This activity is one of a series in the collection, The Potential Consequences of Climate Variability and Change activities. 

Students review Earth System phenomena that are affected by soil moisture.  They analyze and evaluate maps of seasonal global surface air temperature and soil moisture data from NASA satellites. Building from their observations, students will select a location in the U.S.

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

In this activity, students explore three indicators of drought are: soil moisture, lack of precipitation, and decreased streamflows. Students investigate each of these parameters develop a sense for the effects of drought on land.

This learning activity uses data acquired by the TOPEX/Poseidon altimeter, a joint project of NASA and the French Space Agency, to investigate the relationship between the topography of a sea-floor feature and the topography of the overlying sea surface.

Helping students build their understanding of Earth's spheres and how they are connected is difficult.  Review the graphics to help identify the parts of the Earth System and the processes that connect them at the local, regional, and global scales.

In this mini-lesson, students analyze soil moisture quantities associated with Hurricane Harvey around Houston, Texas on August 25, 2017.

The ocean's surface is not level, and sea levels change in response to changes in chemistry and temperature. Sophisticated satellite measurements are required for scientists to document current sea level rise.

In this activity, students will use sea-level rise data to create models and compare short-term trends to long-term trends. They will then determine whether sea-level rise is occurring based on the data.

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.