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Ocean/Atmosphere Time Series Analysis

Authors: Jonathan M. Lilly;

Ocean/Atmosphere Time Series Analysis

Abstract

This package contains all necessary files for the course Ocean/Atmosphere Time Series Analysis, an introduction to data and time series analysis for graduate students in oceanography, atmospheric science, and climate. This material is generally taught in two separate portions, a five-day and a ten-day intensive, both with five hours a day of course time. The first intensive covers Part I: Fundamentals, while the second intensive covers Part II: Spectral and Time-Frequency Analysis. See the course home page for a list of upcoming and past courses. Comments, questions, bug reports, etc. are all welcome. Feel free to email me at jmlilly@psi.edu, or use the GitHub issue tracker. To get started, just open the file index.html with any web browser. These notes were made using Liminal, a theme for Remark.js, itself a Javascript package for rendering Markdown and LaTeX as Powerpoint-style presentations within a web browser. A complete distribution of KaTeX, a minimal typesetting library for LaTeX, is also included. Version 0.2 is the initial public release of the Ocean/Atmosphere Time Series Analysis course files. A significant to-do in this version is translating the stochastic modeling code into Python. Version 0.21 is updated with a doi from Zenodo. Cite as: Lilly, J. M. (2022). Ocean/Atmosphere Time Series Analysis, v. 0.21. Zenodo. https://doi.org/10.5281/zenodo.5977995

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Time series analysis, signal processing, data analysis, course notes

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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