On regional dynamical downscaling for the assessment and projection of temperature and precipitation extremes across Tasmania, Australia

Christopher J. White, Kathleen L. McInnes, Robert P. Cechet, Stuart P. Corney, Michael R. Grose, Gregory K. Holz, Jack J. Katzfey, Nathaniel L. Bindoff

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

The ability of an ensemble of six GCMs, downscaled to a 0.1° lat/lon grid using the Conformal Cubic Atmospheric Model over Tasmania, Australia, to simulate observed extreme temperature and precipitation climatologies and statewide trends is assessed for 1961-2009 using a suite of extreme indices. The downscaled simulations have high skill in reproducing extreme temperatures, with the majority of models reproducing the statewide averaged sign and magnitude of recent observed trends of increasing warm days and warm nights and decreasing frost days. The warm spell duration index is however underestimated, while variance is generally overrepresented in the extreme temperature range across most regions. The simulations show a lower level of skill in modelling the amplitude of the extreme precipitation indices such as very wet days, but simulate the observed spatial patterns and variability. In general, simulations of dry extreme precipitation indices are underestimated in dryer areas and wet extremes indices are underestimated in wetter areas. Using two SRES emissions scenarios, the simulations indicate a significant increase in warm nights compared to a slightly more moderate increase in warm days, and an increase in maximum 1- and 5-day precipitation intensities interspersed with longer consecutive dry spells across Tasmania during the twenty-first century.

Original languageEnglish
Pages (from-to)3145-3165
Number of pages21
JournalClimate Dynamics
Volume41
Issue number11-12
Early online date21 Mar 2013
DOIs
Publication statusPublished - 31 Dec 2013

Keywords

  • Australian climate
  • climate change
  • extremes
  • observations
  • projections
  • regional climate models

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