This classroom activity is aimed at an understanding of different ecosystems by understanding the influence of temperature and precipitation. Students correlate graphs of vegetation vigor with those of temperature and precipitation data for four diverse ecosystems, ranging from near-equatorial to polar, and spanning both hemispheres to determine which climatic factor is limiting growth.
Students examine data from Mauna Loa to learn about CO2 in the atmosphere. The students also examine how atmospheric CO2 changes through the seasonal cycle, by location on Earth, and over about 40 years and more specifically over 15 years. Students graph data in both the Northern and Southern Hemisphere and draw conclusions about hemispherical differences in CO2 release and uptake.
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.
This is a sequence of 5 classroom activities focusing on the El NiÃo climate variability. The activities increase in complexity and student-directedness. The focus of the activities is on accessing and manipulating real data to help students understand El NiÃo as an interaction of Earth systems.
Hands-on laboratory activity that allows students to investigate the effects of distance and angle on the input of solar radiation at Earth's surface, the role played by albedo, the heat capacity of land and water, and how these cause the seasons. Students predict radiative heating based on simple geometry and experiment to test their hypotheses.
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 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.
In this hands-on lesson, students measure the effect of distance and inclination on the amount of heat felt by an object and apply this experiment to building an understanding of seasonality. In Part 1, the students set up two thermometers at different distances from a light bulb and record their temperatures to determine how distance from a heat source affects temperature. In Part 2, students construct a device designed to measure the temperature as a function of viewing angle toward the Sun by placing a thermometer inside a black construction paper sleeve, and placing the device at different angles toward the Sun. They then explain how distance and inclination affect heat and identify situations where these concepts apply, such as the seasons on Earth and the NASA Mercury MESSENGER mission.
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.