ORCID Profile
0000-0002-1158-2427
Current Organisation
Australian Bureau of Meteorology
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Publisher: American Meteorological Society
Date: 03-2019
Abstract: El Niño and La Niña, the warm and cold phases of El Niño–Southern Oscillation (ENSO), cause significant year-to-year disruptions in global climate, including in the atmosphere, oceans, and cryosphere. Australia is one of the countries where its climate, including droughts and flooding rains, is highly sensitive to the temporal and spatial variations of ENSO. The dramatic impacts of ENSO on the environment, society, health, and economies worldwide make the application of reliable ENSO predictions a powerful way to manage risks and resources. An improved understanding of ENSO dynamics in a changing climate has the potential to lead to more accurate and reliable ENSO predictions by facilitating improved forecast systems. This motivated an Australian national workshop on ENSO dynamics and prediction that was held in Sydney, Australia, in November 2017. This workshop followed the aftermath of the 2015/16 extreme El Niño, which exhibited different characteristics to previous extreme El Niños and whose early evolution since 2014 was challenging to predict. This essay summarizes the collective workshop perspective on recent progress and challenges in understanding ENSO dynamics and predictability and improving forecast systems. While this essay discusses key issues from an Australian perspective, many of the same issues are important for other ENSO-affected countries and for the international ENSO research community.
Publisher: American Geophysical Union (AGU)
Date: 25-08-2017
DOI: 10.1002/2017GL074244
Publisher: American Meteorological Society
Date: 06-2017
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.
Publisher: American Meteorological Society
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 02-01-2019
DOI: 10.1038/S41467-018-07689-7
Abstract: After exhibiting an upward trend since 1979, Antarctic sea ice extent (SIE) declined dramatically during austral spring 2016, reaching a record low by December 2016. Here we show that a combination of atmospheric and oceanic phenomena played primary roles for this decline. The anomalous atmospheric circulation was initially driven by record strength tropical convection over the Indian and western Pacific Oceans, which resulted in a wave-3 circulation pattern around Antarctica that acted to reduce SIE in the Indian Ocean, Ross and Bellingshausen Sea sectors. Subsequently, the polar stratospheric vortex weakened significantly, resulting in record weakening of the circumpolar surface westerlies that acted to decrease SIE in the Indian Ocean and Pacific Ocean sectors. These processes appear to reflect unusual internal atmosphere-ocean variability. However, the warming trend of the tropical Indian Ocean, which may partly stem from anthropogenic forcing, may have contributed to the severity of the 2016 SIE decline.
Publisher: Springer Science and Business Media LLC
Date: 30-04-2010
Publisher: American Meteorological Society
Date: 15-08-2007
DOI: 10.1175/JCLI4228.1
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.
Publisher: American Meteorological Society
Date: 12-2016
Publisher: Springer Science and Business Media LLC
Date: 07-2018
DOI: 10.1038/S41586-018-0252-6
Abstract: El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño-Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.
Publisher: Springer Science and Business Media LLC
Date: 07-05-2001
Publisher: American Meteorological Society
Date: 11-2009
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 in idual 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.
Publisher: American Meteorological Society
Date: 02-09-2016
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 lify 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.
Publisher: American Geophysical Union (AGU)
Date: 10-2009
DOI: 10.1029/2009GL040100
Publisher: Elsevier BV
Date: 04-2012
Publisher: Wiley
Date: 12-06-2015
DOI: 10.1002/JOC.4395
Publisher: American Meteorological Society
Date: 15-05-2009
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 litude 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 in idual 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.
Publisher: Springer Science and Business Media LLC
Date: 28-09-2016
Publisher: Springer Science and Business Media LLC
Date: 20-11-2022
Publisher: American Meteorological Society
Date: 04-2002
Publisher: Springer Science and Business Media LLC
Date: 20-02-2019
DOI: 10.1038/S41586-019-0994-9
Abstract: In this Review, the middle initial of author Kim M. Cobb was omitted. The original Review has been corrected online.
Publisher: American Geophysical Union (AGU)
Date: 13-01-2016
DOI: 10.1002/2015GL066984
Publisher: American Meteorological Society
Date: 2019
Publisher: Springer Science and Business Media LLC
Date: 14-04-2009
Publisher: American Meteorological Society
Date: 12-2015
Publisher: Springer Science and Business Media LLC
Date: 25-02-2010
Publisher: Springer Science and Business Media LLC
Date: 28-10-2010
Publisher: Springer Science and Business Media LLC
Date: 27-08-2020
No related grants have been discovered for Guomin Wang.