These graphs show carbon dioxide measurements at the Mauna Loa Observatory, Hawaii. The graphs display recent measurements as well as historical long term measurements. The related website summarizes in graphs the recent monthly CO2, the full CO2 Record, the annual Mean CO2 Growth Rate, and gives links to detailed CO2 data for this location, which is one of the most important CO2 tracking sites in the world.
This monthly bulletin and animation provides regular and reliable visualizations of world weather and climate events of the previous month using NOAA data. Archives are available from October 2011 to present.
This video describes why tropical ice cores are important and provide different information than polar ice cores, why getting them now is important (they are disappearing), and how scientists get them. The work of glaciologist Lonnie Thompson is featured, with a focus on his work collecting cores of ice from high mountain glaciers that contain significant data about past climate change.
In this activity, students graph and analyze methane data, extracted from an ice core, to examine how atmospheric methane has changed over the past 109,000 years in a case study format. Calculating the rate of change of modern methane concentrations, they compare the radiative forcing of methane and carbon dioxide and make predictions about the future, based on what they have learned from the data and man's role in that future.
This interactive visualization provides a clear, well-documented snapshot of current and projected values of several climate variables for local areas in California. The climate variables include observed and projected temperatures, projected snowpack, areas vulnerable to flooding due to sea level rise, and projected increase in wildfires. The projected values come from expert sources and well-established climate models.
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.