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.
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Students will analyze and interpret maps of the average net atmospheric radiation to compare the flow of energy from the Sun toward Earth in different months and for cloudy versus clear days. Students will draw conclusions and support them with evidence.
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 review a video showing a global view of the top-of-atmosphere shortwave radiation from January 26 and 27, 2012 and answer the questions that follow.
This story map allows students to explore the urban heat island effect using land surface temperature and vegetation data in a 5 E-learning cycle. Students investigate the processes that create differences in surface temperatures, as well as how human activities have led to the creation of urban heat islands.
Students interpret a graph of surface temperatures taken from city districts and other types of communities.
This Lesson Plan provides maps, graphs, and data tables for use with the Data Literacy Cubes. Because it is a differentiated resource, it is appropriate for multiple grade bands.
This unit plan is published by the NASA Climate Change Research Initiative's (CCRI) Applied Research STEM Curriculum Portfolio. The CCRI Unit Plan, called “Urban Surface Temperatures and the Urban Heat Island Effects,“ has the purpose to educate students how climate is changi
Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year. Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S
Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.