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 analyze a graph that illustrates the change in global surface temperature relative to 1951-1980 average temperatures.

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 move through a series of short activities to explore and evaluate global solar radiation data from NASA satellites.  In this process, students make qualitative and quantitative observations about seasonal variations in net energy input to the Earth System.

Students review a visualization showing a global view of the top-of-atmosphere longwave radiation from January 26 and 27, 2012. They review the supporting text and analyze the data in the visualization to answer questions.

Students will examine a 2014-2015 El Niño Southern Oscillation (ENSO) event to identify relationships among sea surface height, sea surface temperature, precipitation, and wind vectors.

The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.  

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.

The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.  

In this activity, students will use sea-level rise data to create models and compare short-term trends to long-term trends. They will then determine whether sea-level rise is occurring based on the data.