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 Earth System phenomena that are affected by soil moisture.  They analyze and evaluate maps of seasonal global surface air temperature and soil moisture data from NASA satellites. Building from their observations, students will select a location in the U.S.

Learn about how Janine Pollack, an Environmental Engineer, got her start at NASA and the kinds of work she does as an engineer.

GLOBE protocols and learning activities that complement the Ocean Circulation Patterns phenomenon through hands-on investigations are detailed. These protocols can be used to build a basis for understanding the principles of salinity and water temperature which are drivers of the ocean circulation patterns.

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. 

Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year.  Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S

What is the hydrosphere and why is it important?

Students will describe how the spread of COVID-19 is affected by population density and explain why patterns in the spread of COVID-19 are happening over time. 

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.  

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.