This investigation is part of the NASA: Mission Geography Module "What are the causes and consequences of climate change?" that guides students through explorations in climatic variability and evidence for global climate change.
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In this experiment, students make a claim about the cause of ocean currents and then develop a model to explain the role of salinity and density in deep ocean currents. This lesson is modified from "Visit to an Ocean Planet" Caltech and NASA/Jet Propulsion Laboratory.
Use the Earth System Data Explorer to analyze data and make a claim about which 2018 eruption was larger, Kilauea, HI or Ambae Island, Vanuatu.
Watch NASA videos about aerosols and volcanic ash.
Students will engage in a collaborative learning routine as they explore slides that show how the development of public transportation infrastructure changed the land in Woodlawn, Maryland. They will make observations of a satellite image and a photo from the ground as well as read background information on the impact of urbanization.
Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.
These resources are intended to be used with teachers and students to help model how to apply data literacy skills to analyzing patterns as they relate to stability and change in COVID-19 (and related human geographic) and nitrogen dioxide data.
Are you looking for a data story to use with your students that demonstrates the interaction of the geosphere and atmosphere in the form of volcanic eruptions? Consider using the following resources in your classroom today!
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.
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.