One of a suite of online climate interactive simulations, this Greenhouse Gas Simulator uses the bathtub model to demonstrate how atmospheric concentrations of CO2 will continue to rise unless they are lowered to match the amount of CO2 that can be removed through natural processes.

This graph, based on key ice core data sets and recent monitoring programs, shows the variations in concentration of carbon dioxide (CO2) in the atmosphere during the last 400,000 years.

C-Learn is a simplified version of the C-ROADS simulator. Its primary purpose is to help users understand the long-term climate effects (CO2 concentrations, global temperature, sea level rise) of various customized actions to reduce fossil fuel CO2 emissions, reduce deforestation, and grow more trees. Students can ask multiple, customized what-if questions and understand why the system reacts as it does.

This lab exercise is designed to provide a basic understanding of a real-world scientific investigation. Learners are introduced to the concept of tropospheric ozone as an air pollutant due to human activities and burning of fossil fuel energy. The activity uses, analyzes, and visualizes data to investigate this air pollution and climate change problem, determines the season in which it commonly occurs, and communicates the analysis to others in a standard scientific format.

In this activity from the Deep Earth Academy, students divide into groups to read and discuss one of nine short articles (1-2 pages) about research done by the Ocean Drilling Program. These articles discuss our understanding about past climate based on collected data. These articles briefly describe the research conducted and the findings. Students use the information from the article to complete a write-up that they share with other students. An extension activity involves examining ocean drilling data using Google Earth.

Hands-on laboratory activity that allows students to investigate the effects of distance and angle on the input of solar radiation at Earth's surface, the role played by albedo, the heat capacity of land and water, and how these cause the seasons. Students predict radiative heating based on simple geometry and experiment to test their hypotheses.

In this activity for undergraduates, students explore the CLIMAP (Climate: Long-Range Investigation, Mapping and Prediction) model results for differences between the modern and the Last Glacial Maximum (LGM) and discover the how climate and vegetation may have changed in different regions of the Earth based on scientific data.

This multi-part activity introduces users to normal seasonal sea surface temperature (SST) variation as well as extreme variation, as in the case of El NiÃo and La NiÃa events, in the equatorial Pacific Ocean. Via a THREDDS server, users learn how to download seasonal SST data for the years 1982 to 1998. Using a geographic information system (GIS), they visualize and analyze that data, looking for the tell-tale SST signature of El Nino and La Nina events that occurred during that time period. At the end, students analyze a season of their own choosing to determine if an El NiÃo or La NiÃa SST pattern emerged in that year's data.

This activity from NOAA Earth System Research Laboratory introduces students to the current scientific understanding of the greenhouse effect and the carbon cycle. The activity leads them through several interactive tasks investigating recent trends in atmospheric carbon dioxide. Students analyze scientific data and use scientific reasoning to determine the causes responsible for these recent trends. By studying carbon cycle science in a visual and interactive manner, the activity provides students with a conceptual framework with which to address the challenges of a changing climate.

Students consider why the observed atmospheric CO2 increase rate is only ~60% of the CO2 loading rate due to fossil fuel combustion. They develop a box-model to simulate the atmospheric CO2 increase during the industrial era and compare it to the historic observations of atmospheric CO2 concentrations. The model is then used to forecast future concentrations of atmospheric CO2 during the next century.