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Estimating Climate Sensitivity Report of a Workshop (2003) / Chapter Skim
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Opening Session
Pages 2-6

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 2...
... When examining a large number of scenarios, modeling with a Fill climate model is too costly and timeconsuming. Instead they rely on reduced-form climate models in which climate sensitivity is an input assumption, ' For specific climate model intercomparisons and evaluations that use "realistic" past and projected radiative forcing, it has sometimes proved useful to use "effective climate sensitivity" (Seff ~ as a measure of a model time-varying warming responses under "realistic" forcing scenarios.
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From page 3...
... SCENGEN uses a scaling algorithm to provide information about spatial patterns of climate change. The primary purpose of the MAGICC-SCENGEN software is to allow nonexpert users to investigate the implications of different emission scenarios for future global mean and regional climate change and to quantify uncertainties in these changes.
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From page 4...
... In Chapter 6 of the IPCC/TAR "Radiative Forcing of Climate Change", the forcing-response relationship is defined such Hat the global, annual mean surface temperature is equal to the global, annual mean radiative forcing (evaluated at the tropopause after equilibration of the stratosphere) multiplied by a global mean climate sensitivity factor (k, given In units of Kelvin per watts per meter squared ~/Wm-23.
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From page 5...
... Ramas~amy: Generally, global mean metrics are limited in they applicability. Broccoli: Sensitivity is relevant to the consideration of local and regional climate changes because as sensitivity increases, the mean of the distribution (and thus the probability of a temperature increase in any one place)
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From page 6...
... Even modest changes in cloud parameteriza~ons have been found to affect cloud feedbacks and, hence, sensitivity. The primary difference is that for the NCAR model, there is a strong negative feedback involving low clouds.
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Key Terms

  • global mean
  • climate models
  • climate model
  • radiative forcing
  • sensitivity factor

  • mean temperature
  • equilibrium climate
  • water vapor
  • mean surface
  • feedback involving

  • annual mean
  • deep ocean
  • surface temperature
  • climate equilibrium
  • input value

  • observed climate
  • involving low
  • uncertainty due
  • feedback processes
  • ipcc chapter

  • model intercomparison
  • positive feedback
  • balance climate
  • ocean mixing
  • cloud feedbacks

  • intercomparison studies
  • uncertainty range
  • current models
  • low clouds
  • heat exchange


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