This short cartoon video uses a simple baseball analogy (steroid use increases probability of hitting home runs) to explain how small increases in greenhouse gases can cause global temperature changes and increase the probability of extreme weather events.

This activity focuses on reconstructing the Paleocene-Eocene Thermal Maximum (PETM) as an example of a relatively abrupt global warming period. Students access Integrated Ocean Drilling Program (IODP) sediment core data with Virtual Ocean software in order to display relevant marine sediments and their biostratigraphy.

In this activity, students learn about the tools and methods paleoclimatologists use to reconstruct past climates. In constructing sediment cores themselves, students will achieve a very good understanding of the sedimentological interpretation of past climates that scientists can draw from cores.

This series of visualizations show the annual Arctic sea ice minimum from 1979 to 2015. The decrease in Arctic sea ice over time is shown in an animation and a graph plotted simultaneously, but can be parsed so that the change in sea ice area can be shown without the graph.

This teaching activity is an introduction to how ice cores from the cryosphere are used as indicators and record-keepers of climate change as well as how climate change will affect the cryosphere.

This short video clip summarizes NOAA's annual State of the Climate Report for 2009. It presents a comprehensive summary of Earth's climate in 2009 and establishes the last decade as the warmest on record. Reduced extent of Arctic sea ice, glacier volume, and snow cover reflect the effects of rising global temperature.

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 NiÃo and La NiÃa 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.