The benefits of quantifying climate model uncertainty in climate change impacts assessment: an example with heat-related mortality change estimates View Full Text


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Article Info

DATE

2011-08-31

AUTHORS

Simon N. Gosling, Glenn R. McGregor, Jason A. Lowe

ABSTRACT

The majority of climate change impacts assessments account for climate change uncertainty by adopting the scenario-based approach. This typically involves assessing the impacts for a small number of emissions scenarios but neglecting the role of climate model physics uncertainty. Perturbed physics ensemble (PPE) climate simulations offer a unique opportunity to explore this uncertainty. Furthermore, PPEs mean it is now possible to make risk-based impacts estimates because they allow for a range of estimates to be presented to decision-makers, which spans the range of climate model physics uncertainty inherent from a given climate model and emissions scenario, due to uncertainty associated with the understanding of physical processes in the climate model. This is generally not possible with the scenario-based approach. Here, we present the first application of a PPE to estimate the impact of climate change on heat-related mortality. By using the estimated impacts of climate change on heat-related mortality in six cities, we demonstrate the benefits of quantifying climate model physics uncertainty in climate change impacts assessment over the more common scenario-based approach. We also show that the impacts are more sensitive to climate model physics uncertainty than they are to emissions scenario uncertainty, and least sensitive to whether the climate change projections are from a global climate model or a regional climate model. The results demonstrate the importance of presenting model uncertainties in climate change impacts assessments if the impacts are to be placed within a climate risk management framework. More... »

PAGES

217-231

References to SciGraph publications

  • 2004-08. Quantification of modelling uncertainties in a large ensemble of climate change simulations in NATURE
  • 2005-01-01. Projected Changes in Extreme Weather and Climate Events in Europe in EXTREME WEATHER EVENTS AND PUBLIC HEALTH RESPONSES
  • 2003-09. The Effect of Spatial Scale of Climatic Change Scenarios on Simulated Maize, Winter Wheat, and Rice Production in the Southeastern United States in CLIMATIC CHANGE
  • 2006-02-04. On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles in CLIMATE DYNAMICS
  • 2003-10. Pattern Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates in CLIMATIC CHANGE
  • 2009-11-11. Changes in European temperature extremes can be predicted from changes in PDF central statistics in CLIMATIC CHANGE
  • 2008-12-04. Climate change and heat-related mortality in six cities Part 2: climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change in INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
  • 2001-11. Comparison of Agricultural Impacts of Climate Change Calculated from High and Low Resolution Climate Change Scenarios: Part I. The Uncertainty Due to Spatial Scale in CLIMATIC CHANGE
  • 2003-05-14. Heat stress and mortality in Lisbon Part II. An assessment of the potential impacts of climate change in INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
  • 2006-04-06. Towards quantifying uncertainty in transient climate change in CLIMATE DYNAMICS
  • 2004-01-11. The role of increasing temperature variability in European summer heatwaves in NATURE
  • 2000-02. The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3 in CLIMATE DYNAMICS
  • 2008-09-16. Comparison of uncertainty sources for climate change impacts: flood frequency in England in CLIMATIC CHANGE
  • 2000-02. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments in CLIMATE DYNAMICS
  • 2007-03-09. Climate change and heat-related mortality in six cities Part 1: model construction and validation in INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
  • 2005-01. Uncertainty in predictions of the climate response to rising levels of greenhouse gases in NATURE
  • 2008-08-19. Associations between elevated atmospheric temperature and human mortality: a critical review of the literature in CLIMATIC CHANGE
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    URI

    http://scigraph.springernature.com/pub.10.1007/s10584-011-0211-9

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    http://dx.doi.org/10.1007/s10584-011-0211-9

    DIMENSIONS

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