In this activity, students learn about the urban heat island effect by investigating which areas of their schoolyard have higher temperatures - trees, grass, asphalt, and other materials. Based on their results, they hypothesize how concentrations of surfaces that absorb heat might affect the temperature in cities - the urban heat island effect. Then they analyze data about the history of Los Angeles heat waves and look for patterns in the Los Angeles climate data and explore patterns.
This classroom resource is a combination of 3 visualizations and accompanying text that illustrate how 3 key natural phenomena - cyclical changes in solar energy output, major volcanic eruptions over the last century, and El Nino/Nina cycles - are insufficient to explain recent global warming.
This NASA animation of the Five-Year Average Global Temperature Anomalies from 1881 to 2009 shows how temperature anomalies have varied in the last 130 years. The color-coded map displays a long-term progression of changing global surface temperatures from 1881 to 2009. Dark red indicates the greatest warming and dark blue indicates the greatest cooling.
This video introduces phytoplankton - the base of the marine food web, the source of half of the oxygen on Earth, and an important remover of CO2 from the atmosphere. The video also explains how satellites are used to monitor phytoplankton and how warming waters and acidification negatively affect phytoplankton.
In this lab activity, students use a chemical indicator (bromothymol blue) to detect the presence of carbon dioxide in animal and plant respiration and in the burning of fossil fuels and its absence in the products of plant photosynthesis. After completing the five parts of this activity, students compare the colors of the chemical indicator in each part and interpret the results in terms of the qualitative importance of carbon sinks and sources.
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.
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.