C-Learn is a simplified version of a climate 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 interactive visualization is a suite of weather and climate datasets as well as tools with which to manipulate and display them visually.

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.

This is a series of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images taken over a 10 year period, 2000-2010, showing the extent of deforestation in the State of Rondonia in western Brazil over that period of time.

This is an interactive graph that involves records of ice cover in two Wisconsin lakes - Lake Mendota and Lake Monona - from 1855-2010.

This visualization tool shows sea ice data from 1978 to the present. Selected data can be animated to show changes in sea ice extent over time. Data is added by the National Snow and Ice Data Center as it becomes available.

This article and slide show from the New York Times, features several scientists from the University of Alaska, Fairbanks, who study the effects of thawing permafrost in Alaska.

This is an interactive webtool that allows the user to choose a state or country and both assess how climate has changed over time and project what future changes are predicted to occur in a given area.

This interactive visualization allows users to compare projections of Wisconsin's average annual temperature with the actual changes of the last five decades. Text on the web page encourages students to think about the challenges Wisconsin could face if these changes occur.

This interactive visualization depicts sea surface temperatures (SST) and SST anomalies from 1885 to 2007. Learn all about SST and why SST data are highly valuable to ocean and atmospheric scientists. Understand the difference between what actual SST readings can reveal about local weather conditions and how variations from normalâcalled anomaliesâcan help scientists identify warming and cooling trends and make predictions about the effects of global climate change. Discover the relationships between SST and marine life, sea ice formation, local and global weather events, and sea level.