This activity with a lab report instructs students to solve and plot 160,000 years' worth of ice core data from the Vostok ice core using Excel or similar spreadsheets to analyze data. Students learn about ice cores and what they can tell us about past atmospheric conditions and the past atmospheric concentrations of CO2 and CH4.

This narrated animation displays three separate graphs of carbon emissions by humans, atmospheric concentrations of CO2, and average global temperature as it has changed over the last 1000 years. The final slide overlays the three graphs to show how they all correspond.

This video is part two of a seven-part National Academies series, Climate Change: Lines of Evidence. The video outlines, with the use of recent research and historical data, how we know that the Earth is warming.

This video, from ClimateCentral, features a team of scientists from the Northern Greenland Eemian Ice Drilling Project (NEEM), who study atmospheric air bubbles trapped in an ice core from a period in Greenland's ice sheet which began about 130,000 years ago and lasted about 10,000 years; a period known as the Eemian. The air bubbles from the ancient atmosphere - all aligned on the same time scale - reveal what happened with climate change over that period of time.

In this activity, students use authentic Arctic climate data to unravel some causes and effects related to the seasonal melting of the snowpack and to further understand albedo.

This static graph of changes in CO2 concentrations goes back 400,000 years, showing the dramatic spike in recent years.

In this exercise learners use statistics (T-test using Excel) to analyze an authentic dataset from Lake Mendota in Madison, WI that spans the last 150 years to explore ice on/ice off dates. In addition, students are asked to investigate the IPCC Likelihood Scale and apply it to their statistical results.

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 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 animation shows predicted changes in temperature across the globe, relative to pre-industrial levels, under two different emissions scenarios in the COP 17 climate model. The first is with emissions continuing to increase through the century. The second is with emissions declining through the century.