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.
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Students observe the map image, individually, looking for changes in surface air temperatures (using data displayed, unit of measure, range of values, etc.) and noticeable patterns.
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.
Students review a video that models the global impact of smoke from fires to develop an understanding of how models can be used to interpret and forecast phenomena in the Earth System.
This mini lesson provides a video on an ultra-high-resolution NASA computer model of how carbon dioxide in the atmosphere travels around the globe. Students will review the video and answer the following questions.
Students watch a short video to gather information about sources of methane emissions and then extend their understanding of these sources to evaluate monthly trends in the Alaska region, ultimately making connections to Earth’s energy budget.
Compare a histogram and map to determine the differences in the information conveyed in each data display.
Learners will analyze and interpret a box plot and evaluate the spread of the data. Learners will compare it with a different visualization of the data to see how the two compare, discuss the limitations of the two types of data displays and formulate questions.
Interpret a scatter plot to find patterns in the number of tropical cyclones from 1842 to 2018.