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

Teachers, are you looking for resources to help you engage students in data analysis related to Global Phytoplankton Distribution?

Check out the monthly 2018 images featuring two science variables related to Phytoplankton Distribution: Chlorophyll Concentration (milligrams per cubic meter)  & Monthly Flow of Energy into Surface by Shortwave Radiation (watts per square meter)

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

Students will analyze a pie chart (circle graph) showing the distribution of different parts of the Earth system's absorption and reflection of energy. 

Students will examine how radiation, conduction, and convection work together as a part of Earth’s Energy Budget to heat the atmosphere.

Students will investigate the role of clouds and their contribution (if any) to global warming. Working in cooperative groups, students will make a claim about the future role clouds will play in Earth’s Energy Budget if temperatures continue to increase.

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.

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

The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.