Interpret the map, or model, to find patterns in the occurrence of tropical cyclones from 1842 through 2018.
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An urban heat island is a phenomenon that is best described when a city experiences much warmer temperatures than in nearby rural areas. The sun’s heat and light reach the city and the country in the same way. The difference in temperature between urban and less-developed rural areas has to do with how well the surfaces in each environment absorb and hold heat.
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 observe how air quality changes over time, for a selected location, using data from the United States Environmental Protection Agency (EPA).
Carbon dioxide concentration in the atmosphere is affected by many processes including fires, deforestation, and plant respiration. Students will evaluate a Landsat image to determine the rate of carbon dioxide sequestration in a particular area.
Students can interact with NASA data to build a custom visualizations of local, regional, or global plant growth patterns over time, using the Earth System Data Explorer to generate plots of satellite data as they develop models of this phenomenon.
Students analyze the data and details of a complicated graph by identifying components and data patterns.
This mini lesson focuses on the 2015-2016 El Niño event and how its weather conditions triggered regional disease outbreaks throughout the world. Students will review a NASA article and watch the associated video to use as a tool to compare with maps related to 2015-2016 rainfall and elevated disease risk, and answer the questions.
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.