Motivate...
The interactive tool above from NASA called ‘Climate Time Machine’ showcases a selection of variables that have been documented over a period of time. These videos come from a variety of time series. In Meteo 815, you worked with time series data, but in this course, we are going to utilize this data in ways that take advantage of the time component. The two primary purposes for time series data in this course will be 1) to explore a natural phenomenon (such as changes in a variable, like temperature) and 2) for forecasting.
In this lesson, we will begin with the basics. We will focus on breaking down the time series into components, perform initial analyses, and begin to look at common patterns in weather and climate data. There are a lot of time series data out there. I highly recommend checking out the NASA App ‘Eyes on Earth’ which allows you to look and play with some of this data. Or you can check out Science On a Sphere which has a variety of movies (intended for a sphere but still pretty cool) that showcase an enormous amount of weather/climate variables through time. They are both great ways to appreciate the amount of data out there and the length of these datasets.
Lesson Objectives
- List the most important aspects to consider when performing a time series analysis.
- Distinguish between stationary and nonstationary.
- Identify common patterns in weather and climate data.
- Prepare and decompose a time series.
Newsstand
- Srivastava, Tavish. (2015, December 16). A Complete Tutorial on Time Series Modeling in R. Retrieved August 14, 2017.
- NOAA. Natural Climate Patterns. Retrieved August 14, 2017.
- NOAA. Locating Climate and Weather Data and Information. Retrieved August 14, 2017.
- NASA. Eyes on the Earth. Retrieved August 14, 2017.
- NOAA. Dataset Catalog. Retrieved August 14, 2017.
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