Finn Ryan, Scott Pauli, Pitch Interactive, Wisconsin Educational Communications Board
Learn more about Teaching Climate Literacy and Energy Awareness»
See how this Simulation/Interactive supports the Next Generation Science Standards»
Middle School: 2 Disciplinary Core Ideas, 5 Cross Cutting Concepts, 6 Science and Engineering Practices
High School: 1 Disciplinary Core Idea, 5 Cross Cutting Concepts, 4 Science and Engineering Practices
About Teaching Climate Literacy
Other materials addressing 4b
Other materials addressing 4c
Other materials addressing 4e
Notes From Our Reviewers
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Teaching Tips | Science | Pedagogy |
- The web page for this activity offers teaching tips.
- The datasets used in this visualization are specifically about Wisconsin, but the lesson can be applied to any region with ice-covered lakes. Furthermore, it might be useful as a case study of the effects of climate change on the Earth system.
About the Science
- Interactive provides simple buttons that allow users to view the 10 longest seasons, the 10 shortest seasons and the overall trend. The records show significant year-to-year variability in the length of the ice-cover season, but there is a clear trend of fewer ice-cover days over time. In both lakes, the 10 longest ice cover winters were prior to 1905; the shortest ice cover seasons mainly fall in the last 20 years.
- This data illustrates the important point that although there is significant year-to-year variability, there also is an unmistakable trend in these data. There also are pop-ups that give the actual dates of ice cover and melting for each year.
- Data ends in 2010. Up-to-date data can be accessed from the WI climatology office: Mendota and Monona.
- Comments from expert scientist: The resource provides a useful, easy-to-read historical record of ice cover for two well-known lakes in Madison, WI. The biological and limnological significance of changing ice cover on the lakes is explained accurately and at a level accessible to non-scientists. In each case, the science is accurate and accessible to anyone interested in understanding how climate change has affected Wisconsin.
About the Pedagogy
- Very engaging data display that allows students to examine how the period of ice cover has changed over the decades.
- The main point of this visualization is to show that climate change is already happening, and the overall trend is toward significantly fewer ice covered days on these two lakes.
- The simple examination of these datasets opens up questions about the long-term implications for local culture and economy. There are additional examples on this website that explore other impacts of climate change and their implications.
- This data-driven visual can lead to a variety of questions.
Technical Details/Ease of Use
- The technical quality of the graphical and the interactive features is very high.
- Excellent interface.
Related URLs These related sites were noted by our reviewers but have not been reviewed by CLEANHome page for Climate Wisconsin has other examples of changing climate.
Next Generation Science Standards See how this Simulation/Interactive supports:
Disciplinary Core Ideas: 2
MS-ESS2.C2:The complex patterns of the changes and the movement of water in the atmosphere, determined by winds, landforms, and ocean temperatures and currents, are major determinants of local weather patterns.
MS-ESS2.D1:Weather and climate are influenced by interactions involving sunlight, the ocean, the atmosphere, ice, landforms, and living things. These interactions vary with latitude, altitude, and local and regional geography, all of which can affect oceanic and atmospheric flow patterns.
Cross Cutting Concepts: 5
MS-C7.1: Explanations of stability and change in natural or designed systems can be constructed by examining the changes over time and forces at different scales, including the atomic scale.
MS-C7.3:Stability might be disturbed either by sudden events or gradual changes that accumulate over time.
MS-C7.4:Systems in dynamic equilibrium are stable due to a balance of feedback mechanisms.
MS-C1.4:Graphs, charts, and images can be used to identify patterns in data.
MS-C2.2:Cause and effect relationships may be used to predict phenomena in natural or designed systems.
Science and Engineering Practices: 6
MS-P4.1:Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.
MS-P4.2:Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.
MS-P4.3: Distinguish between causal and correlational relationships in data.
MS-P1.1:Ask questions that arise from careful observation of phenomena, models, or unexpected results, to clarify and/or seek additional information.
MS-P1.2:ask questions to identify and/or clarify evidence and/or the premise(s) of an argument.
MS-P1.3:Ask questions to determine relationships between independent and dependent variables and relationships in models.
Disciplinary Core Ideas: 1
HS-ESS2.C1:The abundance of liquid water on Earth’s surface and its unique combination of physical and chemical properties are central to the planet’s dynamics. These properties include water’s exceptional capacity to absorb, store, and release large amounts of energy, transmit sunlight, expand upon freezing, dissolve and transport materials, and lower the viscosities and melting points of rocks.
Cross Cutting Concepts: 5
HS-C1.5:Empirical evidence is needed to identify patterns.
HS-C2.1:Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.
HS-C7.1:Much of science deals with constructing explanations of how things change and how they remain stable.
HS-C7.2:Change and rates of change can be quantified and modeled over very short or very long periods of time. Some system changes are irreversible.
HS-C7.3:Feedback (negative or positive) can stabilize or destabilize a system.
Science and Engineering Practices: 4
HS-P1.1:ask questions that arise from careful observation of phenomena, or unexpected results, to clarify and/or seek additional information.
HS-P1.2:ask questions that arise from examining models or a theory, to clarify and/or seek additional information and relationships.
HS-P1.3:ask questions to determine relationships, including quantitative relationships, between independent and dependent variables
HS-P4.1:Analyze data using tools, technologies, and/or models (e.g., computational, mathematical) in order to make valid and reliable scientific claims or determine an optimal design solution.