The representation of health‐relevant heatwave characteristics in a Regional Climate Model ensemble for New South Wales and the Australian Capital Territory, Australia. (12th May 2016)

• Record Type: Journal Article
• Authors: Gross, Mia H.; Alexander, Lisa V.; Macadam, Ian; Green, Donna; Evans, Jason P.
• Is Part Of: International journal of climatology. Volume 37:Number 3(2017)
• Page Start: 1195
• Page End: 1210
• Publication Date: 2016-05-12
• Subjects: heat extremes -- excess heat factor -- bias‐correction -- downscaling -- WRF -- GCM -- model evaluation -- Australia; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.4769
• Languages: English
• ISSNs: 0899-8418

Abstract

ABSTRACT: 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.