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

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. 

NASA visualizers take data – numbers, codes – and turn them into animations people can see and quickly understand.

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 will use coloring sheets to create a color coded model of El Niño, then make comparisons using the actual model by answering questions. 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. 

Students will make a claim about whether changing albedo contributes to changes in Arctic habitats.

This mini lesson focuses on Landsat satellite data and how it is used to detect changes in land use. Students will answer questions based off of a NASA Video that features how Landsat data are interpreted in the forests of the Pacific Northwest, and gives examples of the effects insects and logging have with land management.

Students will analyze and interpret graphs to compare the flow of (shortwave) energy from the Sun toward China over the course of a year on cloudy versus clear days. Students will draw a conclusion and support it with evidence.