In this exercise learners use statistics (T-test using Excel) to analyze an authentic dataset from Lake Mendota in Madison, WI that spans the last 150 years to explore ice on/ice off dates. In addition, students are asked to investigate the IPCC Likelihood Scale and apply it to their statistical results.
This lesson sequence guides students to learn about the geography and the unique characteristics of the Arctic, including vegetation, and people who live there. Students use Google Earth to explore the Arctic and learn about meteorological observations in the Arctic, including collecting their own data in hands-on experiments. This is the first part of a three-part curriculum about Arctic climate.
This animation illustrates how the hardiness zones for plants have changed between 1990 and 2006 based data from 5,000 National Climatic Data Center cooperative stations across the continental United States.
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 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 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 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.