Realism of the Indian Ocean Dipole in CMIP5 Models: The Implications for Climate Projections

Weller, Evan; Cai, Wenju

doi:10.1175/jcli-d-12-00807.1

Cited by 64 publications

(46 citation statements)

References 29 publications

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“…The IOD is not defined using EOF analysis-as without detrending prior to analysis (as in Weller and Cai 2013), the IOD and a basinwide IOD-like warming mode are poorly separated , leading to an ambiguous IOD signal. The ENSO index is defined as the principal component time series of the first EOF of SST anomalies in the tropical Pacific Ocean, over 208S-208N, 1208E-808W (similar to Saji and Yamagata 2003).…”

Section: Methodsmentioning

confidence: 99%

Did Climate Change–Induced Rainfall Trends Contribute to the Australian Millennium Drought?

et al. 2014

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The Australian decade-long ''Millennium Drought'' broke in the summer of 2010/11 and was considered the most severe drought since instrumental records began in the 1900s. A crucial question is whether climate change played a role in inducing the rainfall deficit. The climate modes in question include the Indian Ocean dipole (IOD), affecting southern Australia in winter and spring; the southern annular mode (SAM) with an opposing influence on southern Australia in winter to that in spring; and El Niño-Southern Oscillation, affecting northern and eastern Australia in most seasons and southeastern Australia in spring through its coherence with the IOD. Furthermore, the poleward edge of the Southern Hemisphere Hadley cell, which indicates the position of the subtropical dry zone, has possible implications for recent rainfall declines in autumn. Using observations and simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), it is shown that the drought over southwest Western Australia is partly attributable to a long-term upward SAM trend, which contributed to half of the winter rainfall reduction in this region. For southeast Australia, models simulate weak trends in the pertinent climate modes. In particular, they severely underestimate the observed poleward expansion of the subtropical dry zone and associated impacts. Thus, although climate models generally suggest that Australia's Millennium Drought was mostly due to multidecadal variability, some late-twentieth-century changes in climate modes that influence regional rainfall are partially attributable to anthropogenic greenhouse warming.

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Section: Methodsmentioning

confidence: 99%

Did Climate Change–Induced Rainfall Trends Contribute to the Australian Millennium Drought?

et al. 2014

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“…Following Weller and Cai (2013), we measure the amplitude (units of Celsius) of the IOD as the standard deviation of the EOF spatial pattern (scaled as indicated). We also compute the total fraction of variability that the IOD accounts for.…”

Section: Impact On the Iodmentioning

confidence: 99%

The impact of stochastic parametrisations on the representation of the Asian summer monsoon

Strommen¹,

Christensen

Berner

et al. 2017

Clim Dyn

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“…The teleconnection patterns from ENSO to rainfall over Australia are reasonably well s imulated in the key September-November season (Cai et al 2009;Weller and Cai 2013b) in the CMIP3 and CMIP5 multi-model mean. Figure 11 shows the ranked list of the skill of this relationship in both CMIP3 and CMIP5 models.…”

Section: The El Niño-southern Oscillationmentioning

confidence: 73%

Evaluation of CMIP3 and CMIP5 models over the Australian region to inform confidence in projections

Moise¹,

Wilson²,

Grose³

et al. 2015

AMOJ

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Model evaluation is an important tool to help rate confidence in climate model simulations. This can add to the overall confidence assessment for future projections of the Australian climate. Additionally it can highlight significant model deficiencies that may affect the selection of a subset of models for use in impact assessment.Here we present results from an extensive model evaluation undertaken as part of the Natural Resource Management (NRM) Project in order to inform the newest set of climate change projections for Australia.The assessment covers mean climate skill over Australia as well as variability measures and teleconnections from up to 47 CMIP5 models and 23 CMIP3 models (for comparison where appropriate). Additionally, the skill in representing important climate features such as MJO, SAM, blocking and cut-off lows are also reviewed. Selected extremes are evaluated as well as simulations of two different types of downscaling simulations used within the NRM project. Finally, an attempt is made to synthesise this information in order to highlight a small group of CMIP5 models which show consistent deficiencies in representing the Australian climate and its features.

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Realism of the Indian Ocean Dipole in CMIP5 Models: The Implications for Climate Projections

Cited by 64 publications

References 29 publications

Did Climate Change–Induced Rainfall Trends Contribute to the Australian Millennium Drought?

Did Climate Change–Induced Rainfall Trends Contribute to the Australian Millennium Drought?

The impact of stochastic parametrisations on the representation of the Asian summer monsoon

Evaluation of CMIP3 and CMIP5 models over the Australian region to inform confidence in projections

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