This activity will help students better understand and practice estimating percent cloud cover.

This activity was developed by NASA's Global Precipitation Measurement (GPM) team as an introductory experience to a series of lessons about water resources on Earth.

This lesson is taken from NASA's Phytopia: Discovery of the Marine Ecosystem written in partnership with Bigelow Laboratory for Ocean Science with funding from the National Science Foundation.

Learners will analyze space-weather data from the National Oceanic and Atmospheric Administration (NOAA). Learners will compare two different types of data: sunspot data and measurements from magnetometers on Earth.

Students watch a short video to gather information about sources of methane emissions and then extend their understanding of these sources to evaluate monthly trends in the Alaska region, ultimately making connections to Earth’s energy budget.

In this mini-lesson, students analyze soil moisture quantities associated with Hurricane Harvey around Houston, Texas on August 25, 2017.

This StoryMap lesson plan allows students to explore global phytoplankton distribution using chlorophyll concentration data in a 5 E-learning cycle. Students will investigate the processes that allow phytoplankton populations to thrive, as well as how their role in the carbon cycle impacts the other spheres of the Earth System. 

Carbon dioxide concentration in the atmosphere is affected by many processes including fires, deforestation, and plant respiration. Students will evaluate a Landsat image to determine the rate of carbon dioxide sequestration in a particular area.

Using a “fun-size” bag of rainbow bite-sized candies learners will place different colored candies on a diagram of the Sun-Earth system to show different space weather conditions during solar minimum and solar maximum.

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.