This activity develops students' understanding of climate by having them make in-depth examinations of historical climate patterns using both graphical and map image formats rather than presenting a general definition of climate. Students explore local climate in order to inform a pen pal what type of weather to expect during an upcoming visit. Students generate and explore a variety of graphs, charts, and map images and interpret them to develop an understanding of climate.

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.

This hands-on activity demonstrates and explains the reasons for the seasons caused by the tilt of Earth on its axis as it orbits around the sun.

This activity from NOAA Earth System Research Laboratory introduces students to the scientific understanding of the greenhouse effect and the carbon cycle. The activity leads them through several interactive tasks to investigate recent trends in atmospheric carbon dioxide. Students analyze scientific data and use scientific reasoning to determine the causes responsible for these recent trends. By studying carbon cycle science in a visual and interactive manner, students can learn firsthand about the reasons behind our changing climate.

In this Webquest activity, students assume roles of scientist, business leader, or policy maker. The students then collaborate as part of a climate action team and learn how society and the environment might be impacted by global warming. They explore the decision making process regarding issues of climate change, energy use, and available policy options. Student teams investigate how and why climate is changing and how humans may have contributed to these changes. Upon completion of their individual tasks, student teams present their findings and make recommendations that address the situation.

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 model of ocean-atmosphere interaction shows how carbon dioxide gas diffuses into water, causing the water to become more acidic. The video demonstration and instruction provide an explanation of the chemistry behind this change and the consequences of ocean acidification. The video also addresses a misconception about how ocean acidification affects shelled organisms.

In this activity, students explore the way that human activities have changed the way that carbon is distributed in Earth's atmosphere, lithosphere, biosphere and hydrosphere.

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 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.

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