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Variations in carbon dioxide concentrations in Earth's atmosphere
http://www.globalwarmingart.com/wiki/File:Carbon_Dioxide_400kyr_Rev_png

Robert A. Rohde, Global Warming Art

This resource is no longer officially part of our collection This resource has been removed from our collection, likely because the original resource is no longer available. If you have further information about the link (e.g. a new location where the information can be found) please let us know.

You may be able to find previous versions at the Internet Archive.

This graph, based on key ice core data sets and recent monitoring programs, shows the variations in concentration of carbon dioxide (CO2) in the atmosphere during the last 400,000 years.

Learn more about Teaching Climate Literacy and Energy Awareness»

ngssSee how this Static Visualization supports the Next Generation Science Standards»
Middle School: 1 Disciplinary Core Idea, 3 Cross Cutting Concepts, 3 Science and Engineering Practices
High School: 4 Disciplinary Core Ideas, 3 Cross Cutting Concepts, 4 Science and Engineering Practices

Climate Literacy
About Teaching Climate Literacy

Global warming and especially arctic warming is recorded in natural geological and historic records
About Teaching Principle 4
Other materials addressing 4e
Observations are the foundation for understanding the climate system
About Teaching Principle 5
Other materials addressing 5b
Global warming is "very likely" caused by human greenhouse gas emission
About Teaching Principle 6
Other materials addressing 6a

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

  • Discussion of this visualization should include information about how ice cores are collected and analyzed as well as the Mauna Loa Observatory data.
  • Also link to Milankovitch orbital cycles, which play an important role in climate change over millennial scales: http://serc.carleton.edu/resources/36458.html

About the Science

  • This figure was developed from credible data sources, e.g. US Department of Energy, Nature Earth and Planetary Science Letters. While the figure does not contain the most recent data from the Mauna Loa Observatory, available elsewhere, it does illustrate several important ice core records.
  • The graph clearly shows that since the Industrial Revolution, circa 1800, the burning of fossil fuels has caused a dramatic increase of CO2 in the atmosphere, reaching levels that are likely unprecedented in the last 20 million years.
  • Comment from expert scientist: It points out CO2 has a natural variability, but since the industrial revolution, anthropogenic sources have caused changes to the amount of CO2 in the atmosphere beyond the natural variability.

About the Pedagogy

  • This visualization illustrates some of the main evidence that the current levels of global carbon dioxide are historically unprecedented. It is central to any discussion of human-induced climate change.
  • Discussions around this visualization can include the different sources of CO2 data that scientists validated and merged to produce the graph, including the Vostok Ice Core, EPICA ice core, Law Dome ice core, Siple ice core, and Mauna Loa Observations.

Related URLs These related sites were noted by our reviewers but have not been reviewed by CLEAN

This is some background information at: http://www.fs.fed.us/ccrc/climate-basics/climate-primer.shtml where the same figure appears.

Next Generation Science Standards See how this Static Visualization supports:

Middle School

Disciplinary Core Ideas: 1

MS-ESS3.D:

Cross Cutting Concepts: 3

Patterns, Scale, Proportion and Quantity

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

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

Science and Engineering Practices: 3

Analyzing and Interpreting Data

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

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).

High School

Disciplinary Core Ideas: 4

HS-ESS2.D2:Gradual atmospheric changes were due to plants and other organisms that captured carbon dioxide and released oxygen.

HS-ESS2.D3:Changes in the atmosphere due to human activity have increased carbon dioxide concentrations and thus affect climate.

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.

HS-LS2.B3:Photosynthesis and cellular respiration are important components of the carbon cycle, in which carbon is exchanged among the biosphere, atmosphere, oceans, and geosphere through chemical, physical, geological, and biological processes.

Cross Cutting Concepts: 3

Patterns, Scale, Proportion and Quantity

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-C1.5:Empirical evidence is needed to identify patterns.

HS-C3:

Science and Engineering Practices: 4

Analyzing and Interpreting Data

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

HS-P4.5:Evaluate the impact of new data on a working explanation and/or model of a proposed process or system.


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