Search

ACCESS-S2 is a major upgrade to the Australian Bureau of Meteorology’s multi-week to seasonal prediction system. It was made operational in October 2021, replacing ACCESS-S1. The focus of the upgrade is the addition of a new weakly coupled data assimilation system to provide initial conditions for atmosphere, ocean, land and ice fields. The model is based on the UK Met Office GloSea5-GC2 seasonal prediction system and is unchanged from ACCESS-S1, aside from minor corrections and enhancements. The performance of the assimilation system and the skill of the seasonal and multi-week forecasts have been assessed and compared to ACCESS-S1. There are improvements in the ACCESS-S2 initial conditions compared to ACCESS-S1, particularly for soil moisture and aspects of the ocean, notably the ocean currents. More realistic soil moisture initialisation has led to increased skill for forecasts over Australia, especially those of maximum temperature. The ACCESS-S2 system is shown to have increased skill of El Nino–Southern Oscillation forecasts over ACCESS-S1 during the challenging autumn forecast period. Analysis suggests that ACCESS-S2 will deliver improved operational forecast accuracy in comparison to ACCESS-S1. Assessments of the operational forecasts are underway. ACCESS-S2 represents another step forward in the development of seasonal forecast systems at the Bureau of Meteorology. However, key rainfall and sea surface temperature biases in ACCESS-S1 remain in ACCESS-S2, indicating where future efforts should be focused.

A phenomenon referred to here as Java–Sumatra Niño/Niña (JSN or JS Niño/Niña) is characterized by the appearance of warm/cold sea surface temperature anomalies (SSTAs) in the coastal upwelling region off Java–Sumatra in the southeastern equatorial Indian Ocean. JSN develops in July–September and sometimes as a precursor to the Indian Ocean dipole, but often without corresponding SSTAs in the western equatorial Indian Ocean. Although its spatiotemporal evolution varies considerably between individual events, JSN is essentially an intrinsic mode of variability driven by local atmosphere–ocean positive feedback, and thus does not rely on remote forcing from the Pacific for its emergence. JSN is an important driver of climate variability over the tropical Indian Ocean and the surrounding continents. Notably, JS Niña events developing in July–September project onto the South and Southeast Asian summer monsoons, increasing the probability of heavy rainfall and flooding across the most heavily populated regions of the world.

The austral spring climate of 2020 was characterised by the occurrence of La Niña, which is the most predictable climate driver of Australian springtime rainfall. Consistent with this La Niña, the Bureau of Meteorology’s dynamical sub-seasonal to seasonal forecast system, ACCESS-S1, made highly confident predictions of wetter-than-normal conditions over central and eastern Australia for spring when initialised in July 2020 and thereafter. However, many areas of Australia received near average to severely below average rainfall, particularly during November. Possible causes of the deviation of rainfall from its historical response to La Niña and causes of the forecast error are explored with observational and reanalysis data for the period 1979–2020 and real-time forecasts of ACCESS-S1 initialised in July to November 2020. Several compounding factors were identified as key contributors to the drier-than-anticipated spring conditions. Although the ocean surface to the north of Australia was warmer than normal, which would have acted to promote rainfall over northern Australia, it was not as warm as expected from its historical relationship with La Niña and its long-term warming trend. Moreover, a negative phase of the Indian Ocean Dipole mode, which typically acts to increase spring rainfall in southern Australia, decayed earlier than normal in October. Finally, the Madden–Julian Oscillation activity over the equatorial Indian Ocean acted to suppress rainfall across northern and eastern Australia during November. While ACCESS-S1 accurately predicted the strength of La Niña over the Niño3.4 region, it over-predicted the ocean warming to the north of Australia and under-predicted the strength of the November MJO event, leading to an over-prediction of the Australian spring rainfall and especially the November-mean rainfall.

This study offers an overview of the low-frequency (i.e., monthly to seasonal) evolution, dynamics, predictability, and surface impacts of a rare Southern Hemisphere (SH) stratospheric warming that occurred in austral spring 2019. Between late August and mid-September 2019, the stratospheric circumpolar westerly jet weakened rapidly, and Antarctic stratospheric temperatures rose dramatically. The deceleration of the vortex at 10 hPa was as drastic as that of the first-ever-observed major sudden stratospheric warming in the SH during 2002, while the mean Antarctic warming over the course of spring 2019 broke the previous record of 2002 by ∼50% in the midstratosphere. This event was preceded by a poleward shift of the SH polar night jet in the uppermost stratosphere in early winter, which was then followed by record-strong planetary wave-1 activity propagating upward from the troposphere in August that acted to dramatically weaken the polar vortex throughout the depth of the stratosphere. The weakened vortex winds and elevated temperatures moved downward to the surface from mid-October to December, promoting a record strong swing of the southern annular mode (SAM) to its negative phase. This record-negative SAM appeared to be a primary driver of the extreme hot and dry conditions over subtropical eastern Australia that accompanied the severe wildfires that occurred in late spring 2019. State-of-the-art dynamical seasonal forecast systems skillfully predicted the significant vortex weakening of spring 2019 and subsequent development of negative SAM from as early as late July.

Interannual variability of the Southern Hemisphere subtropical jet (STJ) is assessed using atmospheric reanalyses during 1979–2018. The focus is on the austral winter season when the STJ is strongest and most distinct from the midlatitude eddy-driven jet (EDJ). Variations in the intensity and latitudinal position of the STJ are diagnosed using an index developed to discriminate between variations associated with the EDJ. STJ intensity and position variations are found to be tied to different mechanisms. An intensification of the STJ is associated with enhanced divergent outflow from diabatic heating over the equatorial Pacific Ocean, primarily resulting from eastern Pacific or canonical El Niño. This intensification is associated with a narrowing of the STJ and an in-place weakening of the EDJ. An equatorward-shifted STJ, however, appears to be eddy driven and is associated with an acceleration and poleward displacement of the EDJ, which projects onto the positive polarity of the southern annular mode. As has previously been reported, El Niño Modoki (or central Pacific El Niño) can act to shift the EDJ poleward during austral winter; thus, a possible pathway for changes in the position of the STJ is via tropically forced changes in the position of the EDJ. In contrast to previous studies, we also highlight a weakening and poleward shift of the STJ in association with an expansion of the Hadley circulation.

We explore the causes and predictability of extreme low minimum temperatures (Tmin) that occurred across northern and eastern Australia in September 2019. Historically, reduced Tmin is related to the occurrence of a positive Indian Ocean Dipole (IOD) and central Pacific El Nino. Positive IOD events tend to locate an anomalous anticyclone over the Great Australian Bight, therefore inducing cold advection across eastern Australia. Positive IOD and central Pacific El Nino also reduce cloud cover over northern and eastern Australia, thus enhancing radiative cooling at night-time. During September 2019, the IOD and central Pacific El Nino were strongly positive, and so the observed Tmin anomalies are well reconstructed based on their historical relationships with the IOD and central Pacific El Nino. This implies that September 2019 Tmin anomalies should have been predictable at least 1–2 months in advance. However, even at zero lead time the Bureau of Metereorolgy ACCESS-S1 seasonal prediction model failed to predict the anomalous anticyclone in the Bight and the cold anomalies in the east. Analysis of hindcasts for 1990–2012 indicates that the model's teleconnections from the IOD are systematically weaker than the observed, which likely stems from mean state biases in sea surface temperature and rainfall in the tropical Indian and western Pacific Oceans. Together with this weak IOD teleconnection, forecasts for earlier-than-observed onset of the negative Southern Annular Mode following the strong polar stratospheric warming that occurred in late August 2019 may have contributed to the Tmin forecast bust over Australia for September 2019.

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.

Australian maximum temperatures have reached record values in recent austral springs and are projected to increase further in a warming world. We focus on three record spring heat events in September 2013, October–November 2014 and October 2015, and examine the anomalous atmospheric circulation associated with these events in reanalysis and a sub-seasonal to seasonal prediction system, POAMA, to identify factors contributing to extreme heat over Australia. We find that an anomalous equivalent barotropic cyclonic circulation southwest of Australia and a quasi-stationary wave train formed by an upper-troposphere anticyclonic circulation over southern Australia and barotropic cyclone southeast of Australia are important features in these heat events, though the wave train was only observed in the latter two events. This wave train appears to be linked to the tropics, and particularly the tropical Indian Ocean, suggesting that teleconnections to the tropical Indian Ocean can be important for monthly spring extreme heat formation in Australia. However, the forecast relationship with the tropical Pacific Ocean was over-represented at the cost of the relationship between the Indian Ocean and upper-troposphere anomaly, limiting the ability of POAMA to forecast the full extent of the month- or 2 month-long heat extremes at zero lead time. This means that the model might underestimate the magnitude of future extreme heat events in spring, a factor that should be assessed in the next generation of seasonal forecast models.

Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere–troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could further benefit these rapidly evolving predictions., Atmospheric Chemistry and Physics, 22 (4), ISSN:1680-7375, ISSN:1680-7367

The Southern Hemisphere summertime eddy-driven jet and storm tracks have shifted poleward over the recent few decades. In previous studies, explanations have mainly stressed the influence of external forcing in driving this trend. Here we examine the role of internal tropical SST variability in controlling the austral summer jet’s poleward migration, with a focus on interdecadal time scales. The role of external forcing and internal variability are isolated by using a hierarchy of Community Earth System Model version 1 (CESM1) simulations, including the pre-industrial control, large ensemble, and pacemaker runs. Model simulations suggest that in the early twenty-first century, both external forcing and internal tropical Pacific SST variability are important in driving a positive southern annular mode (SAM) phase and a poleward migration of the eddy-driven jet. Tropical Pacific SST variability, associated with the negative phase of the interdecadal Pacific oscillation (IPO), acts to shift the jet poleward over the southern Indian and southwestern Pacific Oceans and intensify the jet in the southeastern Pacific basin, while external forcing drives a significant poleward jet shift in the South Atlantic basin. In response to both external forcing and decadal Pacific SST variability, the transient eddy momentum flux convergence belt in the middle latitudes experiences a poleward migration due to the enhanced meridional temperature gradient, leading to a zonally symmetric southward migration of the eddy-driven jet. This mechanism distinguishes the influence of the IPO on the midlatitude circulation from the dynamical impact of ENSO, with the latter mainly promoting the subtropical wave-breaking critical latitude poleward and pushing the midlatitude jet to higher latitudes.

Seasonal climate prediction to date has largely focussed on probabilistic forecasts for above- and below-average conditions in climate means. Here, we examine the possibility of making sub-seasonal to seasonal outlooks for daily-scale precipitation extremes in Australia. We first use observational data to show that significant relationships exist between climate modes, such as the El Nino–Southern Oscillation, and indices representing rainfall extremes across much of Australia. The strong observed teleconnections between climate modes and daily rainfall extremes suggest the potential for predictability on seasonal scales. The current Australian Bureau of Meteorology seasonal prediction system (ACCESS-S1) is examined for performance in predicting rainfall extreme indices using a range of measures. Ensemble hindcasts, consisting of 11 members initialised every month during 1990–2012, perform well for some extreme rainfall indices on short lead-times (up to 1 month). We note that at short lead-times, forecasts are aided by skilful weather prediction, so forecast performance drops at lead-times of a week or more. Forecast performance is lower in austral summer than other seasons and greater in the north and interior of the continent, particularly in the dry season, than elsewhere. The ACCESS-S1 ensemble is overconfident but exhibits some reliability in probabilistic forecasts of above- or below-average number of wet days and intensity of the highest daily maximum precipitation, especially in northern Australia. ACCESS-S1 captures the broad pattern of relationships between climate modes and rainfall extremes that are observed. For two case-studies of unusually extreme precipitation, ACCESS-S exhibits contrasting performance for forecasts of extreme rainfall anomalies beyond the first month. These results suggest that ACCESS-S1 may be used to produce outlooks for some rainfall indices, such as the number of wet days and the intensity of the wettest day, for the month ahead.

Major disruptions of the winter season, high-latitude, stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research. We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortices in sub-seasonal to seasonal forecast models. Based on a set of controlled, subseasonal, ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models, and fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts.

Geoscientific Model Development, 15 (13), ISSN:1991-9603, ISSN:1991-959X

Observational records show that occurrences of the negative polarity of the Southern Annular Mode (low SAM) is significantly linked to El Niño during austral spring and summer, potentially providing long-lead predictability of the SAM and its associated surface climate conditions. In this study, we explore how this linkage may change under a scenario of a continuation of the ocean temperature trends that have been observed over the past 60 years, which are plausibly forced by increasing greenhouse gas concentrations. We generated coupled model seasonal forecasts for three recent extreme El Niño events by initialising the forecasts with observed ocean anomalies of 1 September 1982, 1997 and 2015 added into (1) the current ocean mean state and into (2) the ocean mean state updated to include double the recent ocean temperature trends. We show that the strength of extreme El Niño is reduced with the warmer ocean mean state as a result of reduced thermocline feedback and weakened rainfall-wind-sea surface temperature coupling over the tropical eastern Pacific. The El Niño-low SAM relationship also weakens, implying the possibility of reduced long-lead predictability of the SAM and associated surface climate impacts in the future.

Over recent years there have been parallel advances in the development of stratosphere resolving numerical models, our understanding of stratosphere-troposphere interaction and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing new and improved capability in long range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal and decadal climate predictions. We end with an outlook towards the future of climate forecasts and identify areas for improvement that could further benefit these rapidly evolving predictions.

A phenomenon referred to here as Java-Sumatra Niño/Niña (JSN or JS Niño/Niña) is characterized by the appearance of warm/cold sea surface temperature anomalies (SSTAs) in the coastal upwelling region off Java-Sumatra in the southeastern equatorial Indian Ocean. JSN develops in July-September and sometimes as a precursor to the Indian Ocean Dipole, but often without corresponding SSTAs in the western equatorial Indian Ocean. Although its spatiotemporal evolution varies considerably between individual events, JSN is essentially an intrinsic mode of variability driven by local atmosphere-ocean positive feedback, and thus does not rely on remote forcing from the Pacific for its emergence. JSN is an important driver of climate variability over the tropical Indian Ocean and the surrounding continents. Notably, JS Niña events developing in July-September project onto the South and Southeast Asian summer monsoons, increasing the probability of heavy rainfall and flooding across the most heavily populated regions of the world.

The occurrence of extreme hot and dry conditions in warm seasons can have large impacts on human health, energy and water supplies, agriculture and wildfires. Australian hot and dry extremes have been known to be associated with the occurrence of El Nino and other variations of tropospheric circulation. Here we identify an additional driver: variability of the stratospheric Antarctic polar vortex. On the basis of statistical analyses using observational data covering the past 40 yr, we show that weakenings and warmings of the stratospheric polar vortex, which episodically occur during austral spring, substantially increase the chances of hot and dry extremes and of associated fire-conducive weather across subtropical eastern Australia from austral spring to early summer. The promotion of these Australian climate extremes results from the downward coupling of the weakened polar vortex to tropospheric levels, where it is linked to the low-index polarity of the Southern Annular Mode, an equatorward shift of the mid-latitude westerly jet stream and subsidence and warming in the subtropics. Because of the long timescale of the polar vortex variations, the enhanced likelihood of early-summertime hot and dry extremes and wildfire risks across eastern Australia may be predictable a season in advance during years of vortex weakenings. Hot and dry climate extremes in Australia are linked to stratospheric polar vortex weakening, with potential implications for their predictability, according to statistical analyses of observational data from the past 40 years.

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.

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., Antarctic sea ice extent declined dramatically in austral spring 2016. This study shows the decline was initially driven by tropical convection resulting in a wave-3 circulation pattern, followed by weakened circumpolar surface westerlies initialised in the polar stratospheric vortex.

Stratosphere-troposphere coupling in the Southern Hemisphere (SH) polar vortex is an important dynamical process that provides predictability of the tropospheric Southern Annular Mode (SAM) and its associated surface impacts. SH stratosphere-troposphere coupling is explored by height-time domain empirical orthogonal function (EOF) analysis applied to the zonal mean-zonal wind anomalies averaged over the Antarctic circumpolar region (55–65°S; U55–65°S). The leading EOF explains 42% of the height-time variance of U55–65°S and depicts the variations of the vortex that is tightly tied to the seasonal breakdown of the vortex during late spring. The leading EOF pattern, defined here as the stratosphere-troposphere coupled mode, is characterized by variations in U55–65°S that develop in early winter near the stratopause, change sign from late winter to early spring, gain maximum amplitude during October in the upper stratosphere, and then extend downward to the surface from October to January. This stratosphere-troposphere coupling during the spring months appears to be preconditioned by anomalies in upward propagating planetary wave activity and a meridional shift of the vortex as high as the stratopause and as early as June. Interannual variations of the stratosphere-troposphere coupled mode are highly correlated with those of the tropospheric SAM, Antarctic stratospheric ozone concentration, Antarctic sea ice concentrations in the South Pacific and the Weddell Sea, and SH regional climate during late spring–early summer. Anomalies in the upper stratospheric flow as early as June are thus a potentially important source of predictability for the tropospheric SAM and its associated impacts on surface climate in spring and summer.

Observational records show that occurrences of the negative polarity of the Southern Annular Mode (low SAM) is significantly linked to El Niño during austral spring and summer, potentially providing long-lead predictability of the SAM and its associated surface climate conditions. In this study, we explore how this linkage may change under a scenario of a continuation of the ocean temperature trends that have been observed over the past 60 years, which are plausibly forced by increasing greenhouse gas concentrations. We generated coupled model seasonal forecasts for three recent extreme El Niño events by initialising the forecasts with observed ocean anomalies of 1 September 1982, 1997 and 2015 added into (1) the current ocean mean state and into (2) the ocean mean state updated to include double the recent ocean temperature trends. We show that the strength of extreme El Niño is reduced with the warmer ocean mean state as a result of reduced thermocline feedback and weakened rainfall-wind-sea surface temperature coupling over the tropical eastern Pacific. The El Niño-low SAM relationship also weakens, implying the possibility of reduced long-lead predictability of the SAM and associated surface climate impacts in the future.

The stratosphere can have a significant impact on winter surface weather on subseasonal to seasonal (S2S) timescales. This study evaluates the ability of current operational S2S prediction systems to capture two important links between the stratosphere and troposphere: (1) changes in probabilistic prediction skill in the extratropical stratosphere by precursors in the tropics and the extratropical troposphere and (2) changes in surface predictability in the extratropics after stratospheric weak and strong vortex events. Probabilistic skill exists for stratospheric events when including extratropical tropospheric precursors over the North Pacific and Eurasia, though only a limited set of models captures the Eurasian precursors. Tropical teleconnections such as the Madden‐Julian Oscillation, the Quasi‐Biennial Oscillation, and El Niño–Southern Oscillation increase the probabilistic skill of the polar vortex strength, though these are only captured by a limited set of models. At the surface, predictability is increased over the United States, Russia, and the Middle East for weak vortex events, but not for Europe, and the change in predictability is smaller for strong vortex events for all prediction systems. Prediction systems with poorly resolved stratospheric processes represent this skill to a lesser degree. Altogether, the analyses indicate that correctly simulating stratospheric variability and stratosphere‐troposphere dynamical coupling are critical elements for skillful S2S wintertime predictions. ISSN:0148-0227 ISSN:2169-897X

Observed long-term variations in summer season timing and length in the Northern Hemisphere (NH) continents and their subregions were analyzed using temperature-based indices. The climatological mean showed coastal–inland contrast; summer starts and ends earlier inland than in coastal areas because of differences in heat capacity. Observations for the past 60 years (1953–2012) show lengthening of the summer season with earlier summer onset and delayed summer withdrawal across the NH. The summer onset advance contributed more to the observed increase in summer season length in many regions than the delay of summer withdrawal. To understand anthropogenic and natural contributions to the observed change, summer season trends from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel simulations forced with the observed external forcings [anthropogenic plus natural forcing (ALL), natural forcing only (NAT), and greenhouse gas forcing only (GHG)] were analyzed. ALL and GHG simulations were found to reproduce the overall observed global and regional lengthening trends, but NAT had negligible trends, which implies that increased greenhouse gases were the main cause of the observed changes. However, ALL runs tend to underestimate the observed trend of summer onset and overestimate that of withdrawal, the causes of which remain to be determined. Possible contributions of multidecadal variabilities, such as Pacific decadal oscillation and Atlantic multidecadal oscillation, to the observed regional trends in summer season length were also assessed. The results suggest that multidecadal variability can explain a moderate portion (about ±10%) of the observed trends in summer season length, mainly over the high latitudes.

The stratosphere has been identified as an important source of predictability for a range of processes on subseasonal to seasonal (S2S) time scales. Knowledge about S2S predictability within the stratosphere is however still limited. This study evaluates to what extent predictability in the extratropical stratosphere exists in hindcasts of operational prediction systems in the S2S database. The stratosphere is found to exhibit extended predictability as compared to the troposphere. Prediction systems with higher stratospheric skill tend to also exhibit higher skill in the troposphere. The analysis also includes an assessment of the predictability for stratospheric events, including early and midwinter sudden stratospheric warming events, strong vortex events, and extreme heat flux events for the Northern Hemisphere and final warming events for both hemispheres. Strong vortex events and final warming events exhibit higher levels of predictability as compared to sudden stratospheric warming events. In general, skill is limited to the deterministic range of 1 to 2 weeks. High‐top prediction systems overall exhibit higher stratospheric prediction skill as compared to their low‐top counterparts, pointing to the important role of stratospheric representation in S2S prediction models. ISSN:0148-0227 ISSN:2169-897X

During 2017–2019, drought existed in many parts of Australia with varying degrees of severity and varied timing of development and intensification. In a broad sense, the surface climate conditions went from anomalously wet in 2016 to an official government-declared drought from the end of 2017. The drought subsequently intensified further to become most severe in mid to late 2019. Here we explore the more detailed evolution of the 2019 conditions over subtropical eastern Australia and infer its predictability through linear relationships with large-scale climate drivers. To monitor the detailed drought evolution, we use the Evaporative Stress Index (ESI) computed over a 4-week running window on a 5 km grid. Flash drought onset is defined as when there is a rapid decline in the ESI that is sustained over at least 2 weeks which ends in drought conditions. For the Central Slopes area of the upper Darling River basin, flash drought onset occurred in June, persisted over 6 months, and rapidly terminated through a flash recovery in February 2020. In the far east of Australia (East Coast regions), flash drought onset was identified later, in November and December. For the Central Slopes area, less than half the magnitude of the flash drought development in June could be explained through linear relationships with the positive Indian Ocean Dipole mode (IOD) and the central Pacific El Nino, together with the long-term trend in ESI in the region. Similarly, only about half the magnitude of the East Coast flash drought developments in November and December could be explained by the ongoing positive IOD, central Pacific El Nino, negative Southern Annular Mode, and ongoing global warming trend. Therefore, although these large-scale drivers set the stage for the likelihood of drought, successful prediction of flash drought will require more local and current information than those large-scale climate drivers alone.

ACCESS-S1 will be the next version of the Australian Bureau of Meteorology's seasonal prediction system, due to become operational in early 2018. The multiweek and seasonal performance of ACCESS-S1 has been evaluated based on a 23-year hindcast set and compared to the current operational system, POAMA. The system has considerable enhancements compared to POAMA, including higher vertical and horizontal resolution of the component models and state-ofthe-art physics parameterisation schemes. ACCESS-S1 is based on the UK Met Office GloSea5-GC2 seasonal prediction system, but has enhancements to the ensemble generation strategy to make it appropriate for multi-week forecasting, and a larger ensemble size. ACCESS-S1 has markedly reduced biases in the mean state of the climate, both globally and over Australia, compared to POAMA. ACCESS-S1 also better predicts the early stages of the development of the El Niño Southern Oscillation (through the predictability barrier) and the Indian Ocean Dipole, as well as multi-week variations of the Southern Annular Mode and the Madden-Julian Oscillation — all important drivers of Australian climate variability. There is an overall improvement in the skill of the forecasts of rainfall, maximum temperature (Tmax) and minimum temperature (Tmin) over Australia on multi-week timescales compared to POAMA. On seasonal timescales the differences between the two systems are generally less marked. ACCESS-S1 has improved seasonal forecasts over Australia for the austral spring season compared to POAMA, with particularly good forecast reliability for rainfall and Tmax. However, forecasts of seasonal mean Tmax are noticeably less skilful over eastern Australia for forecasts of late autumn and winter compared to POAMA. The study has identified scope for improvement of ACCESS-S in the future, particularly 1) reducing rainfall errors in the Indian Ocean and Maritime Continent regions, and 2) initialising the land surface with realistic soil moisture rather than climatology. The latter impacts negatively on the skill of the temperature forecasts over eastern Australia and is being addressed in the next version of the system, ACCESS-S2.

The 30 year period 1985–2014 experienced a swing of the Inter-decadal Pacific Oscillation (IPO) from the warm phase to the cold phase. Here we investigate variation of the relation between El Nino and the Southern Oscillation (ENSO) and the Indian Ocean Dipole mode (IOD) and resultant changes in the predictability of the IOD and south-eastern Australian (SEA) springtime rainfall associated with this swing in the IPO. Using observational analyses, we show that during the warm phase of the IPO in the 1980s–1990s, the amplitudes of ENSO and the IOD were large, and the correlation between them was high; thus predictability of the IOD was high. Nevertheless, during these decades SEA spring rainfall was only weakly related to ENSO and the IOD, and therefore predictability of SEA rainfall was low. In contrast, during the cold phase of the IPO in the 2000s, the opposite was found: the IOD occurred more independently from ENSO, so the IOD was less predictable. Nonetheless, SEA spring rainfall was more strongly related to ENSO and the IOD, and therefore, SEA rainfall was more predictable in the 2000s than in the 1980s–1990s. The cause of this decadal variation in the relationship of SEA rainfall with ENSO and the IOD between the recent warm and cold states of the IPO appears to be a systematic zonal variation of the rainfall anomalies in the tropical Indo-Pacific associated with the IOD and ENSO and related changes in the Rossby wave train path over Australia.

Australia experienced record high rainfall in austral spring 2010, which has previously been attributed to the concurrence of a strong La Nina event and a strong positive excursion of the Southern Annular Mode (SAM). In this study, we examine the role of the sea surface temperature (SST) trend over the recent 50 years, which has large warming over the tropical Indian, western Pacific and North Atlantic Oceans, in driving the extraordinary climate conditions of spring 2010, using the Australian Bureau of Meteorology coupled model seasonal forecast system. Four forecast sensitivity experiments were designed by using randomly chosen atmospheric initial conditions but with: (1) observed ocean initial conditions for 1 September 2010; (2) the same ocean initial conditions except the linear temperature trend over the period 1960–2010 was removed; (3) ocean initial conditions in which the trend was added to the climatological ocean state for 1 September; and (4) climatological ocean conditions only. A synergistic response to the La Nina SST anomalies and the SST trend was detected: the tropical rainfall anomalies were amplified over the western side of the Indo-Pacific warm-pool, which led to a significant increase of tropical upper tropospheric warming and a resultant increase of meridional temperature gradient in the Southern Hemisphere (SH) extratropics. Consequently, the SH eddy-driven jet was shifted poleward (i.e. positive phase of the SAM), which induced rainfall over subtropical Australia. Our findings highlight that the interaction of interannual anomalies and the trend may play an important role in the amplification of extreme events.

Data. Monthly maximum temperatures from the Australian Water Availability Project (AWAP) gridded dataset (Jones et al. 2009) were analyzed on a 0.25° grid over Australian land points. Observed sea surface temperatures from Hurrell et al. (2008) for 1981 and Reynolds et al. (2002) from 1982 onwards were used for the ENSO index (based on Nino-3.4 SSTs: 5°N–5°S, 170°–120°W) and the Indian Ocean dipole mode index [IOD: western pole (10°S–10°N, 50°–70°E); eastern pole (10°S–0°, 90°–110°E); Saji et al. 1999]. The SAM was calculated as the first EOF of mean sea level pressure (MSLP) anomalies over 20°–75°S (e.g., Lim et al. 2011) from the ERA-Interim reanalysis (Dee et al. 2011). Soil moisture estimates are from Raupach et al. (2009) for the upper-layer (

This study investigates the causes and predictability of the different springtime rainfall responses over Australia for El Niño in 1997 and 2002. The rainfall deficit over Australia is generally assumed to be linearly related to the strength of El Niño. However, Australia received near-normal springtime rainfall during the record strong El Niño in 1997, whereas it suffered from severe drought, especially in the east, during the weak El Niño of 2002. Statistical reconstruction of the rainfall anomalies and forecasts produced from the Australian Bureau of Meteorology’s dynamical seasonal forecast system [Predictive Ocean and Atmosphere Model for Australia (POAMA)] demonstrated that the eastward and westward shifts of the maximum SST warming of El Niño contributed to the near-normal and dry responses of Australian spring rainfall in 1997 and 2002, respectively. Hence, the contrasting rainfall responses were largely predictable. However, the dry conditions in 2002 were significantly amplified by the occurrence of the record strength negative phase of the southern annular mode (SAM), which could only be predicted with the use of realistic atmospheric initial conditions in the atmosphere–ocean coupled configuration of POAMA. Therefore, predictability of the severity of the 2002 drought over Australia was strongly constrained by the predictability of the SAM, despite the high predictability of the drier than normal condition of 2002 spring that stems from the anomalous central Pacific warming of 2002 El Niño.

In 2010 eastern Australia experienced its wettest spring on record, which has been largely attributed to a strong La Nina event in conjunction with an extraordinary positive excursion of the Southern Annular Mode (SAM). La Nina impacts would be expected to have been predictable months in advance, but predictability of the occurrence of the strong SAM is less known. We explore the predictability of the strong SAM in austral spring 2010 and its contribution to the extreme wet conditions in eastern Australia, using the Australian Bureau of Meteorology’s dynamical seasonal forecast system (POAMA2). Seasonal forecasts from POAMA2 were skilful in predicting the wet conditions over eastern Australia at up to 2 month lead time as a result of a good prediction of the impacts of the ongoing La Nina and the development of a strong positive excursion of the SAM. Forecast sensitivity experiments on initial conditions demonstrate that (1) the strong La Nina was a necessary condition for promoting the positive phase of SAM (high SAM) and the anomalous wet conditions over eastern Australia during October to November 2010; but (2) internal atmospheric processes were important for producing the moderate strength of the high SAM in September 2010 and for amplifying the strength of the high SAM forced by La Nina in October to November 2010; and (3) the strong high SAM was an important factor for the extremity of the Australian rainfall in late spring 2010. Therefore, high quality atmosphere and ocean initial conditions were both essential for the successful prediction of the extreme climate during austral spring 2010.

In the latter half of 2016 Indonesia and Australia experienced extreme wet conditions and East Africa suffered devastating drought, which have largely been attributed to the occurrence of strong negative Indian Ocean Dipole (IOD) and weak La Niña. Here we examine the causes and predictability of the strong negative IOD and its impact on the development of La Niña in 2016. Analysis on atmosphere and ocean reanalyses and forecast sensitivity experiments using the Australian Bureau of Meteorology’s dynamical seasonal forecast system reveals that this strong negative IOD, which peaked in July-September, developed primarily by the Indian Ocean surface and subsurface conditions. The long-term trend over the last 55 years in sea surface and subsurface temperatures, which is characterised by warming of the tropical Indian and western Pacific and cooling in the equatorial eastern Pacific, contributed positively to the extraordinary strength of this IOD. We further show that the strong negative IOD was a key promoter of the weak La Niña of 2016. Without the remote forcing from the IOD, this weak La Niña may have been substantially weaker because of the extraordinarily long-lasting warm surface condition over the dateline from the tail end of strong El Niño of 2015–16.

Seasonal variations of subtropical precipitation anomalies associated with the southern annular mode (SAM) are explored for the period 1979–2011. In all seasons, high-polarity SAM, which refers to a poleward-shifted eddy-driven westerly jet, results in increased precipitation in high latitudes and decreased precipitation in midlatitudes as a result of the concomitant poleward shift of the midlatitude storm track. In addition, during spring–autumn, high SAM also results in increased rainfall in the subtropics. This subtropical precipitation anomaly is absent during winter. This seasonal variation of the response of subtropical precipitation to the SAM is shown to be consistent with the seasonal variation of the eddy-induced divergent meridional circulation in the subtropics (strong in summer and weak in winter). The lack of an induced divergent meridional circulation in the subtropics during winter is attributed to the presence of the wintertime subtropical jet, which causes a broad latitudinal span of eddy momentum flux divergence due primarily to higher phase speed eddies breaking poleward of the subtropical jet and lower speed eddies not breaking until they reach the equatorward flank of the subtropical jet. During the other seasons, when the subtropical jet is less distinctive, the critical line for both high and low speed eddies is on the equatorward flank of the single jet and so breaking in the subtropics occurs over a narrow range of latitudes. The implications of these findings for the seasonality of future subtropical climate change, in which a shift to high SAM in all seasons is expected to be promoted, are discussed.

Predictability of the southern annular mode (SAM) for lead times beyond 1–2 weeks has traditionally been considered to be low because the SAM is regarded as an internal mode of variability with a typical decorrelation time of about 10 days. However, the association of the SAM with El Niño–Southern Oscillation (ENSO) suggests the potential for making seasonal predictions of the SAM. In this study the authors explore seasonal predictability and the predictive skill of SAM using observations and retrospective forecasts (hindcasts) from the Australian Bureau of Meteorology dynamical seasonal forecast system [the Predictive Ocean and Atmosphere Model for Australia, version 2 (POAMA2)]. Based on the observed seasonal relationships of the SAM with tropical sea surface temperatures, two distinctive periods of high seasonal predictability are suggested: austral late autumn to winter and late spring to early summer. Predictability of the SAM in the austral cold seasons stems from the association of the SAM with warm-pool (or Modoki/central Pacific) ENSO, whereas predictability in the austral warm seasons stems from the association of the SAM with cold-tongue (or eastern Pacific) ENSO. Using seasonal hindcasts for 1980–2010 from POAMA2, it is shown that the observed relationship between SAM and ENSO is faithfully depicted and SST variations associated with ENSO are skillfully predicted. Consequently, POAMA2 can skillfully predict the phase and amplitude of seasonal anomalies of the SAM in early summer and early winter for at least one season in advance. Zero-lead monthly forecasts of the SAM are furthermore shown to be highly skillful in almost all months, which is ascribed to predictability stemming from observed atmospheric initial conditions.

The development of a dynamical model seasonal prediction service for island nations in the tropical South Pacific is described. The forecast model is the Australian Bureau of Meteorology's Predictive Ocean–Atmosphere Model for Australia (POAMA), a dynamical seasonal forecast system. Using a hindcast set for the period 1982–2006, POAMA is shown to provide skillful forecasts of El Niño and La Niña many months in advance and, because the model faithfully simulates the spatial and temporal variability of rainfall associated with displacements of the southern Pacific convergence zone (SPCZ) and ITCZ during La Niña and El Niño, it also provides good predictions of rainfall throughout the tropical Pacific region. The availability of seasonal forecasts from POAMA should be beneficial to Pacific island countries for the production of regional climate outlooks across the region.

In 2010 eastern Australia received its highest springtime (September–November) rainfall since 1900. Based on historical relationships with sea surface temperatures (SST) and other climate indices, this record rainfall in 2010 was shown to be largely commensurate with the occurrence of a very strong La Nina event and an extreme positive excursion of the SAM. The pattern and magnitude of the tropical SST anomalies in austral spring 2010 were diagnosed to be nearly perfect to produce high rainfall across eastern Australia. Key aspects of this SST pattern were the strong cold anomaly in the central equatorial Pacific, and the strong warm anomalies in the eastern Indian Ocean and the far western Pacific to the north of Australia. Although the recent upward trend in SSTs in the western Pacific/eastern Indian Ocean warm pool accounted for about 50 % of the SST anomaly surrounding northern Australia in 2010, the contribution by the warming trend in these SSTs to the Australian rainfall anomaly in 2010 was assessed to be relatively modest. The strong positive swing in SAM was estimated to have accounted for upwards of 40 % of the regional anomaly along the central east coastal region and about 10 % of the area mean anomaly across eastern Australia. This contribution by the SAM suggests that a significant portion of the rainfall in 2010 may not have been seasonally predictable. However, predictability arising from the promotion of high SAM by the extreme La Nina event can not be ruled out.