Acycle v1.2: time-series analysis software for paleoclimate research and education
Wiki updated on May 20, 2019
- 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
What they say
Dr. J. Fred Read (Emeritus Professor of Sedimentary Geology, Dept of Geosciences, Virginia Tech)
I am writing to express my appreciation for all the hard work and thought that has gone into the development of the Acycle software program. It is truly an amazing contribution to the geosciences community. As someone who has spent much of the last 50 years trying to understand cyclic carbonates on shallow platforms, and having been involved with my students in some of the early work on stratigraphic modelling of the effects of Milankovitch forcing of carbonate platform stratigraphy, I was blown away by the power of the Acycle software.
In the old days we used in house programs from our geophysicist Cahit Coruh, and recently I have used Analyseries, kSpectra and Timefrq43, moving from Dos to Windows to Mac, jumping from one to the other to get the job done. Acycle has done away with the need for this, and I have been impressed with how very user friendly the program is – an indication of the tremendous effort and thought that has gone into putting this together.
You should all feel very proud of this contribution. It opens up much needed access to these powerful tools for a wide audience in the sedimentary geology and paleoclimate community. Thanks again for all your efforts. A really marvellous job.
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."
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.
Dr. Arsenio Muñoz Jiménez (Department of Earth Sciences, 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."
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.
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.
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.
Dr. Nicolas R. Thibault (University of Copenhagen, 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."
Acycle has been used in
1. 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
2. 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
3. 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
4. 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
5. Shi, J., Jin, Z., Liu, Q., Zhang, R., Huang, Z., 2019. Cyclostratigraphy and astronomical tuning of the middle eocene terrestrial successions in the Bohai Bay Basin, Eastern China. Global and Planetary Change 174, 115-126. https://doi.org/10.1016/j.gloplacha.2019.01.001
6. Lu, Y., Huang, C., Jiang, S., Zhang, J., Lu, Y., Liu, Y., 2019. Cyclic late Katian through Hirnantian glacioeustasy and its control of the development of the organic-rich Wufeng and Longmaxi shales, South China. Palaeogeography, Palaeoclimatology, Palaeoecology. https://doi.org/10.1016/j.palaeo.2019.04.012
7. Zhang, Y., Yi, L., Ogg, J.G., 2019. Pliocene-Pleistocene magneto-cyclostratigraphy of IODP Site U1499 and implications for climate-driven sedimentation in the northern South China Sea. Palaeogeography, Palaeoclimatology, Palaeoecology. https://doi.org/10.1016/j.palaeo.2019.04.030
8. Zhang, R., Jin, Z., Liu, Q., Li, P., Huang, Z., Shi, J., Ge, Y., Du, K., 2019. Astronomical constraints on deposition of the Middle Triassic Chang 7 lacustrine shales in the Ordos Basin, Central China. Palaeogeography, Palaeoclimatology, Palaeoecology. https://doi.org/10.1016/j.palaeo.2019.04.030
9. Zhao, K., Du, X., Lu, Y., Xiong, S., Wang, Y., 2019. Are light-dark coupled laminae in lacustrine shale seasonally controlled? A case study using astronomical tuning from 42.2 to 45.4 Ma in the Dongying Depression, Bohai Bay Basin, eastern China. Palaeogeography, Palaeoclimatology, Palaeoecology 528, 35-49. https://doi.org/10.1016/j.palaeo.2019.04.034
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 (examples).
- 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 (example).
- Detrending is usually useful (example).
- 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 (example).
- Users may need evolutionary power spectral analysis (example) 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 (example).
- 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 (example).
- Stratigraphic data series may be correlated/tuned using the “Age Scale” function in Acycle based on the astronomical cycles inferred from filtering (example).
- 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.
Flowchart of the cyclostratigraphic analysis in Acycle software
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.