Students develop and test a hypothesis about how albedo affects temperature.
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These six graphs show Ocean Chlorophyll Concentrations from 1998 - 2018 in a variety of locations: East Bering Sea, Gulf of Alaska, California Coast, Southeastern US/Gulf of Mexico, Northeastern US and the Scotian Shelf, and the Hawaiian Islands.
Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.
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 will observe monthly satellite data of the North Atlantic to identify relationships among key science variables that include sea surface salinity (SS), air temperature at the ocean surface (AT), sea surface temperature (ST), evaporation (EV), precipitation (PT), and evaporation minus pre
Students collect and analyze temperature data to explore what governs how much energy is reflected.
Use the Data Literacy Cubes to guide students’ exploration of data to enrich their observations and inferences. This is a flexible resource that may be used with a variety of graphical representations of data. This activity requires a graph for students to evaluate.
This lesson, "Awenasa Goes to Camp!," is a data analysis activity that presents maps of NASA Earth satellite data for a variety of locations
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.
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.