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    Assessing the Stationarity of Australian Precipitation Extremes in Forced and Unforced CMIP5 Simulations

    Source: Journal of Climate:;2017:;volume( 031 ):;issue: 001::page 131
    Author:
    Lewis, Sophie C.
    DOI: 10.1175/JCLI-D-17-0393.1
    Publisher: American Meteorological Society
    Abstract: AbstractKnowledge of the range of precipitation variability and extremes is restricted in regions such as Australia, where instrumental records are short and paleoclimatic records are limited in spatial and temporal extent and resolution. In such comparatively data-poor regions, there is limited context for understanding the statistical unusualness of recently observed extreme events, such as heavy rain and drought, and the influence of stochastic and anthropogenic forcings on their magnitude. This study attempts to further understandings of the range of forced and unforced variability using CMIP5 climate models. Focusing on extremes in the magnitude of monthly, seasonal, and annual precipitation, the distribution of instrumental-period observed precipitation in various Australian regions is compared to simulated precipitation in historical experiments as well as various long experiment (preindustrial control and Last Millennium) and anthropogenically forced simulations of the twenty-first century (RCP2.6 and RCP8.5). There is no systematic increase in the magnitude of simulated extremes corresponding to the length of model simulations, although many realizations reveal higher magnitude extremes compared to those observed, suggesting that the duration of the instrumental record may not capture the potential severity of stochastically driven extremes. A coherent increase in both wet and dry extremes is simulated throughout Australian regions in high greenhouse gas emissions scenarios, demonstrating a forced hydrological response.
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      Assessing the Stationarity of Australian Precipitation Extremes in Forced and Unforced CMIP5 Simulations

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    contributor authorLewis, Sophie C.
    date accessioned2018-01-03T11:01:56Z
    date available2018-01-03T11:01:56Z
    date copyright10/5/2017 12:00:00 AM
    date issued2017
    identifier otherjcli-d-17-0393.1.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4246300
    description abstractAbstractKnowledge of the range of precipitation variability and extremes is restricted in regions such as Australia, where instrumental records are short and paleoclimatic records are limited in spatial and temporal extent and resolution. In such comparatively data-poor regions, there is limited context for understanding the statistical unusualness of recently observed extreme events, such as heavy rain and drought, and the influence of stochastic and anthropogenic forcings on their magnitude. This study attempts to further understandings of the range of forced and unforced variability using CMIP5 climate models. Focusing on extremes in the magnitude of monthly, seasonal, and annual precipitation, the distribution of instrumental-period observed precipitation in various Australian regions is compared to simulated precipitation in historical experiments as well as various long experiment (preindustrial control and Last Millennium) and anthropogenically forced simulations of the twenty-first century (RCP2.6 and RCP8.5). There is no systematic increase in the magnitude of simulated extremes corresponding to the length of model simulations, although many realizations reveal higher magnitude extremes compared to those observed, suggesting that the duration of the instrumental record may not capture the potential severity of stochastically driven extremes. A coherent increase in both wet and dry extremes is simulated throughout Australian regions in high greenhouse gas emissions scenarios, demonstrating a forced hydrological response.
    publisherAmerican Meteorological Society
    titleAssessing the Stationarity of Australian Precipitation Extremes in Forced and Unforced CMIP5 Simulations
    typeJournal Paper
    journal volume31
    journal issue1
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-17-0393.1
    journal fristpage131
    journal lastpage145
    treeJournal of Climate:;2017:;volume( 031 ):;issue: 001
    contenttypeFulltext
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