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 activity addresses naturally occurring climate change involving ENSO (El-NiÃo Southern Oscillation). In this activity, students play the role of a policy maker in Peru. First, they determine what sort of ENSO variation is occurring. Then, they must decide how to allocate Peru's resources to manage for possible weather-related problems.
This NOAA visualization video on YouTube shows the seasonal variations in sea surface temperatures and ice cover for the 22 years prior to 2007 based on data collected by NOAA polar-orbiting satellites (POES). El NiÃo and La NiÃa are easily identified, as are the trends in decreasing polar sea ice.
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.
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 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.