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.

Students will practice the process of making claims, collecting evidence to support claims, and applying scientific reasoning to connect evidence to claims.

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.

In this activity, students investigate three different soil samples with varying moisture content. They use a soil moisture probe to determine the percentage (by volume) of water in each of the soil samples.

Students analyze four data visualizations focused on the topic of sea level.  They use a jigsaw method to explore and communicate their findings to their peers.

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.

Students will examine a 2014-2015 El Niño Southern Oscillation (ENSO) event to identify relationships among sea surface height, sea surface temperature, precipitation, and wind vectors.

In this activity students will compare different methods for observing the Sun’s corona and make predictions about what they will observe during the April 8, 2024 total solar eclipse.

Students use scale to determine the area of volcanic deposits following the March 3, 2015 eruption of Chile's Mount Villarrica stratovolcano, one of the country's most active volcanoes.

The purpose of this lesson is for students to compare data displays to determine which best answers the driving question. To do this they will evaluate the spread of the data and what the displays show.