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Time Series: Uncovering the Hidden Processes in Science
http://pal.lternet.edu/docs/outreach/educators/instructional_materials/time_series_lesson/Palmer%20LTER%20FINAL%20Time%20Series%20Teacher%20Ver2013.pdf

Beth Simmons, Palmer LTER

In this activity, students review techniques used by scientists, as they analyze a 50-year temperature time series dataset. The exercise helps students understand that data typically has considerable variability from year to year and to predict trends or forecast the future, there is value in long-term data collection.

Activity takes about one 45-60 minute period

Learn more about Teaching Climate Literacy and Energy Awareness»

ngssSee how this Activity supports the Next Generation Science Standards»
Middle School: 1 Performance Expectation, 2 Disciplinary Core Ideas, 9 Cross Cutting Concepts, 9 Science and Engineering Practices
High School: 1 Performance Expectation, 1 Disciplinary Core Idea, 9 Cross Cutting Concepts, 10 Science and Engineering Practices

Climate Literacy
About Teaching Climate Literacy

Changes in climate is normal but varies over times/ space
About Teaching Principle 4
Other materials addressing 4d
Observations are the foundation for understanding the climate system
About Teaching Principle 5
Other materials addressing 5b

Excellence in Environmental Education Guidelines

1. Questioning, Analysis and Interpretation Skills:G) Drawing conclusions and developing explanations
Other materials addressing:
G) Drawing conclusions and developing explanations.
1. Questioning, Analysis and Interpretation Skills:A) Questioning
Other materials addressing:
A) Questioning.
1. Questioning, Analysis and Interpretation Skills:C) Collecting information
Other materials addressing:
C) Collecting information.
1. Questioning, Analysis and Interpretation Skills:E) Organizing information
Other materials addressing:
E) Organizing information.

Notes From Our Reviewers The CLEAN collection is hand-picked and rigorously reviewed for scientific accuracy and classroom effectiveness. Read what our review team had to say about this resource below or learn more about how CLEAN reviews teaching materials
Teaching Tips | Science | Pedagogy | Technical Details

Teaching Tips

  • Educator can use this activity in a variety of ways as a formative or summative assessment, or stand-alone activity during any time of the year as it addresses science processes.
  • Great activity to use in any discussion of why, at least in climate science, data collected over long periods of time is valuable.

About the Science

  • This lesson uses long-term sea surface temperatures to help students understand the benefits of using long-term data to make scientific observations and identify trends, as opposed to selecting a short-term occurrence. Strengths lie in its short to-the-point format.
  • The concept is simple - demonstrating why single snapshots of data are not suitable for finding trends or patterns that occur over long time periods, as in changes in climate. Richard Alley illustrates this concept nicely in one of the Earth: The Operator's Manual segments, choosing individual data points in his lifetime.
  • Passed initial science review - expert science review pending.

About the Pedagogy

  • Straightforward simple activity that very quickly demonstrates to students the importance of looking beyond a snapshot of data.
  • This lesson is intended to be an introductory activity to a science methods/process unit as stated by the author.
  • The assessment is successful completion of the worksheets used to analyze the temperature graphs.
  • Group discussions both in small groups and with the entire class round out the exercise.
  • Resources for those interested in learning more are provided.

Technical Details/Ease of Use

  • Available in pdf format.

Next Generation Science Standards See how this Activity supports:

Middle School

Performance Expectations: 1

MS-ESS3-5:Ask questions to clarify evidence of the factors that have caused the rise in global temperatures over the past century.

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.D2:Because these patterns are so complex, weather can only be predicted probabilistically.

Cross Cutting Concepts: 9

Energy and Matter, Stability and Change, Patterns, Cause and effect, Scale, Proportion and Quantity

MS-C5.3:Energy may take different forms (e.g. energy in fields, thermal energy, energy of motion).

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-C7.4:Systems in dynamic equilibrium are stable due to a balance of feedback mechanisms.

MS-C1.2: Patterns in rates of change and other numerical relationships can provide information about natural and human designed systems

MS-C1.4:Graphs, charts, and images can be used to identify patterns in data.

MS-C2.3:Phenomena may have more than one cause, and some cause and effect relationships in systems can only be described using probability.

MS-C3.1:Time, space, and energy phenomena can be observed at various scales using models to study systems that are too large or too small.

MS-C3.2: The observed function of natural and designed systems may change with scale.

MS-C3.5:Phenomena that can be observed at one scale may not be observable at another scale.

Science and Engineering Practices: 9

Analyzing and Interpreting Data, Constructing Explanations and Designing Solutions, Engaging in Argument from Evidence, Obtaining, Evaluating, and Communicating Information, Asking Questions and Defining Problems

MS-P4.1:Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.

MS-P4.4:Analyze and interpret data to provide evidence for phenomena.

MS-P4.5:Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible.

MS-P4.6:Consider limitations of data analysis (e.g., measurement error), and/or seek to improve precision and accuracy of data with better technological tools and methods (e.g., multiple trials).

MS-P6.1:Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena.

MS-P6.5:Apply scientific reasoning to show why the data or evidence is adequate for the explanation or conclusion

MS-P7.1:Compare and critique two arguments on the same topic and analyze whether they emphasize similar or different evidence and/or interpretations of facts.

MS-P8.2:Integrate qualitative and/or quantitative scientific and/or technical information in written text with that contained in media and visual displays to clarify claims and findings.

MS-P1.1:Ask questions that arise from careful observation of phenomena, models, or unexpected results, to clarify and/or seek additional information.

High School

Performance Expectations: 1

HS-ESS3-5: Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth systems.

Disciplinary Core Ideas: 1

HS-ESS2.D4:Current models predict that, although future regional climate changes will be complex and varied, average global temperatures will continue to rise. The outcomes predicted by global climate models strongly depend on the amounts of human-generated greenhouse gases added to the atmosphere each year and by the ways in which these gases are absorbed by the ocean and biosphere.

Cross Cutting Concepts: 9

Patterns, Scale, Proportion and Quantity, Energy and Matter, Stability and Change

HS-C1.1:Different patterns may be observed at each of the scales at which a system is studied and can provide evidence for causality in explanations of phenomena

HS-C1.2:Classifications or explanations used at one scale may fail or need revision when information from smaller or larger scales is introduced; thus requiring improved investigations and experiments.

HS-C1.4: Mathematical representations are needed to identify some patterns.

HS-C3.1:The significance of a phenomenon is dependent on the scale, proportion, and quantity at which it occurs.

HS-C3.3:Patterns observable at one scale may not be observable or exist at other scales.

HS-C3.5: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).

HS-C5.3:Energy cannot be created or destroyed—only moves between one place and another place, between objects and/or fields, or between systems.

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: 10

Asking Questions and Defining Problems, Developing and Using Models, Analyzing and Interpreting Data, Using Mathematics and Computational Thinking, Constructing Explanations and Designing Solutions, Engaging in Argument from Evidence, Obtaining, Evaluating, and Communicating Information

HS-P1.1:ask questions that arise from careful observation of phenomena, or unexpected results, to clarify and/or seek additional information.

HS-P1.3:ask questions to determine relationships, including quantitative relationships, between independent and dependent variables

HS-P2.1:Evaluate merits and limitations of two different models of the same proposed tool, process, mechanism or system in order to select or revise a model that best fits the evidence or design criteria.

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.

HS-P4.2:Apply concepts of statistics and probability (including determining function fits to data, slope, intercept, and correlation coefficient for linear fits) to scientific and engineering questions and problems, using digital tools when feasible.

HS-P4.3:Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data

HS-P5.2:Use mathematical, computational, and/or algorithmic representations of phenomena or design solutions to describe and/or support claims and/or explanations.

HS-P6.1:Make a quantitative and/or qualitative claim regarding the relationship between dependent and independent variables.

HS-P7.1:Compare and evaluate competing arguments or design solutions in light of currently accepted explanations, new evidence, limitations (e.g., trade-offs), constraints, and ethical issues

HS-P8.4: Evaluate the validity and reliability of and/or synthesize multiple claims, methods, and/or designs that appear in scientific and technical texts or media reports, verifying the data when possible.


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