Geophysical Institute at University of Fairbanks
Activity takes about one class period. Additional materials are needed.Discuss this Resource»
Learn more about Teaching Climate Literacy and Energy Awareness»
Resource indicates that the appropriate grade level is 9-12. The reviewers thought that the activity is better suited for middle school.
About Teaching Climate Literacy
Other materials addressing 1a
Other materials addressing 2f
1.2 Thermal energy.
2.3 Earth's climate driven by the Sun.
Excellence in Environmental Education Guidelines
Other materials addressing:
C) Collecting information.
Other materials addressing:
A) Processes that shape the Earth.
Other materials addressing:
Benchmarks for Science Literacy
Learn more about the Benchmarks
Notes From Our Reviewers
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Teaching Tips | Science | Pedagogy |
- The educator should explain the limitations of the model because they are using a light bulb, which is different than the radiation from the Sun.
- The educator could conduct activity outdoors rather than using a 60W light bulb so as to avoid confusion between solar radiation and "heat."
About the Science
- The activity nicely illustrates the effect of albedo in a simple way.
- Using a lamp to simulate radiation from the sun may promote misconceptions such as: Higher albedo surfaces reflect more "heat." To prevent this, educators should clarify that this activity is an attempt to model the effect of different surface albedos. It does not represent the actual phenomenon.
- Useful part of activity: Educator discusses why the ice-albedo feedback effect is a positive feedback loop that could contribute to climate change.
- Comment from scientist: Be careful of the wording when explaining feedback loops: A positive feedback reinforces the initial change whichever direction. So using increases or decreases can be potentially confusing. Here it is worded correctly in the sense of increasing the effect of the system but students might still get confused, maybe use the word magnifies instead of increases and counteracts instead of decreases.
- Comment from scientist: Activity Procedure 3 - It's important to note that an increase in temperature can cause snow and ice to start melting earlier in the year. In fact, this is where the albedo effect plays a bigger role, because melt really gets going during late spring and early summer when the sun is strongest and, therefore, the effect of albedo is strongest. By the time snow and ice start to form, it is generally September or later and the sun is already on its way to setting in the Arctic. The later freeze-up is affected to some extent by the albedo, but a bigger effect, especially for sea ice in the ocean, is the surface has heated more and is too warm initially to form snow or ice.
- Be careful with the wording that is used in activity - "ice forms" but snow doesn't "form on the earth" it "falls."
- Background information might need to be supplemented by educator.
About the Pedagogy
- Students are encouraged to hypothesize before the experiment, but the procedure is step-by-step rather than open-ended.
Related URLs These related sites were noted by our reviewers but have not been reviewed by CLEAN
- The activity is from the University of Alaska Fairbanks (UAF) as part of the Alaskan Climate Modeling Program curriculum (ACMP). Unit information can be found at: http://www.arcticclimatemodeling.org/subject_climate_change.html.
Disciplinary Core Ideas
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.
HS-ESS2.A1: Earth’s systems, being dynamic and interacting, cause feedback effects that can increase or decrease the original changes.
Science and Engineering Practices
MS-P2.7: Develop and/or use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales.
MS-P3.4: Collect data to produce data to serve as the basis for evidence to answer scientific questions or test design solutions under a range of conditions
MS-P4.1: Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.
MS-P4.3: Distinguish between causal and correlational relationships in data.
MS-P4.4: Analyze and interpret data to provide evidence for phenomena.
MS-P4.7: Analyze and interpret data to determine similarities and differences in findings.
MS-P6.1: Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena.
MS-P6.2: Construct an explanation using models or representations.
MS-P6.3: Construct a scientific explanation based on valid and reliable evidence obtained from sources (including the students’ own experiments) and the assumption that theories and laws that describe the natural world operate today as they did in the past and will continue to do so in the future.
MS-P6.4: Apply scientific ideas, principles, and/or evidence to construct, revise and/or use an explanation for real- world phenomena, examples, or events.
HS-P1.3: ask questions to determine relationships, including quantitative relationships, between independent and dependent variables
HS-P4.4: Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations.
HS-P6.1: Make a quantitative and/or qualitative claim regarding the relationship between dependent and independent variables.
MS-C4.3: Models are limited in that they only represent certain aspects of the system under study.
MS-C5.3: Energy may take different forms (e.g. energy in fields, thermal energy, energy of motion).
MS-C5.4: The transfer of energy can be tracked as energy flows through a designed or natural system.
MS-C1.3: Patterns can be used to identify cause and effect relationships.
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.
HS-C4.3: Models (e.g., physical, mathematical, computer models) can be used to simulate systems and interactions—including energy, matter, and information flows—within and between systems at different scales.
HS-C4.4: Models can be used to predict the behavior of a system, but these predictions have limited precision and reliability due to the assumptions and approximations inherent in models.
HS-C5.2: Changes of energy and matter in a system can be described in terms of energy and matter flows into, out of, and within that system.
HS-C7.1: Much of science deals with constructing explanations of how things change and how they remain stable.
HS-C7.3: Feedback (negative or positive) can stabilize or destabilize a system.
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