In this interactive you will create space weather forecast maps for solar minimum and solar maximum.

Students will synthesize information from maps that show population, concentrations of PM_2.5, and PM_2.5-attributable mortality across the globe in order to draw conclusions about the relationship between particulate pollution and human health. 

Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.

The advance-and-retreat cycle of snow cover drastically changes the whiteness and brightness of Earth. Using two maps created using NASA satellite data for 2017, students review the seasonal differences of snow and ice extent and answer questions on their observations.

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 use coloring sheets to create a color coded model of El Niño and analyze it. If the Data Literacy Map Cube is used with this, students will color their models first.

Students will analyze a graph showing the amounts of peak energy received at local noon each day over the year changes with different latitudes. 

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

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.