Arctic Climate Curriculum, Activity 3: Exploring Arctic Climate Data

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In this activity, students use authentic Arctic climate data to unravel some causes and effects related to the seasonal melting of the snowpack and to further understand albedo.

MS-PS4-2 Develop and use a model to describe that waves are reflected, absorbed, or transmitted through various materials.

HS-ESS2-2 Analyze geoscience data to make the claim that one change to Earth's surface can create feedbacks that cause changes to other Earth systems.

Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.

Distinguish between causal and correlational relationships in data.

Analyze and interpret data to provide evidence for phenomena.

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.

Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena.

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.

Make a quantitative and/or qualitative claim regarding the relationship between dependent and independent variables.

Construct and revise an explanation based on valid and reliable evidence obtained from a variety of sources (including students’ own investigations, models, theories, simulations, peer review) 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.

Use digital tools (e.g., computers) to analyze very large data sets for patterns and trends.

Use mathematical, computational, and/or algorithmic representations of phenomena or design solutions to describe and/or support claims and/or explanations.

Make directional hypotheses that specify what happens to a dependent variable when an independent variable is manipulated.

Although energy cannot be destroyed, it can be converted to less useful forms—for example, to thermal energy in the surrounding environment.

The foundation for Earth’s global climate systems is the electromagnetic radiation from the sun, as well as its reflection, absorption, storage, and redistribution among the atmosphere, ocean, and land systems, and this energy’s re-radiation into space.

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.

When light shines on an object, it is reflected, absorbed, or transmitted through the object, depending on the object’s material and the frequency (color) of the light.

Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.

Much of science deals with constructing explanations of how things change and how they remain stable.

Cause and effect relationships can be suggested and predicted for complex natural and human designed systems by examining what is known about smaller scale mechanisms within the system.

Energy cannot be created or destroyed—it only moves between one place and another place, between objects and/or fields, or between systems.

Feedback (negative or positive) can stabilize or destabilize a system.

Cause and effect relationships may be used to predict phenomena in natural or designed systems.

Algebraic thinking is used to examine scientific data and predict the effect of a change in one variable on another (e.g., linear growth vs. exponential growth).

The transfer of energy can be tracked as energy flows through a designed or natural system.

Empirical evidence is needed to identify patterns.

Energy may take different forms (e.g. energy in fields, thermal energy, energy of motion).

Graphs, charts, and images can be used to identify patterns in data.

Patterns in rates of change and other numerical relationships can provide information about natural systems.

Explanations of stability and change in natural or designed systems can be constructed by examining the changes over time and processes at different scales, including the atomic scale.

Systems in dynamic equilibrium are stable due to a balance of feedback mechanisms.

Arctic Climate Curriculum, Activity 3: Exploring Arctic Climate Data

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