Use the Data Literacy Cube to guide students’ exploration of data to enrich their observations and inferences.  This is a flexible resource that may be used with a variety of graphical representations of data.  This activity requires a graph for students to evaluate.   Fo

Students can interact with NASA data to build a custom visualizations of local, regional, or global plant growth patterns over time, using the Earth System Data Explorer to generate plots of satellite data as they develop models of this phenomenon.

This mini lesson engages students by watching a NASA video related to plant growth activity around the world using data from the NASA/NOAA Suomi NPP satellite and answering questions on these stability and change relationships.

The purpose of this activity is for students to create a desktop soil profile based on the biome region of the United States where your school is located.

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

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.

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.

Students will investigate the role of clouds and their contribution (if any) to global warming. Working in cooperative groups, students will make a claim about the future role clouds will play in Earth’s Energy Budget if temperatures continue to increase.

Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.

Students differentiate between data sets of monthly shortwave radiation and monthly cloud coverage to discover a relationship between radiation and clouds by answering analysis questions.