In this activity, students explore three indicators of drought are: soil moisture, lack of precipitation, and decreased streamflows. Students investigate each of these parameters develop a sense for the effects of drought on land.
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This series of videos highlights how NASA Climate Scientists use mathematics to solve everyday problems. These educational videos to illustrate how math is used in satellite data analysis.
The purpose of this activity is for students to create a desktop soil profile based on the biome region of the United States where your school is located.
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.
In this mini lesson, students use in-water profiles of historical ocean data to analyze how sea surface salinity varies with depth.
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.
Students observe seasonal images of Monthly Normalized Difference Vegetation, looking for any changes in vegetation that are occurring throughout the year. They put the images in order based on what they know about seasonal changes.
Students watch a video and answer questions on Dr. Patrick Taylor (Atmospheric Scientist, NASA Langley Research Center) as he discusses the study of clouds and Earth's energy budget by analyzing data from Low Earth Orbit satellites.
This Lesson Plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cubes. Because it is a differentiated resource, this Lesson Plan is appropriate for multiple grade bands.
Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.