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 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.
This Earth Exploration Toolbook chapter uses ArcGIS and climate data from the National Center for Atmospheric Research (NCAR) Climate Change Scenarios GIS Data Portal to help users learn the basics of GIS-based climate modeling. The five-part exercise involves calculating summer average temperatures for the present day and future climate modeled output, visually comparing the temperature differences for the two model runs, and creating a temperature anomaly map to highlight air temperature increases or decreases around the world.
A detailed Google Earth tour of glacier change over the last 50 years is given in class as an introduction. Students are then asked to select from a group of glaciers and create their own Google Earth tour exploring key characteristics and evident changes in that glacier.
In this activity, students compare carbon dioxide (CO2) data from Mauna Loa Observatory, Barrow (Alaska), and the South Pole over the past 40 years to help them better understand what controls atmospheric carbon dioxide. This activity makes extensive use of Excel.
In this activity, students explore what types of energy resources exist in their state by examining a state map to identify the different energy sources in their state, including the state's renewable energy potential.
This teaching activity addresses regional variability as predicted in climate change models for the next century. Using real climatological data from climate models, students will obtain annual predictions for minimum temperature, maximum temperature, precipitation, and solar radiation for Minnesota and California to explore this regional variability. Students import the data into a spreadsheet application and analyze it to interpret regional differences. Finally, students download data for their state and compare them with other states to answer a series of questions about regional differences in climate change.
In this activity for undergraduate students, learners build a highly simplified computer model of thermohaline circulation (THC) in the North Atlantic Ocean and conduct a set of simulation experiments to understand the complex dynamics inherent in this simple model.
In this exercise learners use statistics (T-test using Excel) to analyze an authentic dataset from Lake Mendota in Madison, WI that spans the last 150 years to explore ice on/ice off dates. In addition, students are asked to investigate the IPCC Likelihoodscale and apply it to their statistical results.