Pyleoclim: Paleoclimate Timeseries Analysis and Visualization With Python

We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim. The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging tec...

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Vydáno v:Paleoceanography and paleoclimatology Ročník 37; číslo 10
Hlavní autoři: Khider, Deborah, Emile‐Geay, Julien, Zhu, Feng, James, Alexander, Landers, Jordan, Ratnakar, Varun, Gil, Yolanda
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken Blackwell Publishing Ltd 01.10.2022
Témata:
Analysis
Climate
Climate variability
Climatic analysis
Correlation analysis
Datasets
Documentation
Ecology
Online tutorials
Paleoclimate
paleoclimate observations
Paleoclimatology
Python
Scaling
Scientists
Software
timeseries analysis
Uncertainty
Visualization
Wavelet analysis
ISSN:2572-4517, 2572-4525
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Abstract We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim. The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure, and base functionalities and apply it to three paleoclimate problems: (a) orbital‐scale climate variability in a deep‐sea core, illustrating spectral, wavelet, and coherency analysis in the presence of age uncertainties; (b) correlating a high‐resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (c) model‐data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting Findable, Accessible, Interoperable, and Reusable software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud‐executable Jupyter notebooks, to encourage adoption by new users. Plain Language Summary This article describes a software application called Pyleoclim meant to help scientists analyze datasets of ordered observations, particularly applicable to the study of past climates, environments, and ecology. Pyleoclim is meant to be used by domain scientists as well as students interested in learning more about Earth's climate through examples provided in the documentation and online tutorials. Pyleoclim is intended to help scientists save time with their analyses, documenting the steps for better transparency, and as such, allows other scientists to reproduce results from previous studies. Key Points Pyleoclim makes timeseries analysis tools accessible to practicing scientists, via a user‐friendly Python package Three Jupyter Notebooks illustrate how Pyleoclim facilitates common and advanced tasks Pyleoclim can enhance reproducibility and rigor of paleogeoscientific workflows involving timeseries
AbstractList We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim. The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure, and base functionalities and apply it to three paleoclimate problems: (a) orbital‐scale climate variability in a deep‐sea core, illustrating spectral, wavelet, and coherency analysis in the presence of age uncertainties; (b) correlating a high‐resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (c) model‐data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting Findable, Accessible, Interoperable, and Reusable software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud‐executable Jupyter notebooks, to encourage adoption by new users.
We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim. The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure, and base functionalities and apply it to three paleoclimate problems: (a) orbital‐scale climate variability in a deep‐sea core, illustrating spectral, wavelet, and coherency analysis in the presence of age uncertainties; (b) correlating a high‐resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (c) model‐data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting Findable, Accessible, Interoperable, and Reusable software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud‐executable Jupyter notebooks, to encourage adoption by new users. Plain Language Summary This article describes a software application called Pyleoclim meant to help scientists analyze datasets of ordered observations, particularly applicable to the study of past climates, environments, and ecology. Pyleoclim is meant to be used by domain scientists as well as students interested in learning more about Earth's climate through examples provided in the documentation and online tutorials. Pyleoclim is intended to help scientists save time with their analyses, documenting the steps for better transparency, and as such, allows other scientists to reproduce results from previous studies. Key Points Pyleoclim makes timeseries analysis tools accessible to practicing scientists, via a user‐friendly Python package Three Jupyter Notebooks illustrate how Pyleoclim facilitates common and advanced tasks Pyleoclim can enhance reproducibility and rigor of paleogeoscientific workflows involving timeseries
We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim . The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure, and base functionalities and apply it to three paleoclimate problems: (a) orbital‐scale climate variability in a deep‐sea core, illustrating spectral, wavelet, and coherency analysis in the presence of age uncertainties; (b) correlating a high‐resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (c) model‐data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting Findable, Accessible, Interoperable, and Reusable software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud‐executable Jupyter notebooks, to encourage adoption by new users. This article describes a software application called Pyleoclim meant to help scientists analyze datasets of ordered observations, particularly applicable to the study of past climates, environments, and ecology. Pyleoclim is meant to be used by domain scientists as well as students interested in learning more about Earth's climate through examples provided in the documentation and online tutorials. Pyleoclim is intended to help scientists save time with their analyses, documenting the steps for better transparency, and as such, allows other scientists to reproduce results from previous studies. Pyleoclim makes timeseries analysis tools accessible to practicing scientists, via a user‐friendly Python package Three Jupyter Notebooks illustrate how Pyleoclim facilitates common and advanced tasks Pyleoclim can enhance reproducibility and rigor of paleogeoscientific workflows involving timeseries
Author James, Alexander
Ratnakar, Varun
Khider, Deborah
Zhu, Feng
Gil, Yolanda
Emile‐Geay, Julien
Landers, Jordan
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  surname: Gil
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Cites_doi 10.1093/climsys/dzx002
10.1002/2015MS000447
10.1098/rspa.1998.0193
10.1016/s0098-3004(97)00087-3
10.1103/PhysRevE.94.052201
10.1038/sdata.2016.18
10.5281/zenodo.7093617
10.1029/2000RG000091
10.1126/science.1227079
10.1162/dint_a_00033
10.1029/2004PA001071
10.5281/zenodo.6365841
10.1126/sciadv.aau4996
10.1126/science.1120395
10.1029/2019GL086908
10.1109/MCSE.2007.55
10.1002/joc.1499
10.1029/2011JD017187
10.1103/PhysRevE.92.022126
10.1038/s41592-019-0686-2
10.18637/jss.v029.i05
10.5281/zenodo.6775197
10.1038/s41586-020-2649-2
10.1111/j.2517-6161.1995.tb02031.x
10.3390/e15010327
10.5281/zenodo.1205661
10.1073/pnas.1304328110
10.1029/2018jd029867
10.1021/ac60214a047
10.1016/0167-2789(89)90077-8
10.5194/cp-12-1093-2016
10.1175/JCLI4237.1
10.1073/pnas.1809959116
10.5194/npg-11-561-2004
10.1175/JCLI-D-16-0877.1
10.1103/PhysRevE.90.052150
10.1561/0900000004
10.21105/joss.03021
10.1175/1520-0442(1996)009<3373:mcsdio>2.0.co;2
10.1016/j.quascirev.2011.02.005
10.1016/0167-2789(92)90103-T
10.25080/Majora-92bf1922-00a
10.1029/97jc01734
10.25080/Majora-92bf1922-011
10.5334/jors.148
10.3233/ds-190026
10.1175/1520-0442(1997)010<2147:amtets>2.0.co;2
10.1029/2019gc008392
10.21105/joss.00659
10.1002/2014PA002713
10.1109/proc.1982.12433
10.1002/2016pa003057
10.1029/2000RG000092
10.1111/j.1467-9876.2008.00623.x
10.1016/j.physrep.2018.10.005
10.1002/2016JD024751
10.1175/1520-0477(1998)079<0061:apgtwa>2.0.co;2
10.1038/s41467-022-28210-1
10.5281/zenodo.6999577
10.6084/m9.figshare.1014336
10.1086/160554
10.1038/518125a
10.5194/gchron-3-149-2021
10.1086/118137
10.1175/2010JCLI3654.1
10.1038/nature19798
10.5281/zenodo.5771123
10.1126/science.1141038
10.1029/2000GL012698
10.1007/bf00648343
10.1016/j.epsl.2016.11.048
10.1016/j.epsl.2017.07.036
10.1029/2019rg000657
10.1086/167757
10.1016/s0098-3004(01)00044-9
10.1063/1.5010253
10.5194/cp-15-1251-2019
10.1073/pnas.1412077111
10.1109/mcse.2007.46
10.1038/NGEO1862
10.1038/sdata.2017.88
10.3847/1538-4365/aab766
10.1126/science.1171041
10.3847/1538-4357/ab910d
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References 2017; 5
2017; 2
2017; 4
2019; 15
2020; 17
2019; 124
2005; 20
1982; 263
2020; 58
1995; 138
2011; 12
1992; 58
2014; 29
2017; 476
2013; 6
2010; 23
1997; 102
2017; 30
2013; 15
2018; 3
2020; 3
2020; 2
2019; 20
1989; 343
1997; 10
2002; 40
2017; 32
2007; 9
2020; 896
2019; 116
2020; 47
1964; 36
2013; 110
2007; 20
1976; 39
2007; 1
1989; 35
2012; 338
1996; 9
2009; 325
2007; 27
2018; 28
2021; 6
2014; 90
2021; 3
2019; 5
1982; 70
2015; 92
2010
1995; 57
1997; 23
2011; 30
2019; 787
2016; 121
2008; 57
2020; 585
2016; 94
2001; 28
2014; 111
1998; 454
2015; 7
2006; 312
2016; 12
2009; 29
2017; 459
2004; 11
2002; 28
2007; 317
2016; 3
2022
2016; 538
2021
2018; 236
1964
2019
2022; 13
2015; 518
2017
2016
2001; 39
1996; 112
2012; 117
1998; 79
e_1_2_7_3_1
e_1_2_7_9_1
e_1_2_7_7_1
e_1_2_7_19_1
e_1_2_7_60_1
e_1_2_7_83_1
e_1_2_7_17_1
e_1_2_7_81_1
e_1_2_7_15_1
e_1_2_7_41_1
e_1_2_7_64_1
e_1_2_7_87_1
e_1_2_7_13_1
e_1_2_7_43_1
e_1_2_7_66_1
e_1_2_7_85_1
e_1_2_7_11_1
e_1_2_7_45_1
Pedregosa F. (e_1_2_7_62_1) 2011; 12
e_1_2_7_68_1
e_1_2_7_47_1
e_1_2_7_89_1
e_1_2_7_26_1
e_1_2_7_49_1
e_1_2_7_28_1
e_1_2_7_90_1
e_1_2_7_73_1
e_1_2_7_50_1
e_1_2_7_71_1
e_1_2_7_92_1
e_1_2_7_25_1
e_1_2_7_31_1
e_1_2_7_52_1
e_1_2_7_77_1
e_1_2_7_23_1
e_1_2_7_33_1
e_1_2_7_54_1
e_1_2_7_21_1
e_1_2_7_35_1
Mix A. C. (e_1_2_7_56_1) 1995; 138
e_1_2_7_37_1
e_1_2_7_79_1
e_1_2_7_39_1
Dawdy D. (e_1_2_7_5_1) 1964
Shackleton N. J. (e_1_2_7_75_1) 1995; 138
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e_1_2_7_27_1
e_1_2_7_29_1
e_1_2_7_91_1
e_1_2_7_72_1
National Academies of Sciences, Engineering, and Medicine (e_1_2_7_58_1) 2021
e_1_2_7_51_1
e_1_2_7_70_1
e_1_2_7_30_1
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References_xml – volume: 343
  start-page: 874
  issue: 2
  year: 1989
  end-page: 887
  article-title: Studies in astronomical time series analysis. III. Fourier transforms, aotocorrelation functions, and cross‐correlation functions of unevenly‐spaced data
  publication-title: The Astrophysical Journal
– volume: 138
  start-page: 839
  year: 1995
  end-page: 847
  article-title: Benthic foraminiferal stable isotope stratigraphy from site 846: 0‐1.8Ma
  publication-title: Proceedings of the Ocean Drilling Program. Scientific results
– volume: 325
  start-page: 310
  issue: 5938
  year: 2009
  end-page: 314
  article-title: Transient simulation of last deglaciation with a new mechanism for bølling‐allerød warming
  publication-title: Science
– volume: 27
  start-page: 1119
  issue: 9
  year: 2007
  end-page: 1152
  article-title: Empirical orthogonal functions and related techniques in atmospheric science: A review
  publication-title: International Journal of Climatology
– volume: 57
  start-page: 399
  issue: 4
  year: 2008
  end-page: 418
  article-title: A simple monotone process with application to radiocarbon‐dated depth chronologies
  publication-title: Journal of the Royal Statistical Society: Series C (Applied Statistics)
– volume: 787
  start-page: 1
  year: 2019
  end-page: 97
  article-title: Complex network approaches to nonlinear time series analysis
  publication-title: Physics Reports
– volume: 57
  start-page: 289
  issue: 1
  year: 1995
  end-page: 300
  article-title: Controlling the false discovery rate: A practical and powerful approach to multiple testing
  publication-title: Journal of the Royal Statistical Society: Series B
– volume: 36
  start-page: 1627
  issue: 8
  year: 1964
  end-page: 1639
  article-title: Smoothing and differentiation of data by simplified least squares procedures
  publication-title: Analytical Chemistry
– volume: 4
  issue: 1
  year: 2017
  article-title: A global multiproxy database for temperature reconstructions of the Common Era
  publication-title: Scientific Data
– start-page: 87
  year: 2016
  end-page: 90
– year: 2021
– volume: 9
  start-page: 52
  issue: 3
  year: 2007
  end-page: 55
  article-title: Analysis of functional magnetic resonance imaging in Python
  publication-title: Computing in Science and Enginering
– volume: 2
  start-page: 108
  issue: 1–2
  year: 2020
  end-page: 121
  article-title: FAIR computational workflows
  publication-title: FAIR Computational Workflows. Data Intelligence
– volume: 23
  start-page: 929
  issue: 9
  year: 1997
  end-page: 945
  article-title: Spectrum: Spectral analysis of unevenly spaced time series
  publication-title: Computers & Geosciences
– volume: 116
  start-page: 8728
  issue: 18
  year: 2019
  end-page: 8733
  article-title: Climate models can correctly simulate the continuum of global‐average temperature variability
  publication-title: Proceedings of the National Academy of Sciences
– volume: 459
  start-page: 362
  year: 2017
  end-page: 371
  article-title: Correlation‐based interpretations of paleoclimate data – Where statistics meet past climates
  publication-title: Earth and Planetary Science Letters
– volume: 23
  start-page: 6074
  issue: 22
  year: 2010
  end-page: 6081
  article-title: Long‐range dependence and climate noise characteristics of Antarctic temperature data
  publication-title: Journal of Climate
– volume: 312
  start-page: 79
  issue: 5770
  year: 2006
  end-page: 83
  article-title: Evolution of the eastern tropical Pacific through plio‐pleistocne glaciation
  publication-title: Science
– volume: 1
  start-page: 163
  issue: 3
  year: 2007
  end-page: 257
  article-title: Long range dependence
  publication-title: Foundations and Trends in Stochastic Systems
– volume: 585
  start-page: 357
  issue: 7825
  year: 2020
  end-page: 362
  article-title: Array programming with NumPy
  publication-title: Nature
– volume: 12
  start-page: 1093
  issue: 4
  year: 2016
  end-page: 1100
  article-title: Technical note: The linked paleo data framework – A common tongue for paleoclimatology
  publication-title: Climate of the Past
– volume: 11
  start-page: 561
  issue: 5/6
  year: 2004
  end-page: 566
  article-title: Application of the cross wavelet transform and wavelet coherence to geophysical time series
  publication-title: Nonlinear Processes in Geophysics
– volume: 13
  issue: 1
  year: 2022
  article-title: A re‐appraisal of the ENSO response to volcanism with paleoclimate data assimilation
  publication-title: Nature Communications
– volume: 90
  issue: 5
  year: 2014
  article-title: Unraveling the cause‐effect relation between time series
  publication-title: Physical Review E ‐ Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
– year: 2022
– volume: 3
  issue: 24
  year: 2018
  article-title: Climlab: A python toolkit for interactive, process‐oriented climate modeling
  publication-title: Journal of Open Source Software
– volume: 3
  start-page: 149
  issue: 1
  year: 2021
  end-page: 169
  article-title: geoChronR – An R package to model, analyze, and visualize age‐uncertain data
  publication-title: Geochronology
– volume: 12
  start-page: 2825
  issue: 85
  year: 2011
  end-page: 2830
  article-title: Scikit‐learn: Machine learning in Python
  publication-title: Journal of Machine Learning Research
– volume: 236
  issue: 1
  year: 2018
  article-title: Understanding the lomb–scargle periodogram
  publication-title: The Astrophysical Journal ‐ Supplement Series
– volume: 17
  start-page: 261
  issue: 3
  year: 2020
  end-page: 272
  article-title: SciPy 1.0: Fundamental algorithms for scientific computing in Python
  publication-title: Nature Methods
– volume: 518
  start-page: 125
  issue: 7537
  year: 2015
  end-page: 126
  article-title: Programming: Pick up Python
  publication-title: Nature
– volume: 6
  issue: 60
  year: 2021
  article-title: Seaborn: Statistical data visualization
  publication-title: Journal of Open Source Software
– volume: 94
  issue: 5
  year: 2016
  article-title: Information flow and causality as rigorous notions ab initio
  publication-title: Physical Review E ‐ Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
– year: 2019
– volume: 338
  start-page: 496
  issue: 6106
  year: 2012
  end-page: 500
  article-title: Detecting causality in complex ecosystems
  publication-title: Science
– volume: 20
  issue: 1
  year: 2005
  article-title: A Pliocene‐Pleistocene stack of 57 globally distributed benthic O records
  publication-title: Paleoceanography
– volume: 79
  start-page: 61
  issue: 1
  year: 1998
  end-page: 78
  article-title: A practical guide to wavelet analysis
  publication-title: Bulletin of the American Meteorological Society
– volume: 29
  start-page: 1
  issue: 5
  year: 2009
  end-page: 19
  article-title: Maximum entropy bootstrap for time series: The meboot r package
  publication-title: Journal of Statistical Software
– volume: 476
  start-page: 34
  year: 2017
  end-page: 46
  article-title: Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi‐decadal variability
  publication-title: Earth and Planetary Science Letters
– volume: 70
  start-page: 1055
  issue: 9
  year: 1982
  end-page: 1096
  article-title: Spectrum estimation and harmonic analysis
  publication-title: Proceedings of the IEEE
– year: 1964
– volume: 15
  start-page: 327
  issue: 1
  year: 2013
  end-page: 360
  article-title: The Liang‐Kleeman information flow: Theory and applications
  publication-title: Entropy
– volume: 32
  start-page: 1275
  issue: 11
  year: 2017
  end-page: 1290
  article-title: The role of uncertainty in estimating lead/lag relationships in marine sedimentary archives: A case study from the tropical Pacific
  publication-title: Paleoceanography
– volume: 39
  start-page: 447
  issue: 2
  year: 1976
  end-page: 462
  article-title: Least‐squares frequency analysis of unequally spaced data
  publication-title: Astrophysics and Space Science
– volume: 5
  issue: 1
  year: 2017
  article-title: Xarray: N‐D labeled arrays and datasets in Python
  publication-title: Journal of Open Research Software
– volume: 110
  start-page: 12213
  issue: 30
  year: 2013
  end-page: 12218
  article-title: Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection
  publication-title: Proceedings of the National Academy of Sciences of the United States of America
– volume: 58
  start-page: 95
  issue: 1
  year: 1992
  end-page: 126
  article-title: Singular‐spectrum analysis: A toolkit for short, noisy chaotic signals
  publication-title: Physica D: Nonlinear Phenomena
– volume: 117
  issue: D8
  year: 2012
  article-title: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set
  publication-title: Journal of Geophysical Research
– volume: 35
  start-page: 395
  issue: 3
  year: 1989
  end-page: 424
  article-title: Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series
  publication-title: Physica D
– volume: 2
  issue: 1
  year: 2017
  article-title: A probabilistic Pliocene–Pleistocene stack of benthic O using a profile hidden Markov model
  publication-title: Dynamics and Statistics of the Climate System
– volume: 263
  start-page: 835
  issue: 2
  year: 1982
  end-page: 853
  article-title: Studies in astronomical time series analysis. ii. Statistical aspects of spectral analysis of unevenly spaced data
  publication-title: The Astrophysical Journal
– volume: 20
  start-page: 4377
  issue: 17
  year: 2007
  end-page: 4401
  article-title: Simulation of the last 21,000 years using accelerated transient boundary conditions
  publication-title: Journal of Climate
– start-page: 56
  year: 2010
  end-page: 61
– year: 2017
  article-title: Data analysis in the Earth & environmental sciences (Third ed.)
  publication-title: FigShare
– volume: 30
  start-page: 1155
  issue: 9
  year: 2011
  end-page: 1172
  article-title: Deconstructing the last glacial termination: The role of millennial and orbital‐scale forcings
  publication-title: Quaternary Science Reviews
– volume: 454
  start-page: 903
  issue: 1971
  year: 1998
  end-page: 995
  article-title: The empirical mode decomposition and the hilbert spectrum for nonlinear and non‐stationary time series analysis
  publication-title: Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences
– volume: 20
  start-page: 3774
  issue: 7
  year: 2019
  end-page: 3781
  article-title: The climate data toolbox for MATLAB
  publication-title: Geochemistry, Geophysics, Geosystems
– volume: 28
  issue: 7
  year: 2018
  article-title: Causation and information flow with respect to relative entropy
  publication-title: Chaos: An interdisciplinary journal of nonlinear science
– year: 2010
– volume: 28
  start-page: 3187
  issue: 16
  year: 2001
  end-page: 3190
  article-title: Singular spectrum analysis for time series with missing data
  publication-title: Geophysical Research Letters
– volume: 28
  start-page: 421
  issue: 3
  year: 2002
  end-page: 426
  article-title: Redfit: Estimating red‐noise spectra directly from unevenly spaced paleoclimatic time series
  publication-title: Computers & Geosciences
– volume: 121
  start-page: 6745
  issue: 12
  year: 2016
  end-page: 6764
  article-title: The last millennium climate reanalysis project: Framework and first results
  publication-title: Journal of Geophysical Research: Atmospheres
– volume: 15
  start-page: 1251
  issue: 4
  year: 2019
  end-page: 1273
  article-title: Last millennium reanalysis with an expanded proxy database and seasonal proxy modeling
  publication-title: Climate of the Past
– volume: 92
  issue: 2
  year: 2015
  article-title: Normalizing the causality between time series
  publication-title: Physical Review E ‐ Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
– volume: 896
  issue: 2
  year: 2020
  article-title: Systematic search for ‐ray periodicity in active galactic nuclei detected by the fermi large area telescope
  publication-title: The Astrophysical Journal
– volume: 3
  issue: 1
  year: 2016
  article-title: The FAIR Guiding Principles for scientific data management and stewardship
  publication-title: Scientific Data
– volume: 317
  start-page: 793
  issue: 5839
  year: 2007
  end-page: 796
  article-title: Orbital and millennial Antarctic climate variability over the past 800,000 years
  publication-title: Science
– volume: 39
  start-page: 325
  issue: 3
  year: 2001
  end-page: 346
  article-title: Glacial cycles: Toward a new paradigm
  publication-title: Reviews of Geophysics
– volume: 9
  start-page: 3373
  issue: 12
  year: 1996
  end-page: 3404
  article-title: Monte Carlo SSA: Detecting irregular oscillations in the presence of coloured noise
  publication-title: Journal of Climate
– volume: 5
  issue: 11
  year: 2019
  article-title: Detecting and quantifying causal associations in large nonlinear time series datasets
  publication-title: Science Advances
– volume: 7
  start-page: 1220
  issue: 3
  year: 2015
  end-page: 1247
  article-title: PRYSM: An open‐source framework for PRoxY System Modeling, with applications to oxygen‐isotope systems
  publication-title: Journal of Advances in Modeling Earth Systems
– volume: 40
  start-page: 1003
  issue: 1
  year: 2002
  end-page: 1052
  article-title: Advanced spectral methods for climatic time series
  publication-title: Reviews of Geophysics
– volume: 124
  start-page: 7719
  issue: 14
  year: 2019
  end-page: 7763
  article-title: An ensemble data set of sea surface temperature change from 1850: The met office Hadley centre HadSST.4.0.0.0 data set
  publication-title: Journal of Geophysical Research: Atmospheres
– volume: 111
  start-page: 16682
  issue: 47
  year: 2014
  end-page: 16687
  article-title: Ocean surface temperature variability: Large model–data differences at decadal and longer periods
  publication-title: Proceedings of the National Academy of Sciences of the United States of America
– volume: 538
  start-page: 226
  issue: 7624
  year: 2016
  end-page: 228
  article-title: Evolution of global temperature over the past two million years
  publication-title: Nature
– volume: 9
  start-page: 90
  issue: 3
  year: 2007
  end-page: 95
  article-title: Matplotlib: A 2D graphics environment
  publication-title: Computing in Science & Engineering
– volume: 10
  start-page: 2147
  issue: 9
  year: 1997
  end-page: 2153
  article-title: A method to estimate the statistical significance of a correlation when the data are serially correlated
  publication-title: Journal of Climate
– volume: 47
  issue: 8
  year: 2020
  article-title: Resolving the differences in the simulated and reconstructed temperature response to volcanism
  publication-title: Geophysical Research Letters
– volume: 102
  start-page: 27835
  issue: C13
  year: 1997
  end-page: 27860
  article-title: Reduced space optimal analysis for historical data sets: 136 years of Atlantic sea surface temperatures
  publication-title: Journal of Geophysical Research
– volume: 3
  start-page: 37
  issue: 1
  year: 2020
  end-page: 59
  article-title: Towards fair principles for research software
  publication-title: Data Science
– volume: 29
  start-page: 976
  issue: 976–989
  year: 2014
  end-page: 989
  article-title: Probabilistic sequence alignment of stratigraphic records
  publication-title: Paleoceanography
– volume: 112
  start-page: 1709
  issue: 4
  year: 1996
  end-page: 1729
  article-title: Wavelets for period analysis of unevenly sampled time series
  publication-title: The Astronomical Journal
– volume: 6
  start-page: 617
  issue: 8
  year: 2013
  end-page: 621
  article-title: Variable North Pacific influence on drought in southwestern North America since AD 854
  publication-title: Nature Geoscience
– volume: 30
  start-page: 7157
  issue: 18
  year: 2017
  end-page: 7168
  article-title: Long‐range persistence in global surface temperatures explained by linear multibox energy balance models
  publication-title: Journal of Climate
– volume: 58
  issue: 2
  year: 2020
  article-title: The structure of climate variability across scales
  publication-title: Reviews of Geophysics
– volume: 138
  start-page: 337
  year: 1995
  end-page: 356
  article-title: Pliocene stable isotope stratigraphy of ODP site 846
  publication-title: Proceedings of the Ocean Drilling Program, Scientific Results
– ident: e_1_2_7_2_1
  doi: 10.1093/climsys/dzx002
– ident: e_1_2_7_6_1
  doi: 10.1002/2015MS000447
– ident: e_1_2_7_26_1
  doi: 10.1098/rspa.1998.0193
– ident: e_1_2_7_73_1
  doi: 10.1016/s0098-3004(97)00087-3
– ident: e_1_2_7_44_1
  doi: 10.1103/PhysRevE.94.052201
– ident: e_1_2_7_88_1
  doi: 10.1038/sdata.2016.18
– ident: e_1_2_7_33_1
  doi: 10.5281/zenodo.7093617
– ident: e_1_2_7_60_1
  doi: 10.1029/2000RG000091
– ident: e_1_2_7_77_1
  doi: 10.1126/science.1227079
– volume-title: Statistical and probability analysis of hydrologic data, part III: Analysis of variance, covariance and time series
  year: 1964
  ident: e_1_2_7_5_1
– ident: e_1_2_7_17_1
  doi: 10.1162/dint_a_00033
– ident: e_1_2_7_47_1
  doi: 10.1029/2004PA001071
– ident: e_1_2_7_34_1
  doi: 10.5281/zenodo.6365841
– volume: 12
  start-page: 2825
  issue: 85
  year: 2011
  ident: e_1_2_7_62_1
  article-title: Scikit‐learn: Machine learning in Python
  publication-title: Journal of Machine Learning Research
– ident: e_1_2_7_66_1
  doi: 10.1126/sciadv.aau4996
– ident: e_1_2_7_40_1
  doi: 10.1126/science.1120395
– ident: e_1_2_7_90_1
  doi: 10.1029/2019GL086908
– ident: e_1_2_7_27_1
  doi: 10.1109/MCSE.2007.55
– ident: e_1_2_7_21_1
  doi: 10.1002/joc.1499
– ident: e_1_2_7_57_1
  doi: 10.1029/2011JD017187
– ident: e_1_2_7_43_1
  doi: 10.1103/PhysRevE.92.022126
– ident: e_1_2_7_86_1
  doi: 10.1038/s41592-019-0686-2
– ident: e_1_2_7_85_1
  doi: 10.18637/jss.v029.i05
– ident: e_1_2_7_9_1
  doi: 10.5281/zenodo.6775197
– ident: e_1_2_7_22_1
  doi: 10.1038/s41586-020-2649-2
– ident: e_1_2_7_4_1
  doi: 10.1111/j.2517-6161.1995.tb02031.x
– ident: e_1_2_7_41_1
  doi: 10.3390/e15010327
– ident: e_1_2_7_35_1
  doi: 10.5281/zenodo.1205661
– ident: e_1_2_7_36_1
  doi: 10.1073/pnas.1304328110
– ident: e_1_2_7_30_1
  doi: 10.1029/2018jd029867
– ident: e_1_2_7_68_1
  doi: 10.1021/ac60214a047
– ident: e_1_2_7_83_1
  doi: 10.1016/0167-2789(89)90077-8
– ident: e_1_2_7_51_1
  doi: 10.5194/cp-12-1093-2016
– volume: 138
  start-page: 337
  year: 1995
  ident: e_1_2_7_75_1
  article-title: Pliocene stable isotope stratigraphy of ODP site 846
  publication-title: Proceedings of the Ocean Drilling Program, Scientific Results
– ident: e_1_2_7_80_1
  doi: 10.1175/JCLI4237.1
– ident: e_1_2_7_91_1
  doi: 10.1073/pnas.1809959116
– ident: e_1_2_7_19_1
  doi: 10.5194/npg-11-561-2004
– ident: e_1_2_7_15_1
  doi: 10.1175/JCLI-D-16-0877.1
– ident: e_1_2_7_42_1
  doi: 10.1103/PhysRevE.90.052150
– ident: e_1_2_7_67_1
  doi: 10.1561/0900000004
– ident: e_1_2_7_87_1
  doi: 10.21105/joss.03021
– ident: e_1_2_7_3_1
  doi: 10.1175/1520-0442(1996)009<3373:mcsdio>2.0.co;2
– ident: e_1_2_7_37_1
– ident: e_1_2_7_54_1
  doi: 10.1016/j.quascirev.2011.02.005
– ident: e_1_2_7_84_1
  doi: 10.1016/0167-2789(92)90103-T
– ident: e_1_2_7_53_1
  doi: 10.25080/Majora-92bf1922-00a
– ident: e_1_2_7_29_1
  doi: 10.1029/97jc01734
– ident: e_1_2_7_74_1
  doi: 10.25080/Majora-92bf1922-011
– ident: e_1_2_7_24_1
  doi: 10.5334/jors.148
– ident: e_1_2_7_39_1
  doi: 10.3233/ds-190026
– ident: e_1_2_7_8_1
  doi: 10.1175/1520-0442(1997)010<2147:amtets>2.0.co;2
– ident: e_1_2_7_18_1
  doi: 10.1029/2019gc008392
– ident: e_1_2_7_65_1
  doi: 10.21105/joss.00659
– ident: e_1_2_7_46_1
  doi: 10.1002/2014PA002713
– ident: e_1_2_7_79_1
  doi: 10.1109/proc.1982.12433
– ident: e_1_2_7_31_1
  doi: 10.1002/2016pa003057
– ident: e_1_2_7_16_1
  doi: 10.1029/2000RG000092
– ident: e_1_2_7_23_1
  doi: 10.1111/j.1467-9876.2008.00623.x
– ident: e_1_2_7_92_1
  doi: 10.1016/j.physrep.2018.10.005
– ident: e_1_2_7_20_1
  doi: 10.1002/2016JD024751
– ident: e_1_2_7_81_1
  doi: 10.1175/1520-0477(1998)079<0061:apgtwa>2.0.co;2
– ident: e_1_2_7_89_1
  doi: 10.1038/s41467-022-28210-1
– ident: e_1_2_7_32_1
  doi: 10.5281/zenodo.6999577
– ident: e_1_2_7_10_1
  doi: 10.6084/m9.figshare.1014336
– ident: e_1_2_7_69_1
  doi: 10.1086/160554
– ident: e_1_2_7_63_1
  doi: 10.1038/518125a
– ident: e_1_2_7_52_1
  doi: 10.5194/gchron-3-149-2021
– ident: e_1_2_7_12_1
  doi: 10.1086/118137
– ident: e_1_2_7_13_1
  doi: 10.1175/2010JCLI3654.1
– ident: e_1_2_7_76_1
  doi: 10.1038/nature19798
– ident: e_1_2_7_11_1
  doi: 10.5281/zenodo.5771123
– ident: e_1_2_7_28_1
  doi: 10.1126/science.1141038
– ident: e_1_2_7_71_1
  doi: 10.1029/2000GL012698
– volume: 138
  start-page: 839
  year: 1995
  ident: e_1_2_7_56_1
  article-title: Benthic foraminiferal stable isotope stratigraphy from site 846: 0‐1.8Ma
  publication-title: Proceedings of the Ocean Drilling Program. Scientific results
– ident: e_1_2_7_49_1
  doi: 10.1007/bf00648343
– ident: e_1_2_7_25_1
  doi: 10.1016/j.epsl.2016.11.048
– ident: e_1_2_7_7_1
  doi: 10.1016/j.epsl.2017.07.036
– ident: e_1_2_7_14_1
  doi: 10.1029/2019rg000657
– ident: e_1_2_7_64_1
– ident: e_1_2_7_70_1
  doi: 10.1086/167757
– ident: e_1_2_7_72_1
  doi: 10.1016/s0098-3004(01)00044-9
– ident: e_1_2_7_45_1
  doi: 10.1063/1.5010253
– ident: e_1_2_7_78_1
  doi: 10.5194/cp-15-1251-2019
– ident: e_1_2_7_38_1
  doi: 10.1073/pnas.1412077111
– ident: e_1_2_7_55_1
  doi: 10.1109/mcse.2007.46
– ident: e_1_2_7_50_1
  doi: 10.1038/NGEO1862
– ident: e_1_2_7_59_1
  doi: 10.1038/sdata.2017.88
– ident: e_1_2_7_82_1
  doi: 10.3847/1538-4365/aab766
– volume-title: Identifying new community‐driven science themes for NSF's support of paleoclimate research: Proceedings of a workshop
  year: 2021
  ident: e_1_2_7_58_1
– ident: e_1_2_7_48_1
  doi: 10.1126/science.1171041
– ident: e_1_2_7_61_1
  doi: 10.3847/1538-4357/ab910d
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Snippet We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim. The code is open‐source,...
We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim . The code is open‐source,...
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SubjectTerms Analysis
Climate
Climate variability
Climatic analysis
Correlation analysis
Datasets
Documentation
Ecology
Online tutorials
Paleoclimate
paleoclimate observations
Paleoclimatology
Python
Scaling
Scientists
Software
timeseries analysis
Uncertainty
Visualization
Wavelet analysis
Title Pyleoclim: Paleoclimate Timeseries Analysis and Visualization With Python
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https://www.proquest.com/docview/2728555291
Volume 37
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