Students are introduced to the Earthrise phenomenon by seeing the Earth as the Apollo 8 astronauts viewed our home planet for the first time from the Moon.  They will analyze a time series of mapped plots of Earth science variables that NASA monitors to better understand the Earth

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

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.

This mini lesson engages students in writing a commentary for a NASA video regarding changes in global temperatures from 1880 to 2017. 

Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.

Students use albedo values of common surfaces along with photographic images of Earth taken from the International Space Station to make an argument about specific anthropogenic activities that impact Earth’s albedo.

Students review a video showing how the ocean is warmed by solar energy. This is the first video of a four-part series on the water cycle, which follows the journey of water from the ocean to the atmosphere, to the land, and back again to the ocean.

This activity introduces students to aspects of the atmosphere, biosphere, hydrosphere, and litho/geosphere and how they are interrelated. It is designed to promote an interest in authentic investigations of Earth using images acquired by astronauts as the hook.

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.