, Vrije
Universiteit Brussel, 1050 Brussels, Belgium
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Cited
9 citations as recorded by crossref.
- Tracking variable sedimentation rates and astronomical forcing in Phanerozoic paleoclimate proxy series with evolutionary correlation coefficients and hypothesis testing M. Li et al. 10.1016/j.epsl.2018.08.041
- High-resolution sedimentary cyclostratigraphy and astronomical signals in the Upper Ordovician of Southwest China K. Wang et al. 10.1016/j.palwor.2024.11.001
- An integrated pelagic carbonate multi-proxy study using portable X-ray fluorescence (pXRF): Maastrichtian strata from the Bottaccione Gorge, Gubbio, Italy M. Sinnesael et al. 10.1016/j.cretres.2018.04.010
- The Cyclostratigraphy Intercomparison Project (CIP): consistency, merits and pitfalls M. Sinnesael et al. 10.1016/j.earscirev.2019.102965
- Spectral Moments in Cyclostratigraphy: Advantages and Disadvantages Compared to More Classic Approaches M. Sinnesael et al. 10.1029/2017PA003293
- Orbital Signals in Carbon Isotopes: Phase Distortion as a Signature of the Carbon Cycle J. Laurin et al. 10.1002/2017PA003143
- Precession-driven climate cycles and time scale prior to the Hirnantian glacial maximum M. Sinnesael et al. 10.1130/G49083.1
- Ordovician cyclostratigraphy and astrochronology M. Sinnesael 10.1144/SP532-2022-31
- A decomposition approach to cyclostratigraphic signal processing S. Wouters et al. 10.1016/j.earscirev.2021.103894
9 citations as recorded by crossref.
- Tracking variable sedimentation rates and astronomical forcing in Phanerozoic paleoclimate proxy series with evolutionary correlation coefficients and hypothesis testing M. Li et al. 10.1016/j.epsl.2018.08.041
- High-resolution sedimentary cyclostratigraphy and astronomical signals in the Upper Ordovician of Southwest China K. Wang et al. 10.1016/j.palwor.2024.11.001
- An integrated pelagic carbonate multi-proxy study using portable X-ray fluorescence (pXRF): Maastrichtian strata from the Bottaccione Gorge, Gubbio, Italy M. Sinnesael et al. 10.1016/j.cretres.2018.04.010
- The Cyclostratigraphy Intercomparison Project (CIP): consistency, merits and pitfalls M. Sinnesael et al. 10.1016/j.earscirev.2019.102965
- Spectral Moments in Cyclostratigraphy: Advantages and Disadvantages Compared to More Classic Approaches M. Sinnesael et al. 10.1029/2017PA003293
- Orbital Signals in Carbon Isotopes: Phase Distortion as a Signature of the Carbon Cycle J. Laurin et al. 10.1002/2017PA003143
- Precession-driven climate cycles and time scale prior to the Hirnantian glacial maximum M. Sinnesael et al. 10.1130/G49083.1
- Ordovician cyclostratigraphy and astrochronology M. Sinnesael 10.1144/SP532-2022-31
- A decomposition approach to cyclostratigraphic signal processing S. Wouters et al. 10.1016/j.earscirev.2021.103894
Latest update: 31 Jan 2025
Short summary
Classical spectral analysis often relies on methods based on (Fast) Fourier Transformation. This technique has no unique solution separating variations in amplitude and frequency. This drawback is circumvented by using a polynomial approach (ACE v.1 model) to estimate instantaneous amplitude and frequency in orbital components. The model is illustrated and validated using a synthetic insolation signal and tested on two case studies: a benthic δ18O record and a magnetic susceptibility record.
Classical spectral analysis often relies on methods based on (Fast) Fourier Transformation. This...
