In this activity, students examine global climate model output and consider the potential impact of global warming on tropical cyclone initiation and evolution. As a follow-up, students read two short articles on the connection between hurricanes and global warming and discuss these articles in context of what they have learned from model output.
In this activity, students learn about the urban heat island effect by investigating which areas of their schoolyard have higher temperatures - trees, grass, asphalt, and other materials. Based on their results, they hypothesize how concentrations of surfaces that absorb heat might affect the temperature in cities - the urban heat island effect. Then they analyze data about the history of Los Angeles heat waves and look for patterns in the Los Angeles climate data and explore patterns.
This activity engages students in the analysis of climate data to first find areas in the southern United States that are now close to having conditions in which the malaria parasite and its mosquito hosts thrive and then attempt to forecast when areas might become climatically suitable.
This activity engages learners in exploring the impact of climate change on arctic sea ice in the Bering Sea. They graph and analyze sea ice extent data, conduct a lab on thermal expansion of water, and then observe how a scientist collects long-term data on a bird population.
This activity introduces students to plotting and analyzing phenology data. Students use 30 years of data that shows the date of the first lilac bloom and the number of days of ice cover of nearby Gull Lake.
In this activity, students use Google Earth and team up with fictional students in Chersky, Russia to investigate possible causes of thawing permafrost in Siberia and other Arctic regions. Students explore the nature of permafrost and what the effects of thawing permafrost mean both locally and globally. Next, students use a spreadsheet to explore soil temperature data from permafrost boreholes and surface air temperature datasets from in and around the Chersky region for a 50-year time span.
This module contains five activities, in increasing complexity, that focus on understanding how to interpret and manipulate sea level data, using real data from NOAA.
Students first need to understand how to access and interpret sea surface height and tide data. To understand how to interpret these data, students will review and practice computing mean values. Along the way, they will learn how different factors, such as storms, affect tide levels and how to measure them. The goal is for students to become experienced with these kinds of data and the tools for accessing them so that, by the end of the module, they can continue to explore data sets driven by their own inquiry.