Temperature verification:Testing Global Climate Models
Observed global temperature changes versus simulations via the HadGEM1 GCM, assuming only natural climate forcing factors, anthropogenic forcing factors, or the sum of the two. The gray band indicates the uncertainty of the calculations for all forcing fa
Published: December 18, 2010, 12:00 am
Updated: May 7, 2012, 6:55 pm
This article has been reviewed by the following Topic Editor:
David Hassenzahl PhD
If we are given values for the past, present, and projected future of greenhouse gases, we can derive the total of all climatic forcing factors, and run global climate models (GCMs) to calculate the past, present, and likely future of Earth’s climate. Verifying a GCM involves simulating the climate for some time past and comparing the model’s output with what actually occurred. Discrepancies between a GCM and the climate record indicate problems with the model’s assumptions, algorithms, initial conditions, coordination among various submodels, or even the climate record. Tweaking a GCM to correct for such problems is a fine art because climate involves interactions among many variables that do not exhibit linear behavior.
Linear behavior dictates that changes in output be proportional to changes in input. In nonlinear behavior, small changes in conditions may have large consequences, or conversely, large changes may have no perceptible consequences. An example of nonlinear behavior is that lowering the temperature of an air mass has only slight effects on its transmission of electromagnetic radiation until water vapor in the air mass reaches saturation, a cloud forms, and, suddenly, albedo skyrockets.
The Intergovernmental Panel on Climate Change (IPCC), in its Fourth Assessment Report released in 2007, presents the results from 16 or more GCMs that simulated Earth’s climate under a range of forcing factors, both natural (e.g., orbital variations) and anthropogenic (e.g., human activities that emit additional greenhouse gases). The models were run three times: once with only natural climate forcing, the second time with only anthropogenic forcing, and, finally, with both natural and anthropogenic forcing. The best match for reconstructing global temperatures over the past 125 years occurred when the models included both types of forcing. In particular, anthropogenic forcing appears responsible for most of the 0.5°C rise in global temperatures experienced from 1970 until 2000.
This is an excerpt from the book Global Climate Change: Convergence of Disciplines by Dr. Arnold J. Bloom and taken from UCVerse of the University of California.
©2010 Sinauer Associates and UC Regents
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Citation
Arnold J Bloom (Lead Author);David Hassenzahl PhD (Topic Editor) "Testing Global Climate Models". In: Encyclopedia of Earth. Eds. Cutler J. Cleveland (Washington, D.C.: Environmental Information Coalition, National Council for Science and the Environment). [First published in the Encyclopedia of Earth December 18, 2010; Last revised Date May 7, 2012; Retrieved May 25, 2013 <http://www.eoearth.org/article/Testing_Global_Climate_Models?topic=54314>
The Author
Arnold J. Bloom became a botanist through a circuitous route. Upon receiving an undergraduate degree in Physics from Yale University, he spent several years developing computer models of the spread of air pollution over cities in the USA and Germany. He received a Ph.D. in Biological Sciences from Stanford University, where he also completed a two-semester course in Environmental Legislation at the Law School. He conducted postdoctoral research on the temperature responses of plants at the ... (Full Bio)
If we are given values for the past, present, and projected future of greenhouse gases, we can derive the total of all climatic forcing factors, and run global climate models (GCMs) to calculate the past, present, and likely future of Earth’s climate. Verifying a GCM involves simulating the climate for some time past and comparing the model’s output with what actually occurred. Discrepancies between a GCM and the climate record indicate problems with the model’s assumptions, algorithms, initial conditions, coordination among various submodels, or even the climate record. Tweaking a GCM to correct for such problems is a fine art because climate involves interactions among many variables that do not exhibit linear behavior.
Linear behavior dictates that changes in output be proportional to changes in input. In nonlinear behavior, small changes in conditions may have large consequences, or conversely, large changes may have no perceptible consequences. An example of nonlinear behavior is that lowering the temperature of an air mass has only slight effects on its transmission of electromagnetic radiation until water vapor in the air mass reaches saturation, a cloud forms, and, suddenly, albedo skyrockets.
The Intergovernmental Panel on Climate Change (IPCC), in its Fourth Assessment Report released in 2007, presents the results from 16 or more GCMs that simulated Earth’s climate under a range of forcing factors, both natural (e.g., orbital variations) and anthropogenic (e.g., human activities that emit additional greenhouse gases). The models were run three times: once with only natural climate forcing, the second time with only anthropogenic forcing, and, finally, with both natural and anthropogenic forcing. The best match for reconstructing global temperatures over the past 125 years occurred when the models included both types of forcing. In particular, anthropogenic forcing appears responsible for most of the 0.5°C rise in global temperatures experienced from 1970 until 2000.
This is an excerpt from the book Global Climate Change: Convergence of Disciplines by Dr. Arnold J. Bloom and taken from UCVerse of the University of California.
©2010 Sinauer Associates and UC Regents
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