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Guomin Wang and Harry H. Hendon

Abstract

Australia typically experiences drought during El Niño, especially across the eastern two-thirds of the continent during austral spring (September–November). There have, however, been some interesting departures from this paradigm. For instance, the near-record-strength El Niño of 1997 was associated with near-normal rainfall. In contrast, eastern Australia experienced near-record drought during the modest El Niño of 2002. This stark contrast raises the issue of how the magnitude of the drought is related to the character and magnitude of El Niño, for instance as measured by the broadscale sea surface temperature (SST) anomaly in the equatorial eastern Pacific. Internal (unpredictable) atmospheric noise is one plausible explanation for this contrasting behavior during these El Niño events. Here, the authors suggest that Australian rainfall is sensitive to the zonal distribution of SST anomalies during El Niño and, in particular, the greatest sensitivity is to the SST variations on the eastern edge of the Pacific warm pool rather than in the eastern Pacific where El Niño variations are typically largest. Positive SST anomalies maximized near the date line in 2002, but in 1997 maximum anomalies were shifted well into the eastern Pacific, where their influence on Australian rainfall appears to be less. These findings provide a plausible physical basis for the view that forecasting the strength of El Niño is not sufficient to accurately predict rainfall variations across Australia during El Niño.

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Pandora Hope, Eun-Pa Lim, Harry Hendon, and Guomin Wang
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Guomin Wang, Richard Kleeman, Neville Smith, and Faina Tseitkin

Abstract

An El Niño–Southern Oscillation (ENSO) prediction system with a coupled general circulation model and an ocean data assimilation scheme has been developed at the Australian Bureau of Meteorology Research Centre (BMRC). The coupled model consists of an R21L9 version of the BMRC climate model and a global version of the Geophysical Fluid Dynamics Laboratory modular ocean general circulation model with resolution focused in the tropical region and 25 vertical levels. A univariate statistical interpolation method, with 10-day data ingestion windows, is used to assimilate ocean temperature data and initialize the coupled model. The coupling procedure does not use any flux corrections. Hindcasts have been carried out for the period 1981–95 for each season (60 in all), for up to a lead time of 12 months. This paper will describe these initial experiments and show that the skill of sea surface temperature (SST) hindcasts in the tropical Pacific is comparable to other published coupled models. The skill of the model is strongest in the central Pacific. SST skill tends to be lower during the earlier 1990s than during 1980s in the eastern Pacific but not in the central Pacific. Since the ENSO SST anomaly in the central Pacific is the most important forcing of regional and global climate anomalies, the high SST prediction skill and its insensitivity over the hindcast period in this region in this model give grounds for optimism in the use of coupled general circulation models.

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Guomin Wang, Pandora Hope, Eun-Pa Lim, Harry H. Hendon, and Julie M Arblaster

Abstract

When record-breaking climate and weather extremes occur, decision-makers and planners want to know whether they are random natural events with historical levels of reoccurrence or are reflective of an altered frequency or intensity as a result of climate change. This paper describes a method to attribute extreme weather and climate events to observed increases in atmospheric CO2 using an initialized subseasonal to seasonal coupled global climate prediction system. Application of this method provides quantitative estimates of the contribution arising from increases in the level of atmospheric CO2 to individual weather and climate extreme events. Using a coupled subseasonal to seasonal forecast system differs from other methods because it has the merit of being initialized with the observed conditions and subsequently reproducing the observed events and their mechanisms. This can aid understanding when the reforecasts with and without enhanced CO2 are compared and communicated to a general audience. Atmosphere–ocean interactions are accounted for. To illustrate the method, we attribute the record Australian heat event of October 2015. We find that about half of the October 2015 Australia-wide temperature anomaly is due to the increase in atmospheric CO2 since 1960. This method has the potential to provide attribution statements for forecast events within an outlook period (i.e., before they occur). This will allow for informed messaging to be available as required when an extreme event occurs, which is of particular use to weather and climate services.

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Pandora Hope, Eun-Pa Lim, Guomin Wang, Harry H. Hendon, and Julie M. Arblaster
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Mei Zhao, Harry H. Hendon, Oscar Alves, Guoqiang Liu, and Guomin Wang

Abstract

Predictive skill for El Niño in the equatorial eastern Pacific across a range of forecast models declined sharply in the early twenty-first century relative to what was achieved in the late twentieth century despite ongoing improvements of forecast systems. This decline coincided with a shift in Pacific climate to an enhanced east–west surface temperature gradient across the Pacific and a stronger Walker circulation at the end of the twentieth century. Using seasonal forecast sensitivity experiments with the Australian Bureau of Meteorology coupled model POAMA2.4, the authors show that this shift in background climate acted to weaken key ocean–atmosphere feedbacks that amplify eastern Pacific El Niño, thus resulting in weaker variability that is less predictable. These results indicate that extreme El Niños, such as those that occurred in 1982/83 and 1997/98, were conditioned by the background climate and so were favored to occur in the late twentieth century. However, anticipating future changes in El Niño variability and predictability is an outstanding challenge because causes and prediction of low-frequency variations of Pacific climate have not yet been demonstrated.

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Christine T. Y. Chung, Scott B. Power, Agus Santoso, and Guomin Wang

Abstract

Naturally occurring multiyear to decadal variability is evident in rainfall, temperature, severe weather, and flood frequency around the globe. It is therefore important to understand the cause of this variability and the extent to which it can be predicted. Here internally generated decadal climate variability and its predictability potential in an ensemble of CMIP5 models are assessed. Global hot spots of subsurface ocean decadal variability are identified, revealing variability in the southern Tasman Sea that is coherent with variability in much of the Pacific Ocean and Southern Hemisphere. It is found that subsurface temperature variability in the southern Tasman Sea primarily arises in response to preceding changes in Southern Hemisphere winds. This variability is multiyear to decadal in character and is coherent with surface temperature in parts of the Southern Hemisphere up to several years later. This provides some degree of potential predictability to surface temperature in the southern Tasman Sea and surrounding regions. A few models exhibit significant correlation between subsurface variability in the southern Tasman Sea and zonally averaged precipitation south of 50°S; however, the multimodel mean does not exhibit any significant correlation between subsurface variability and precipitation. Models that exhibit stronger subsurface variability in the southern Tasman Sea also have a stronger interdecadal Pacific oscillation signal in the Pacific.

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Pandora Hope, Guomin Wang, Eun-Pa Lim, Harry H. Hendon, and Julie M. Arblaster
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Li Shi, Oscar Alves, Harry H. Hendon, Guomin Wang, and David Anderson

Abstract

The impact of stochastic intraseasonal variability on the onset of the 1997/98 El Niño was examined using a large ensemble of forecasts starting on 1 December 1996, produced using the Australian Bureau of Meteorology Predictive Ocean Atmosphere Model for Australia (POAMA) seasonal forecast coupled model. This coupled model has a reasonable simulation of El Niño and the Madden–Julian oscillation, so it provides an ideal framework for investigating the interaction between the MJO and El Niño. The experiment was designed so that the ensemble spread was simply a result of internal stochastic variability that is generated during the forecast. For the initial conditions used here, all forecasts led to warm El Niño–type conditions with the amplitude of the warming varying from 0.5° to 2.7°C in the Niño-3.4 region.

All forecasts developed an MJO event during the first 4 months, indicating that perhaps the background state favored MJO development. However, the details of the MJOs that developed during December 1996–March 1997 had a significant impact on the subsequent strength of the El Niño event. In particular, the forecasts with the initial MJOs that extended farther into the central Pacific, on average, led to a stronger El Niño, with the westerly winds in the western Pacific associated with the MJO leading the development of SST and thermocline anomalies in the central and eastern Pacific. These results imply a limit to the accuracy with which the strength of El Niño can be predicted because the details of individual MJO events matter. To represent realistic uncertainty, coupled models should be able to represent the MJO, including its propagation into the central Pacific so that forecasts produce sufficient ensemble spread.

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Eun-Pa Lim, Harry H. Hendon, Debra Hudson, Guomin Wang, and Oscar Alves

Abstract

The relationship between variations of Indo-Pacific sea surface temperatures (SSTs) and Australian springtime rainfall over the last 30 years is investigated with a focus on predictability of inter–El Niño variations of SST and associated rainfall anomalies. Based on observed data, the leading empirical orthogonal function (EOF) of Indo-Pacific SST represents mature El Niño conditions, while the second and fourth modes depict major east–west shifts of individual El Niño events. These higher-order EOFs of SST explain more rainfall variance in Australia, especially in the southeast, than does the El Niño mode. Furthermore, intense springtime droughts tend to be associated with peak warming in the central Pacific, as captured by EOFs 2 and 4, together with warming in the eastern Pacific as depicted by EOF1.

The ability to predict these inter–El Niño variations of SST and Australian rainfall is assessed with the Australian Bureau of Meteorology dynamical coupled model seasonal forecast system, the Predictive Ocean and Atmospheric Model for Australia (POAMA). A 10-member ensemble of 9-month hindcasts was generated for the period 1980–2006. For the September–November season, the leading 2 EOFs of SST are predictable with lead times of 3–6 months, while SST EOF4 is predictable out to a lead time of 1 month. The teleconnection between the leading EOFs of SST and Australian rainfall is also well depicted in the model. Based on this ability to predict major east–west variations of El Niño and the teleconnection to Australian rainfall, springtime rainfall over eastern Australia, and major drought events are predictable up to a season in advance.

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