Students will engage in a “Zoom In Inquiry” learning routine to understand a world map that shows changes in PM2.5-attributable mortality per 100,000 population (Bondie, 2013).
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The extreme temperatures during July 2022 prompt students to investigate a model that displays historical heat wave frequency data to discover the importance of defining terms when interpreting data.
This mini lesson engages students in watching a NASA video related to accumulated dust that makes the trans-Atlantic journey from the Sahara Desert to the Amazon rainforest using NASA's CALIPSO satellite. Students will examine a model and answer questions related to dust transport and the introduction of phosphorus to the soils of the Amazon.
Students analyze the stability and change of sea level after watching a visualization of sea level height around the world.
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.
The fires in Greece during the summer of 2007 devastated large tracks of forest and ground cover in this Mediterranean region. Students analyze these data to determine the scale, area, and percentage of the forest impacted by of these fires.
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.
Using an infographic, students describe differences in electromagnetic radiation that is part of a model of Earth’s energy budget by applying the defined terms of Shortwave Radiation and Longwave Radiation.
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.
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.