This long classroom activity introduces students to a climate modeling software. Students visualize how temperature and snow coverage might change over the next 100 years. They run a 'climate simulation' to establish a baseline for comparison, do a 'experimental' simulation and compare the results. Students will then choose a region of their own interest to explore and compare the results with those documented in the IPCC impact reports. Students will gain a greater understanding and appreciation of the process and power of climate modeling.

In this activity students work with real datasets to investigate a real situation regarding disappearing Arctic sea ice. The case study has students working side-by-side with a scientist from the National Snow and Ice Data Center and an Inuit community in Manitoba.

In this activity, students create graphs of real temperature data to analyze climate trends by analyzing the global temperature record from 1867 to the present. Long-term trends and shorter-term fluctuations are both evaluated. The data is examined for evidence of the impact of natural and anthropogenic climate forcing mechanisms on the global surface temperature variability. Students are prompted to determine the difficulties scientists face in using this data to make climate predictions.

In this intermediate Excel activity, students import US Historical Climate Network mean temperature data into Excel from a station of their choice. They are then guided through the activity on how to use Excel for statistical calculations, graphing, and linear trend estimates. The activity assumes some familiarity with Excel and graphing in Excel.

This activity introduces students to global climate patterns by having each student collect information about the climate in a particular region of the globe. After collecting information, students share data through posters in class and consider factors that lead to differences in climate in different parts of the world. Finally, students synthesize the information to see how climate varies around the world.

This lesson explores El Nino 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 Nino from 1997 to 1998. In this way, students will model the methods of researchers who bring their expertise to study integrated science questions.

Students use the GLOBE Student Data Archive and visualizations to display current temperatures on a map of the world. They explore the patterns in the temperature map, looking especially for differences between different regions and hemispheres and zoom in for a closer look at a region that has a high density of student reporting stations (such as the US and Europe). Students compare and contrast the patterns in these maps, looking for seasonal patterns.

Students consider why the observed atmospheric CO2 increase rate is only ~60% of the CO2 loading rate due to fossil fuel combustion. They develop a box-model to simulate the atmospheric CO2 increase during the industrial era and compare it to the historic observations of atmospheric CO2 concentrations. The model is then used to forecast future concentrations of atmospheric CO2 during the next century.

In this activity, students work in groups, plotting carbon dioxide concentrations over time on overheads and estimating the rate of change over five years. Stacked together, the overheads for the whole class show an increase on carbon dioxide over five years and annual variation driven by photosynthesis. This exercise enables students to practice basic quantitative skills and understand how important sampling intervals can be when studying changes over time. A goal is to see how small sample size may give incomplete picture of data.

In this activity, students explore how, in New England, the timing of color change and leaf drop of deciduous trees is changing.

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