Students analyze surface air temperature anomalies to identify change with respect to different latitudes across the world.

Students will examine air temperature data collected through The GLOBE Program during the 2017 US solar eclipse.

The extreme temperatures during July 2022 prompt students to investigate a model that displays historical heat wave frequency data to discover the importance of defining terms when interpreting data.

Students will analyze how surface (skin) temperatures vary across a community and determine what factors contribute to this variation. Students will describe how human activity can affect the local environment. 

Students will analyze a line graph that shows how the surface temperature and air temperature values change over the course of 24 hours.

After learning about the different characteristics of satellite data, students will describe the advantages and disadvantages of using two different satellites to study the Urban Heat Island Effect.  

Students analyze Landsat images of Atlanta, Georgia to explore the relationship between surface temperature and vegetation.

Students analyze and compare satellite data of Ocean Chlorophyll Concentrations with Sea Surface Temperatures, beginning with the North Atlantic region, while answering questions about the global patterns of these phenomenon.

Students will use coloring sheets to create a color coded model of El Niño and analyze it. If the Data Literacy Map Cube is used with this, students will color their models first.

Students will identify and describe the relationship between land cover classification and surface temperature as they relate to the urban heat island effect. Students will also describe patterns between population density and the locations of urban heat islands.