This video illustrates how atmospheric particles, or aerosols (such as black carbon, sulfates, dust, fog), can affect the energy balance of Earth regionally, and the implications for surface temperature warming and cooling.
This video shows 15 years of data obtained via Polar-orbiting satellites that are able to detect subtle differences in ocean color, allowing scientists to see where there are higher concentrations of phytoplankton - a proxy for the concentration of chlorophyll in the ocean.
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.
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.
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 lesson explores El NiÃo 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 NiÃo from 1997 to 1998. In this way, students will model the methods of researchers who bring their expertise to study integrated science questions.