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.

At the core of scientific visualization is the representation of data graphically - through images, animations, and videos - to improve understanding and develop insight. Data visualizers develop data-driven images, maps, and visualizations from information collected by Earth-observing satellites, airborne missions, and ground measurements. Visualizations allow us to explore data, phenomena and behavior; they are particularly effective for showing large scales of time and space, and "invisible" processes (e.g. flows of energy and matter) as integral parts of the models.

A model analyst develops models to help visualize, observe, and predict complicated data. Model analysis is the process of taking large amounts of data and separate it into a structure that makes it intelligible to the binary process of computers. An analyst also manages the flow of information between different user groups through the use of relational databases.

Oceanography covers a wide range of topics, including marine life and ecosystems, ocean circulation, plate tectonics and the geology of the seafloor, and the chemical and physical properties of the ocean.

My NASA Data has recently released several new resources, StoryMaps, for use in educational settings.

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

In this lesson, students investigate and identify various phytoplankton using images that were previously taken with a compound microscope.  Credit:  This lesson is modified from a lesson of the same name created by The Center for Microbial Oceanography: Research and Education&nbsp