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.
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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
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.
In this activity, students will compare the methods scientists use to study the Sun, including drawings made during a total solar eclipse in the 1860’s, modern coronagraphs, and advanced imagery gathered by NASA’s Solar Dynamics Observatory.
Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.
Students learn how to estimate the "energy efficiency" of photosynthesis, or the amount of energy that plants absorb for any given location on Earth. This is the ratio of the amount of energy stored to the amount of light energy absorbed and is used to evaluate and model photosynthesis efficiency.
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.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner determine relationships among variables.