Students observe the map image, individually, looking for changes in surface air temperatures (using data displayed, unit of measure, range of values, etc.) and noticeable patterns.

By investigating the data presented in a model that displays extreme summer air temperatures, students explain energy transfer in the Earth system and consider the impact of excessive heat on local communities.

Students watch a short video to gather information about sources of methane emissions and then extend their understanding of these sources to evaluate monthly trends in the Alaska region, ultimately making connections to Earth’s energy budget.

This mini lesson focuses on the 2015-2016 El Niño event and how its weather conditions triggered regional disease outbreaks throughout the world. Students will review a NASA article and watch the associated video to use as a tool to compare with maps related to 2015-2016 rainfall and elevated disease risk, and answer the questions.

Students review a video that models the global impact of smoke from fires to develop an understanding of how models can be used to interpret and forecast phenomena in the Earth System. 

Students move through a series of short activities to explore and evaluate global solar radiation data from NASA satellites.  In this process, students make qualitative and quantitative observations about seasonal variations in net energy input to the Earth System.

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

Using various visualizations (i.e., images, charts, and graphs), students will explore changes in sea ice extent as it relates to other spheres within the Earth System. This StoryMap is intended to be used with students who have access to the internet in a 1:1 or 1:2 setting.

Students analyze a graph that illustrates the change in global surface temperature relative to 1951-1980 average temperatures.

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.