This NASA visualization shows sea surface salinity observations (September 2011-September 2014). Students review the video and answer questions.

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.

This StoryMap lesson plan allows students to explore ocean circulation patterns as they relate to the world's ocean garbage patches using NASA ocean currents data. Students will investigate the forces that contribute to ocean circulation patterns, and how debris, especially plastics, travel from land to the garbage patches. 

Exploring salinity patterns is a great way to better understand the relationships between the water cycle, ocean circulation, and climate. In this mini lesson, students analyze sea surface salinity mapped plots created from the Earth System Data Explorer, paired with questions (and answers) from the Aquarius Mission. Credit: Aquarius Education

Students identify patterns and describe the relationship between chlorophyll concentration and incoming shortwave radiation. 

The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, identify patterns, and determine relationships among two variables in three months.

Students will analyze a graph showing the amounts of peak energy received at local noon each day over the year changes with different latitudes. 

Students will analyze a graph showing the variation of energy imbalance on Earth over the year along different latitudinal zones and answer the questions that follow.

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

The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.