This mini lesson engages students with answering questions on cause and effect relationships by watching a NASA video related to changing forests in the Pacific Northwest from 1984 to 2011.
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The Great Smoky Mountains have a unique climate and weather pattern. Students will review a Landsat image and read about the history of the area and why Native Americans called the area “Shaconage.” Then they will answer the questions about what caused the unusual “blue smoke.”
Using hourly graphs of PM 2.5 data and HYSPLIT model trajectories, students will collect evidence for the effects of fireworks on air quality.
Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.
Students observe how air quality changes over time, for a selected location, using data from the United States Environmental Protection Agency (EPA).
This mini lesson focuses on Earth's Energy Budget and the surface effects that occur in Central Australia. Students review a line graph depicting net radiation in Central Australia related to a multiyear drought from 2002 - 2009 and answer the questions.
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.
By investigating the data presented in a model that displays extreme summer air temperatures, students explain energy transfer in the Earth system and consider the impact of excessive heat on local communities.
Students analyze the data and details of a complicated graph by identifying components and data patterns.
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.