Assessing the Stationarity of Australian Precipitation Extremes in Forced and Unforced CMIP5 SimulationsSource: Journal of Climate:;2017:;volume( 031 ):;issue: 001::page 131Author:Lewis, Sophie C.
DOI: 10.1175/JCLI-D-17-0393.1Publisher: 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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| contributor author | Lewis, Sophie C. | |
| date accessioned | 2018-01-03T11:01:56Z | |
| date available | 2018-01-03T11:01:56Z | |
| date copyright | 10/5/2017 12:00:00 AM | |
| date issued | 2017 | |
| identifier other | jcli-d-17-0393.1.pdf | |
| identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4246300 | |
| description 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. | |
| publisher | American Meteorological Society | |
| title | Assessing the Stationarity of Australian Precipitation Extremes in Forced and Unforced CMIP5 Simulations | |
| type | Journal Paper | |
| journal volume | 31 | |
| journal issue | 1 | |
| journal title | Journal of Climate | |
| identifier doi | 10.1175/JCLI-D-17-0393.1 | |
| journal fristpage | 131 | |
| journal lastpage | 145 | |
| tree | Journal of Climate:;2017:;volume( 031 ):;issue: 001 | |
| contenttype | Fulltext |