Pyleoclim: Paleoclimate Timeseries Analysis and Visualization With Python
Pyleoclim: Paleoclimate Timeseries Analysis and Visualization With Python
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DOI：
10.1029/2022pa004509
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发表时间：
2022-10-01
影响因子：
3.5
通讯作者：
Gil, Yolanda
中科院分区：
文献类型：
--
作者：
Khider, Deborah;Emile-Geay, Julien;Gil, Yolanda
我们提出了一个Python包，面向古气候时间序列的直观分析和可视化，Pyleoclim。代码是开源的、面向对象的，并且构建在标准的科学Python堆栈之上，允许用户利用大量现有的和新兴的技术。我们描述了代码的原理、结构和基本功能，并将其应用于三个古气候问题：(a)深海岩心的轨道尺度气候变率，说明了存在年龄不确定性的光谱、小波和相干性分析；(b)将高分辨率洞穴与气候场进行关联，说明在存在各种统计缺陷（包括年龄不确定性）的情况下进行相关分析；(c)频域中的模型-数据对抗，说明缩放行为的表征。我们展示了该软件包如何用于古气候和古海洋学数据集的透明和可重复分析，支持可查找、可访问、可互操作和可重用的软件和开放的科学精神。该软件包由大量文档和不断增长的教程库提供支持，这些教程库以视频和云可执行的Jupyter笔记本的形式公开共享，以鼓励新用户采用。
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.