By matching pie charts with dates between 2002 and 2020, students will predict how air quality has changed over the past two decades. They will then use color-coded Air Quality Index signatures to assess the accuracy of their predictions.

Students will identify and describe the relationship between land cover classification and surface temperature as they relate to the urban heat island effect. Students will also describe patterns between population density and the locations of urban heat islands. 

In this lesson, students will explore the effect of aerosols on sky color and visibility by using an interactive virtual model. 

Students will describe how the spread of COVID-19 is affected by population density and explain why patterns in the spread of COVID-19 are happening over time. 

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 analyze a line graph that shows how the surface temperature and air temperature values change over the course of 24 hours.

In this activity, learners predict the likelihood of aurora on Earth by examining the Kp-index and using NOAA’s 30-minute aurora forecast.

Students review different maps of wind trajectories to determine to origins of mud-laden rain in the Pacific Northwest.

Hands-on demonstration of the El Niño Effect, trade winds, and upwelling provided by NASA's Jet Propulsion Lab.