In this intermediate Excel activity, students import US Historical Climate Network mean temperature data into Excel from a station of their choice. They are then guided through the activity on how to use Excel for statistical calculations, graphing, and linear trend estimates. The activity assumes some familiarity with Excel and graphing in Excel.

In this activity, students learn about the urban heat island effect by investigating which areas of their schoolyard have higher temperatures - trees, grass, asphalt, and other materials. Based on their results, they hypothesize how concentrations of surfaces that absorb heat might affect the temperature in cities - the urban heat island effect. Then they analyze data about the history of Los Angeles heat waves and look for patterns in the Los Angeles climate data and explore patterns.

In this activity, students explore how the timing of color change and leaf drop of New England's deciduous trees is changing.

In this activity, students download historic temperature datasets and then graph and compare with different locations. As an extension, students can download and examine data sets for other sites to compare the variability of changes at different distinct locations, and it is at this stage where learning can be individualized and very meaningful.

In this activity, students review techniques used by scientists as they analyze a 50-year temperature time series dataset. The exercise helps students understand that data typically has considerable variability from year to year and to predict trends, one needs to consider long-term data.

This set of activities is about carbon sources, sinks, and fluxes among them - both with and without anthropogenic components.

In this activity, students chart temperature changes over time in Antarctica's paleoclimate history by reading rock cores. Students use their data to create an interactive display illustrating how Antarctica's climate timeline can be interpreted from ANDRILL rock cores.

In this lesson, students examine and interpret varied observational datasets and are asked to determine whether the data supports or does not support the statement: climate change is occurring in Colorado.

This module contains five activities, in increasing complexity, that focus on understanding how to interpret and manipulate sea level data, using real data from NOAA.

Students first need to understand how to access and interpret sea surface height and tide data. To understand how to interpret these data, students will review and practice computing mean values. Along the way, they will learn how different factors, such as storms, affect tide levels and how to measure them. The goal is for students to become experienced with these kinds of data and the tools for accessing them so that, by the end of the module, they can continue to explore data sets driven by their own inquiry.

In this activity, students make a model sea floor sediment core using two types of buttons to represent fossil diatoms. They then compare the numbers of diatom fossils in the sediment at different depths to determine whether the seas were free of ice while the diatoms were alive.

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