A number of scientists continue to take issue with the position taken by IPCC scientists. Some find fault with the entire concept of climate sensitivity. The debate about climate sensitivity modeling is so great that it is sometimes called SWAG (a "scientific wild-ass guess").
Some researchers find fault with measurement techniques, while others insist that global warming and climate change are responses to geophysical occurrences rather than irresponsible human behaviors. A good deal of the controversy about climate sensitivity modeling results from disagreements on the best ways to characterize feedbacks, because variations in the ways that feedbacks are employed in various models produces vastly different results.
The uncertainty of climate change predictions based on cloud feedback are arguably the most frequently-cited evidence that climate sensitivity models are inaccurate predictors of future climate patterns. In most models, cloud feedback is perceived as a positive indicator of global warming. In others, cloud feedback is viewed as a neutral mechanism. Many researchers insist that some uncertainty in predicting global warming through climate sensitivity modeling is inevitable.
Reasons given for this inherent uncertainty include gaps in the understanding of the physical processes that contribute to feedbacks, the fact that interactions among the various processes are likely to be complex, and the dynamic nature of climate. Ongoing attempts to make the use of feedbacks in climate sensitivity predictions more accurate have led to the use of supplementary observational studies, such as those that include data gathered from satellites. Another way in which scientists are trying to make climate modeling more accurate is through the use of Climate Process Teams (CPT), in which groups of scientists work together to improve the prediction process. The National Center for Atmospheric Research (NCAR) and the Geophysical Fluid Dynamics Laboratory (GFDL) have developed two models that are widely used by American researchers in predicting global warming and climate change.
Using low-latitude cloud feedbacks, team members have arrived at vastly different predictions. The NCAR team first used the Community Climate Model (CCM), which they developed in 1983 for use by the global research community. In 1994, NCAR introduced an improved model, the Climate System Model (CSM), which uses atmosphere, land surface, global ocean, and sea ice feedbacks. Research at GFDL combines computer modeling with specialized observations based on the atmosphere and oceans, and on chemistry and biology, to make predictions on climate change.
See ALSO: Attribution of Global Warming; Carbon Dioxide; Climate Feedback; Climate Models; Cloud Feedback; Computer Models; Intergovernmental Panel on Climate Change (IPCC).
BIBLIOGRAphY. S. Bony, et al., Geophysical Research Abstracts, www.cosis.net/abstracts (cited November 2007); Andrew Ford, Modeling the Environment: An Introduction to System Dynamics Models of Environmental Systems (Island Press, 1999); James E. Hansen and Taro Takahashi, eds., Climate Processes and Climate Sensitivity (American Geophysical Union, 1984); Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report, www.ipcc.ch (cited November 2007); IPCC, Third Assessment Report, www.ipcc.ch (cited November 2007); Richard A. Kerr, "Climate Change: Three Degrees of Consensus," Science (August 13, 2004); Irving M. Mint-zer, ed., Confronting Climate Change: Risks, Implications, and Responses (Cambridge University Press, 1991; William O'Keefe, "Climate Sensitivity—Still A Swag," Marshall Policy Institute (September 2004); Gerard H. Roe and Marcia B. Baker, "Why Is Climate Sensitivity So Unpredictable?" Science (October 26, 2007).
Elizabeth R. Purdy Independent Scholar
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