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

In this mini lesson, students explore the relationship of chlorophyll and solar radiation by analyzing line graphs from the North Atlantic during 2016-2018.

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.

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.

Examine (daytime) surface temperature and solar radiation received at locations found near similar latitudes using NASA Data.

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.

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

Students will examine air temperature data collected through The GLOBE Program during the 2017 US solar eclipse.

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.