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

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 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. 

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.

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

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.

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.