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The Findings From Mauna Loa
http://www.globalsystemsscience.org/studentbooks/cc/ch6/investigation-1

The Lawrence Hall of Science

This activity involves plotting and comparing monthly data on atmospheric C02 concentrations over two years, as recorded in Mauna Loa and the South Pole, and postulating reasons for differences in their seasonal patterns. Longer-term data is then examined for both sites to see if seasonal variations from one site to the other carry over into longer term trends.

This activity takes about one to two 45-minute lesson periods.

Learn more about Teaching Climate Literacy and Energy Awareness»

ngssSee how this Activity supports the Next Generation Science Standards»
Middle School: 2 Cross Cutting Concepts, 3 Science and Engineering Practices
High School: 1 Cross Cutting Concept, 2 Science and Engineering Practices

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 may want to use the text that accompanies this activity http://www.globalsystemsscience.org/studentbooks/cc/ch6 to establish context.
  • While part of curricula designed for high school, the activity could be appropriate for upper middle school students, with appropriate supports and modifications.
  • Graphing programs could be used or graphs made in advance for students to interpret if an educator wanted to focus on analysis and not making graphs.
  • Instructions and link are provided at the end of the activity to access current 30+-year data and graphs on carbon cycle gases from NOAA ESRL, which keeps the resource from becoming outdated: http://www.esrl.noaa.gov/gmd/.
  • This activity is from the Climate Change guide, which is part of the Global System Sciences curriculum education theme Key Global Problems.

About the Science

  • The activity uses real data to analyze and compare atmospheric carbon dioxide levels recorded at monitoring stations in Mauna Loa and Antarctica for a 2-year period (2006-2007).
  • The 30-year average (1975-2005) of monthly average carbon dioxide levels at Mauna Loa is observed and the change in concentration over time is calculated.
  • The effects of seasonal variations and differences in land cover on carbon dioxide levels are introduced but not explained in detail.
  • Comments from expert scientist:
    Scientific strengths:
    - Graphing real world data
    - comparing graphs
    - interpreting results to understand the ecological significance

    Suggestions:
    - Also would be a great extension for students to try using Excel to plot their graphs
    - Update the data to reflect more current years

About the Pedagogy

  • This activity is very straight-forward; students plot CO2 concentration data provided from the two locations, compare variations/patterns from month to month and over 2 years, and answer several questions about why the patterns might be different in the two locations. Then they compare data from both sites over 30 years and consider what longer-term data indicates about overall trends common to both locations.
  • Questions posed to students require them to examine the data and explain what they find.
  • Prerequisite background information is available at: http://www.globalsystemsscience.org/studentbooks/cc/ch6

Technical Details/Ease of Use

  • This is a straightforward activity involving interpretation of data tables and corresponding graphs. Very low tech and easy to follow.
  • Free teacher guide with downloadable files and additional activities is available upon request at: http://www.globalsystemsscience.org/teacherguides.

Next Generation Science Standards See how this Activity supports:

Middle School

Cross Cutting Concepts: 2

Patterns, Cause and effect

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

MS-C2.1:Relationships can be classified as causal or correlational, and correlation does not necessarily imply causation.

Science and Engineering Practices: 3

Analyzing and Interpreting Data

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-P4.7:Analyze and interpret data to determine similarities and differences in findings.

High School

Cross Cutting Concepts: 1

Cause and effect

HS-C2.1:Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.

Science and Engineering Practices: 2

Analyzing and Interpreting Data

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-P4.4:Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations.


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