This story map lesson plan allows students to explore ocean circulation patterns as they relate to the world's ocean garbage patches using NASA ocean currents data. Students will investigate the forces that contribute to ocean circulation patterns, and how debris, especially plastics, travel from land to the garbage patches.
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This lesson, "Awenasa Goes to Camp!," is a data analysis activity that presents maps of NASA Earth satellite data for a variety of locations across the United States for four unidentified months throughout the year. Each location represents a real science camp th
Arctic sea ice is the cap of frozen seawater blanketing most of the Arctic Ocean and neighboring seas in wintertime. It follows seasonal patterns of thickening and melting. Students view how the quantity has changed from 1979 through 2018.
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
The activities in this guide will help students understand variations in environmental parameters by examining connections among different phenomena measured on local, regional and global scales.
Air, Water, Land, & Life: A Global Perspective
This NASA visualization shows sea surface salinity observations (September 2011-September 2014). Students review the video and answer questions.
Students review a video showing how the ocean is warmed by solar energy. This is the first video of a four-part series on the water cycle, which follows the journey of water from the ocean to the atmosphere, to the land, and back again to the ocean.
The El Niño Implementation Sequence provides a series of lessons and activities for students to learn about a condition that sometimes occurs in the Pacific Ocean, but it is so big that it affects weather all over the world.
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.