Students will observe monthly satellite data of the North Atlantic to identify relationships among key science variables that include sea surface salinity (SS), air temperature at the ocean surface (AT), sea surface temperature (ST), evaporation (EV), precipitation (PT), and evaporation minus pre

Students identify and classify kinds of land cover (such as vegetation, urban areas, water, and bare soil) in Landsat satellite images of Phoenix, Arizona taken in 1984 and 2018.

Students observe seasonal images of Monthly Normalized Difference Vegetation, looking for any changes in vegetation that are occurring throughout the year. They put the images in order based on what they know about seasonal changes.

This story map allows students to explore the formation and impacts of ash and aerosols from volcanic eruptions around the world in a 5 E-learning cycle. They will investigate how ash and aerosols produced from volcanic eruptions are hazardous to the human ecosystem, and will analyze concentrations of aerosols from a volcanic eruption over time. 

Students analyze four data visualizations focused on the topic of sea level.  They use a jigsaw method to explore and communicate their findings to their peers.

This unit plan is published by the NASA Climate Change Research Initiative's (CCRI) Applied Research STEM Curriculum Portfolio.  The CCRI Unit Plan, called “Urban Surface Temperatures and the Urban Heat Island Effects,“ has the purpose to educate students how climate is changing in urban settings

Students will explore the relationship between Nitrogen Dioxide and Precipitation in Earth's atmosphere. They will explore the data provided, make a claim, and complete a slide guided by a rubric.

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

Students construct explanations about Earth’s energy budget by connecting a model with observations from side-by-side animat

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.