Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.
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Students consider the impact of changing conditions on the remote island of Little Diomede, Alaska after they investigate the relationship between seasonal trends in sea ice extent with shortwave and longwave radiation flux described in Earth’s energy budget.
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 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.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner determine relationships among variables.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, identify patterns, and determine relationships among two variables in three months.
Students will examine a 2014-2015 El Niño Southern Oscillation (ENSO) event to identify relationships among sea surface height, sea surface temperature, precipitation, and wind vectors.
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.
This lesson plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cube. Because it is a differentiated resource, this lesson plan is appropriate for multiple grade bands.
This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.