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 identify patterns in chlorophyll concentration data to formulate their explanations of phytoplankton distribution. 

This mini lesson engages students by watching a NASA video related to seasonal chlorophyll concentration as it relates to net radiation using NASA's Aqua satellite. Students will examine the model and answer the questions.

Students review the NASA video showing biosphere data over the North Atlantic Ocean as a time series animation displaying a decade of phytoplankton blooms and answer questions.

Students will explore the Nitrogen Cycle by modeling the movement of a nitrogen atom as it passes through the cycle. Students will stop in the different reservoirs along the way, answering questions about the processes that brought them to the different reservoirs.  

This lesson was based on an activity from UCAR Center for Science Education. 

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.

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.

Environmental engineers use the basis of engineering, soil science, biology, and chemistry to develop solutions to problems in the environment. Some of their efforts involve recycling, waste disposal, public health, water and air pollution control. Many are engaged in solving practical, yet global issues such as unsafe drinking water, climate change, and environmental sustainability.

Remote sensing scientists use sensors to analyze data and solve regional, national and global concerns. For instance, natural resource management, urban planning, and climate and weather prediction are applications of remote sensing. Many scientists develop new sensor systems, analytical techniques, or new applications for existing systems. 

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.