Earth is a system of systems.

In Earth System Science, underling factors affecting observable phenomena can be difficult to identify and describe.  The Iceberg Diagram diagram uses the metaphor of an iceberg to demonstrate the idea of visible vs hidden as it relates to Earth science phenomena.  This teaching strategy helps students to see beyond the obvious and to develop their awareness of the underlying causes, relationships, and/or conditions that can contribute to phenomenological events. It also provides a framework for digging deeper into phenomena-driven lessons in Earth Science.

Students will analyze the monthly seasonal chlorophyll concentration images in our global oceans for the four different months of 2024, and then answer the following questions.

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

Explore the biosphere and why it is important.

Students will analyze the mapped plot of the historic Ocean Chlorophyll Concentrations at key locations around the world for the period of 1998-2018.

Students analyze and compare satellite data of Ocean Chlorophyll Concentrations with Sea Surface Temperatures, beginning with the North Atlantic region, while answering questions about the global patterns of these phenomenon.

This resource helps to identify and access GLOBE protocols and hands-on learning activities that complement the Phytoplankton Distribution phenomenon.

The Quick Start Guide lists examples of NASA datasets and imagery that could be used for student investigations related to content and practices in the Framework for K-12 Science Education.    This Guide is part of an educator toolkit that features resources for grades K-12 that can support and frame student investigations with NASA data and content. Check out the toolkit and samplers for elementary, middle, and high school at https://www.strategies.org/education/educators-toolkit/.

This video addresses the following question: "We know that there are a number of ways that data can be visualized. Would you please describe your process for looking at the same data as represented by different graph types and how this helps inform your meaning making from the data?"