Earth is made up of five major parts or subsystems: the Atmosphere, Hydrosphere, Biosphere, Cryosphere, and Geosphere. Each major part is connected to the other parts in a complex web of processes.
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A kinesthetic activity that challenges students to participate in a model that describes the fate of solar energy as it enters the Earth system. A good initial lesson for Earth’s energy budget, students unravel the benefits and limitations of their model.
Students construct explanations about Earth’s energy budget by connecting a model with observations from side-by-side animations of the monthly mapped data showing incoming and outgoing shortwave radiation from Earth’s surface.
Students will examine how radiation, conduction, and convection work together as a part of Earth’s Energy Budget to heat the atmosphere.
Students will analyze and interpret graphs to compare the flow of (shortwave) energy from the Sun toward China over the course of a year on cloudy versus clear days. Students will draw a conclusion and support it with evidence.
Students move through a series of short activities to explore and evaluate global solar radiation data from NASA satellites. In this process, students make qualitative and quantitative observations about seasonal variations in net energy input to the Earth System.
My NASA Data has recently released several new resources, StoryMaps, for use in educational settings.
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.
Students will analyze a graph showing the amounts of peak energy received at local noon each day over the year changes with different latitudes.
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.