This activity engages learners to investigate the impact of Earth's tilt and the angle of solar insolation as the reason for seasons by doing a series of hands-on activities that include scale models. Students plot the path of the Sun's apparent movement across the sky on two days separated by three months of time.
In this activity, students review techniques used by scientists as they analyze a 50-year temperature time series dataset. The exercise helps students understand that data typically has considerable variability from year to year and to predict trends, one needs to consider long-term 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 NiÃo and La NiÃa 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 activity focuses on reconstructing the Paleocene-Eocene Thermal Maximum (PETM) as an example of a relatively abrupt global warming period. Students access Integrated Ocean Drilling Program (IODP) sediment core data with Virtual Ocean software in order to display relevant marine sediments and their biostratigraphy.
This activity uses geophysical and geochemical data to determine climate in Central America during the recent past and to explore the link between climate (wet periods and drought) and population growth/demise among the Maya. Students use ocean drilling data to interpret climate and to consider the influence of climate on the Mayan civilization.
In this lesson, students examine and interpret varied observational datasets and are asked to determine whether the data supports or does not support the statement: climate change is occurring in Colorado.
This lesson explores El NiÃo by looking at sea surface temperature, sea surface height, and wind vectors in order to seek out any correlations there may be among these three variables using the My NASA Data Live Access Server. The lesson guides the students through data representing the strong El NiÃo from 1997 to 1998. In this way, students will model the methods of researchers who bring their expertise to study integrated science questions.
This activity engages learners in examining data pertaining to the disappearing glaciers in Glacier National Park. After calculating percentage change of the number of glaciers from 1850 (150) to 1968 (50) and 2009 (26), students move on to the main glacier-monitoring content of the module--area vs. time data for the Grinnell Glacier, one of 26 glaciers that remain in the park. Using a second-order polynomial (quadratic function) fitted to the data, they extrapolate to estimate when there will be no Grinnell Glacier remaining (illustrating the relevance of the question mark in the title of the module).
This is a classroom activity about the forcing mechanisms for the most recent cold period: the Little Ice Age (1350-1850). Students receive data about tree ring records, solar activity, and volcanic eruptions during this time period. By comparing and contrasting time intervals when tree growth was at a minimum, solar activity was low, and major volcanic eruptions occurred, they draw conclusions about possible natural causes of climate change and identify factors that may indicate climate change.
For this lesson, the guiding Concept Question is: What is climate change and how does climate relate to greenhouse gas concentrations over time? This activity is the second lesson in a nine-lesson module 'Visualizing and Understanding the Science of Climate Change' produced by the International Year of Chemistry project (2011).