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.

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.

Students construct explanations about Earth’s energy budget by connecting a model with observations from side-by-side animations of the monthly mapped data showing incoming and outgoing shortwave radiation from Earth’s surface.

Students watch a NOVA PBS video about the different effects of clouds on climate and Earth's energy budget. Then they answer questions and brainstorm to complete a flow chart of events that might occur if the percentage of absorbing clouds increases.

Students will watch and examine a NASA animation of Earth’s rising surface temperatures over an almost 150 year period.

In this mini lesson, students analyze a bar graph showing the relative forcings from natural and human factors that affect Earth's climate. They use information from this graph to assess the relative importance of these factors.

Dr. Norman Loeb, an atmospheric scientist at NASA’s Langley Research Center in Hampton, Virginia, is the principal investigator for an experiment called the Clouds and the Earth’s Radiant Energy System (CERES). CERES instruments measure how much of the sun’s energy is reflected back to space and how much thermal energy is emitted by Earth to space.

My NASA Data has recently released several new resources, StoryMaps, for use in educational settings.

Use the Earth System Data Explorer to analyze data and make a claim about which 2018 eruption was larger, Kilauea, HI or Ambae Island, Vanuatu.

Students will engage in a “Zoom In Inquiry” learning routine to understand a world map that shows changes in PM_2.5-attributable mortality per 100,000 population (Bondie, 2013).