This lesson is an investigation of the impact of climate change on the phenology of a variety of taxa, including migrating birds and hibernating animals in the Colorado Rockies. Students analyze 40 years of data collected by Billy Barr from the Rocky Mountain Biological Laboratory.
In this activity, students learn about the tools and methods paleoclimatologists use to reconstruct past climates. In constructing sediment cores themselves, students will achieve a very good understanding of the sedimentological interpretation of past climates that scientists can draw from cores.
This activity focuses on reconstructing the Paleocene-Eocene Thermal Maximum (PETM) as an example of a relatively abrupt global warming period. Students access Integrated Ocean Drilling Program (IODP) sediment core data with Virtual Ocean software in order to display relevant marine sediments and their biostratigraphy.
In this intermediate Excel activity, students import US Historical Climate Network mean temperature data into Excel from a station of their choice. They are then guided through the activity on how to use Excel for statistical calculations, graphing, and linear trend estimates. The activity assumes some familiarity with Excel and graphing in Excel.
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 teaching activity is an introduction to how ice cores from the cryosphere are used as indicators and record-keepers of climate change as well as how climate change will affect the cryosphere. Students learn through a guided web exercise how scientists analyze ice cores to learn about past climate conditions, how melting sea and land ice will contribute to sea level rise, and what areas of the world would be at risk if Antarctic and/or Greenland ice sheets were to melt away.
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.