Interpret the map, or model, to find patterns in the occurrence of tropical cyclones from 1842 through 2018.

This mini lesson engages students in watching a NASA video related to accumulated dust that makes the trans-Atlantic journey from the Sahara Desert to the Amazon rainforest using NASA's CALIPSO satellite. Students will examine a model and answer questions related to dust transport and the introduction of phosphorus to the soils of the Amazon.

By investigating the data presented in a model that displays extreme summer air temperatures, students explain energy transfer in the Earth system and consider the impact of excessive heat on local communities.

For over 20 years, satellite instruments have measured the sea surface height of our ever-changing oceans.  This video of images shows the complicated patterns of rising and falling ocean levels across the globe from 1993 to 2015.

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 will analyze the monthly seasonal chlorophyll concentration images in our global oceans for the four different months of 2024, and then answer the following questions.

Students review a visualization showing a global view of the top-of-atmosphere longwave radiation from January 26 and 27, 2012. They review the supporting text and analyze the data in the visualization to answer questions.

 Air, Water, Land, & Life: A Global Perspective

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.

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.