In this activity, students examine climate variability in the North Atlantic associated with the North Atlantic Oscillation (NOA) in a case study format.

Students explore the increase in atmospheric carbon dioxide over the past 40 years with an interactive online model. They use the model and observations to estimate present emission rates and emission growth rates. The model is then used to estimate future levels of carbon dioxide using different future emission scenarios. These different scenarios are then linked by students to climate model predictions also used by the Intergovernmental Panel on Climate Change.

This resource is a website that is a self-contained, multi-part introduction to how climate models work. The materials include videos and animations about understanding, constructing and applying climate models.

This is a multi-step activity that helps students measure, investigate, and understand the increase in atmospheric CO2 and the utility of carbon offsets. It also enables students to understand that carbon offsets, through reforestation, are not sufficient to balance increases in atmospheric C02 concentration.

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 use authentic Arctic climate data to unravel some causes and effects related to the seasonal melting of the snowpack and to further understand albedo.

In this activity, students are guided through graphs of surface air temperature anomaly data and Vostok ice core data to illustrate how scientists use these data to develop the basis for modeling how climate is likely to change in the future.

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 Likelihood Scale and apply it to their statistical results.

In this series of activities students investigate the effects of black carbon on snow and ice melt in the Arctic. The lesson begins with an activity that introduces students to the concept of thermal energy and how light and dark surfaces reflect and absorb radiant energy differently. To help quantify the relationship between carbon
and ice melt, the wet lab activity has students create ice samples both with and without black carbon and then compare how they respond to radiant energy while considering implications for the Arctic.

This activity involves plotting and comparing monthly data on atmospheric C02 concentrations over two years, as recorded in Mauna Loa and the South Pole, and postulating reasons for differences in their seasonal patterns. Longer-term data is then examined for both sites to see if seasonal variations from one site to the other carry over into longer term trends.

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