4.6 Article

The representation of health-relevant heatwave characteristics in a Regional Climate Model ensemble for New South Wales and the Australian Capital Territory, Australia

Journal

INTERNATIONAL JOURNAL OF CLIMATOLOGY
Volume 37, Issue 3, Pages 1195-1210

Publisher

WILEY
DOI: 10.1002/joc.4769

Keywords

heat extremes; excess heat factor; bias-correction; downscaling; WRF; GCM; model evaluation; Australia

Funding

  1. NSW Office of Environment and Heritage
  2. Climate Change Research Centre, University of New South Wales
  3. ACT Environment and Sustainable Development Directorate
  4. Sydney Water
  5. Sydney Catchment Authority
  6. Hunter Water, Transport for NSW
  7. NSW Department of Primary Industry
  8. NSW Office of Water
  9. Australian Research Council (ARC) Centre of Excellence for Climate System Science [CE110001028]

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Heatwaves have been linked to increased rates of human mortality and morbidity. Given these adverse health impacts, it is crucial to improve our understanding of future changes in these extreme events to inform health impacts studies and adaptation planning. While this information would be most beneficial at a local scale, Global Climate Models provide projections on much coarser resolutions. Regional Climate Models, such as those used in the New South Wales/Australian Capital Territory Regional Climate Modelling (NARCliM) project, provide simulations at a finer scale more appropriate for regional assessments. This study uses NARCliM output to investigate the ability of a Regional Climate Model ensemble to represent heatwave characteristics through the Excess Heat Factor, an index that includes factors that are known to be important to the heat-health relationship. Both uncorrected and bias-corrected model output is evaluated against observationally-derived heatwave characteristics for the period 1990-2009. The effect of bias-correction on future changes in heatwave characteristics is also assessed. Overall, the simulations provided a good representation of the recent climate and bias-correction did not greatly change simulated heatwave characteristics. Some regions were more affected by bias-correction than others, with bias-correction being most beneficial for coastal regions. We emphasise that these results may not apply to all indices measuring extreme heat, and demonstrate that results for an index based on a fixed absolute temperature threshold are substantially affected when bias-correction is applied. While supporting bias-correction, this study demonstrates that it is not necessarily required when evaluating a relative measure such as the Excess Heat Factor.

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