This activity invites students to model and observe the effect of melting ice sheets (from land) on sea level and the difference between the effect of melting sea-ice to that of melting land ice on sea level.

Arctic sea ice is the cap of frozen seawater blanketing most of the Arctic Ocean and neighboring seas in wintertime. It follows seasonal patterns of thickening and melting. Students view how the quantity has changed from 1979 through 2018. 

This graphic organizer may be used to help students analyze the processes and components of Earth System phenomena.

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.

In this lesson, students will investigate the drivers of climate change, including adding carbon dioxide and other greenhouse gases to the atmosphere, sea level rise, and the effect of decreasing sea ice on temperatures.

Students watch the video Frozen Earth and answer the following questions that discuss how ice helps moderate the planet's temperature using NASA satellites.

This video provides tips for teachers on helping students make sense of data to help them understand and work with data. It is based on the work of Kristin Hunter-Thomson of Dataspire.org and uses data from the My NASA Data Earth System Data Explorer.

Students explore the spatial patterns observed in meteorological data and learn how this information is used to predict weather and understand climate behavior.

In this activity, students use satellite images from the NASA Landsat team to quantify changes in glacier cover over time from 1986 to 2018. 

Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.