With this simulation from the NASA Climate website, learners explore different examples of how ice is melting due to climate change in four places where large quantities of ice are found. The photo comparisons, graphs, animations, and especially the time lapse video clips of glaciers receding are astonishing and dramatic.
In this activity, students estimate the drop in sea level during glacial maxima, when ice and snow in high latitudes and altitudes resulted in lower sea levels. Students estimate the surface area of the world's oceans, use ice volume data to approximate how much sea levels dropped, and determine the sea-level rise that would occur if the remaining ice melted.
In this lesson, students complete a Myers-Briggs Type Inventory of their personality type as an introductory step to understanding what green jobs might suit their personal styles. From the information on this online tool, they look at different Green Jobs to explore possible careers.
In this video, students explore the work of Jay Keasling, a synthetic biologist experimenting with ways to produce a cleaner-burning fuel from biological matter, using genetically modified microorganisms.
In this activity for undergraduates, students explore the CLIMAP (Climate: Long-Range Investigation, Mapping and Prediction) model results for differences between the modern and the Last Glacial Maximum (LGM) and discover the how climate and vegetation may have changed in different regions of the Earth based on scientific data.
This short video is an excerpt from the longer video Acid Test: The Global Challenge of Ocean Acidification, produced by the National Resources Defense Council (NRDC). This short version summarizes the science of ocean acidification as well as the social implications.
This multi-part activity introduces users to normal seasonal sea surface temperature (SST) variation as well as extreme variation, as in the case of El NiÃo and La NiÃa events, in the equatorial Pacific Ocean. Via a THREDDS server, users learn how to download seasonal SST data for the years 1982 to 1998. Using a geographic information system (GIS), they visualize and analyze that data, looking for the tell-tale SST signature of El Nino and La Nina events that occurred during that time period. At the end, students analyze a season of their own choosing to determine if an El NiÃo or La NiÃa SST pattern emerged in that year's data.