Variations in carbon dioxide concentrations in Earth's atmosphere

Type of Resource: Link

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Description

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.

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

Analyze and interpret data to provide evidence for phenomena.

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).

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.

Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data.

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

Evaluate the impact of new data on a working explanation and/or model of a proposed process or system.

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.

Gradual atmospheric changes were due to plants and other organisms that captured carbon dioxide and released oxygen.

Changes in the atmosphere due to human activity have increased carbon dioxide concentrations and thus affect climate.

Photoelectric materials emit electrons when they absorb light of a high-enough frequency.

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.

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

Empirical evidence is needed to identify patterns.

Phenomena that can be observed at one scale may not be observable at another scale.

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