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.
In this 3-part lesson, students explore California climate and factors that are leading to changes within this climate system. Students begin by exploring California's climate and the state's topography. Next, they investigate coastal versus inland climate. Finally, they use My NASA Data to explore the effects of El NiÃo/La NiÃa on two locations found at the same latitude.
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.
These graphs show carbon dioxide measurements at the Mauna Loa Observatory, Hawaii. The graphs display recent measurements as well as historical long term measurements. The related website summarizes in graphs the recent monthly CO2, the full CO2 Record, the annual Mean CO2 Growth Rate, and gives links to detailed CO2 data for this location, which is one of the most important CO2 sites in the world.
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 video describes the role that dendrochronology plays in understanding climate change, especially changes to high elevation environments at an upper tree line. Dendrochronologists from the Big Sky Institute sample living and dead trees, describe how correlations between trees are made, and explain how tree cores record climate changes.
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.
In this activity from the Deep Earth Academy, students divide into groups to read and discuss one of nine short articles (1-2 pages) about research done by the Ocean Drilling Program. These articles discuss our understanding about past climate based on collected data. These articles briefly describe the research conducted and the findings. Students use the information from the article to complete a write-up that they share with other students. An extension activity involves examining ocean drilling data using Google Earth.
In this activity for undergraduates, students explore the CLIMAP (Climate: Long-Range Investigation, Mapping and Prediction) model results for differences between the modern and the Last Glacial Maximum (LGM) and discover the how climate and vegetation may have changed in different regions of the Earth based on scientific data.