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Highlights
- Acycle is signal processing software for paleoclimate research and education
- Many of the functions are specific to cyclostratigraphy and astrochronology
- Acycle includes models for sedimentary noise and sedimentation rate
- A fully implemented graphical user interface facilitates operator use
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Dr. James Ogg (Professor, DEPT. EARTH ,ATMOS. & PLANET. SCI., Purdue University, USA):
"Mingsong Li's Acycle software enables us to quickly analyze the potential of new outcrops and boreholes, and then to determine the sedimentation rates and elapsed time. His Acycle software will become the standard tool for time-scale applications by all international workers."
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Dr. Paul E. Olsen (Professor of Earth and Environmental Sciences, Columbia University; Member, National Academy of Sciences of the USA):
Not only is this software powerful and effective, it is also simple to use and therefore benefits researchers and at all levels within the paleoclimatology community, from novices to experts.
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Dr. Arsenio Muñoz de la Peña (Professor, Department of Analytical Chemistry, University of Zaragoza, Spain):
"Thank you very much and congratulations for the acycle software. I am using it and it is very very useful and interesting."
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Dr. Marco Franceschi (Professor, Department of Geosciences, University of Padova, Italy):
Dr. Li’s software is being immensely valuable to my work. Some of the stratigraphic series I am studying display a prominent cyclicity, but were deposited in contexts characterized by relevant changes in sedimentation rates and often lack accurate geochronological constraints. Acycle has been designed specifically for dealing with similar cases, by tackling them with a rigorous statistical approach, and therefore is providing an invaluable tool for their investigation.
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Dr. Xu Yao (School of Earth Sciences, Lanzhou University, China):
I am working on cyclostratigraphy and paleoclimate study of ancient strata and rocks (270 million years ago) with assistance from Acycle software. I also introduced this software to my colleagues whose research areas are paleoclimate implications of Quaternary loess (several thousand years ago). My colleagues have given me really good feedbacks about Acycle software.
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Dr. Christian Zeeden (IMCCE, Observatoire de Paris, France):
Dr. Li’s software is novel and valuable in this context, especially because it facilitates the easy application of otherwise complex calculations.
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A professor from the University of Copenhagen in Denmark:
I’ve been playing a lot with the excellent Acycle package for Matlab that Mingsong developed. Congratulations, this is a very nice interface that simplifies a lot our work and makes it truly faster to analyse a time-series.
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Li, M., Hinnov, L.A., Huang, C., Ogg, J.G., 2018. Sedimentary noise and sea levels linked to land–ocean water exchange and obliquity forcing. Nature communications 9, 1004. https://doi.org/10.1038/s41467-018-03454-y
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Li, M., Kump, L.R., Hinnov, L.A., Mann, M.E., 2018. Tracking variable sedimentation rates and astronomical forcing in Phanerozoic paleoclimate proxy series with evolutionary correlation coefficients and hypothesis testing. Earth and Planetary Science Letters 501, 165-179. https://doi.org/10.1016/j.epsl.2018.08.041
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Chen, G., Gang, W., Liu, Y., Wang, N., Guo, Y., Zhu, C., Cao, Q., 2019. High-resolution sediment accumulation rate determined by cyclostratigraphy and its impact on the organic matter abundance of the hydrocarbon source rock in the Yanchang Formation, Ordos Basin, China. Marine and Petroleum Geology 103, 1-11. https://doi.org/10.1016/j.marpetgeo.2019.01.044
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Li, M., Huang, C., Ogg, J., Zhang, Y., Hinnov, L., Wu, H., Chen, Z.-Q., Zou, Z., 2019. Paleoclimate proxies for cyclostratigraphy: Comparative analysis using a Lower Triassic marine section in South China. Earth-Science Reviews. https://doi.org/10.1016/j.earscirev.2019.01.011
Flowchart of cyclostratigraphy
The identification of potential astronomical signals in paleoclimate data series using Acycle involves the following steps:
- Users must formulate the data in an input format accepted by Acycle.
- Original data may need sorting, removing empty values, or averaging multiple values assigned to the same depth (time).
- The data must be interpolated to a uniform sampling interval.
- Detrending is usually useful.
- Power spectral analysis is used to identify dominant frequencies. Fitting a red noise model to the background spectrum can help to determine which spectral peaks are significantly different from noise.
- Users may need evolutionary power spectral analysis for inspecting changes in frequency patterns through the data series.
- A method that applies a correlation coefficient approach jointly determines optimal sedimentation rate and tests the null hypothesis that no Milankovitch frequency is present in the data.
- Based on the wavelengths (stratigraphic thicknesses) of prominent cycles in a stratigraphic data series, and an assumed sedimentation rate, filtering tools may be applied to isolate specific frequency bands.
- Stratigraphic data series may be correlated/tuned using the “Age Scale” function in Acycle based on the astronomical cycles inferred from filtering.
- Other approaches are provided to decipher hidden information in the data, for example, a sedimentary noise model for stratigraphic data from marginal marine successions that are linked to sea level changes.
Steps 3-10 are commonly time-consuming, and Steps 2-6 can be done automatically with a “mini-robot” imbedded in Acycle.
Mingsong Li, Linda A. Hinnov, Lee R. Kump, 2019. Acycle: Time-series analysis software for paleoclimate research and education. Computers & Geosciences. 127: 12-22. https://doi.org/10.1016/j.cageo.2019.02.011.