An urban heat island is a phenomenon that is best described when a city experiences much warmer temperatures than in nearby rural areas. The sun’s heat and light reach the city and the country in the same way. The difference in temperature between urban and less-developed rural areas has to do with how well the surfaces in each environment absorb and hold heat.
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Students analyze the stability and change of sea level after watching a visualization of sea level height around the world.
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 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 four data visualizations focused on the topic of sea level. They use a jigsaw method to explore and communicate their findings to their peers.
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 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.
For over 20 years, satellite instruments have measured the sea surface height of our ever-changing oceans. This video of images shows the complicated patterns of rising and falling ocean levels across the globe from 1993 to 2015.
This graphic organizer may be used to help students analyze the processes and components of Earth System phenomena.
The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.