development; what is needed is developing pragmatic methodologies that get most of the benefit with a minimum of time waiting for simulations to finish.

While there has been considerable development in quantifying uncertainties regarding climate models, uncertainty quantification (UQ) is a field important to many different disciplines, particularly those that use models (NRC, 2012a). The climate modeling community could benefit from assessing new methods being developed in other disciplines (NRC, 2012a). Certain government agencies, such as the Department of Energy, are supporting multiple research efforts in such topics as advancing UQ in modeling, simulation, and analysis of complex systems.1

In general, more careful consideration of uncertainty can serve multiple purposes of model improvement and better utilization of model predictions and projections.

Reducing Uncertainties in the Climate Change Problem

Although there has been much progress in characterizing and quantifying uncertainty about future climate change, less progress has been made in the arena of reducing uncertainty. This is a complex issue, because it depends on what type of uncertainty is being reduced and how that particular uncertainty is quantified.

There has been steady reduction in uncertainty about the causes of current climate change, as expressed in the series of IPCC reports, such that in the 2007 report (IPCC, 2007d) it is stated that “[m]ost of the observed increase in global temperatures since the mid-20th century is very likely (i.e., 90% confidence) due to the observed increase in greenhouse gas concentrations.” This is primarily due to observation of continuing global warming and many of its anticipated corollaries consistent with the range of climate model predictions.

However, uncertainty in projections of future climate change is reducing more slowly. Before 2070, uncertainty about climate sensitivity is most important for projection of global-mean climate change. IPCC assessments suggest this uncertainty has not significantly decreased since 1990. It is unclear by how much this metric of uncertainty will be reduced over the next decade. Large regional projection uncertainties, especially in subtropical and summertime midlatitude precipitation, are added to this uncertainty in climate sensitivity; again, more research may beat these uncertainties down, but this may take time. Past 2070, uncertainty about GHG concentrations due to emissions uncertainty (which is difficult to reduce) is more important to projection of

___________________

1http://science.energy.gov/ascr/funding-opportunities/faq-for-math/ (accessed October 11, 2012).



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement