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. 

Learn about the different cloud types and their names. Match cloud photos and names by cloud type and for all types. Evaluate the types of clouds represented in various data displays.

The extreme temperatures during July 2022 prompt students to investigate a model that displays historical heat wave frequency data to discover the importance of defining terms when interpreting data.

Guided by the 5E model, this lesson allows students to work together to uncover how changes in sea ice extent in the Arctic and Antarctic regions are connected to Earth’s energy budget.

Students review a video showing a global view of the top-of-atmosphere shortwave radiation from January 26 and 27, 2012 and answer the questions that follow.

In this lesson, students investigate and identify various phytoplankton using images that were previously taken with a compound microscope.  Credit:  This lesson is modified from a lesson of the same name created by The Center for Microbial Oceanography: Research and Education&nbsp

Students analyze Landsat images of Atlanta, Georgia to explore the relationship between surface temperature and vegetation.

Students consider the impact of changing conditions on the remote island of Little Diomede, Alaska after they investigate the relationship between seasonal trends in sea ice extent with shortwave and longwave radiation flux described in Earth’s energy budget.

Scientific data are often represented by assigning ranges of numbers to specific colors. The colors are then used to make false color images which allow us to see patterns more easily. Students will make a false-color image using a set of numbers.

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.