In this activity students work with real datasets to investigate a real situation regarding disappearing Arctic sea ice. The case study has students working side-by-side with a scientist from the National Snow and Ice Data Center and an Inuit community in Manitoba.

In this activity, students research various topics about ocean health, e.g. overfishing, habitat destruction, invasive species, climate change, pollution, and ocean acidification. An optional extension activity has them creating an aquatic biosphere in a bottle experiment in which they can manipulate variables.

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.

This is a series of 6 guided-inquiry activities that examine data and models that climate scientists use to attempt to answer the question of Earth's future climate.

In this activity, students are guided through the process of locating and graphing web-based environmental data that has been collected by GLOBE Program participants using actual data collected by students in Pennsylvania and comparing them to their local climatic boundary conditions. This activity highlights the opportunities for using GLOBE data to introduce basic concepts of Earth system science.

In this activity, students use a physical model to learn the basics of photosynthesis and respiration within the carbon cycle.

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 activity involves plotting and comparing monthly data on atmospheric C02 concentrations over two years, as recorded in Mauna Loa and the South Pole, and postulating reasons for differences in their seasonal patterns. Longer-term data is then examined for both sites to see if seasonal variations from one site to the other carry over into longer term trends.

This is a teaching activity in which students learn about the connection between CO2 emissions, CO2 concentration, and average global temperatures. Through a simple online model, students learn about the relationship between these and learn about climate modeling while predicting temperature change over the 21st century.

This activity introduces students to visualization capabilities available through NASA's Earth Observatory, global map collection, NASA NEO and ImageJ. Using these tools, students build several animations of satellite data that illustrate carbon pathways through the Earth system.