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Rainfall bursts are relatively short-lived events that typically occur over consecutive days, up to a week. Northern Australian industries like sugar farming and beef are highly sensitive to burst activity, yet little is known about the multiweek prediction of bursts. This study evaluates summer (December–March) bursts over northern Australia in observations and multiweek hindcasts from the Bureau of Meteorology’s multiweek to seasonal system, the Australian Community Climate and Earth-System Simulator, Seasonal version 1 (ACCESS-S1). The main objective is to test ACCESS-S1’s skill to confidently predict tropical burst activity, defined as rainfall accumulation exceeding a threshold amount over three days, for the purpose of producing a practical, user-friendly burst forecast product. The ensemble hindcasts, made up of 11 members for the period 1990–2012, display good predictive skill out to lead week 2 in the far northern regions, despite overestimating the total number of summer burst days and the proportion of total summer rainfall from bursts. Coinciding with a predicted strong Madden–Julian oscillation (MJO), the skill in burst event prediction can be extended out to four weeks over the far northern coast in December; however, this improvement is not apparent in other months or over the far northeast, which shows generally better forecast skill with a predicted weak MJO. The ability of ACCESS-S1 to skillfully forecast bursts out to 2–3 weeks suggests the bureau’s recent prototype development of a burst potential forecast product would be of great interest to northern Australia’s livestock and crop producers, who rely on accurate multiweek rainfall forecasts for managing business decisions.

Monsoonal rainfall in northern Australia (AUMR) varies substantially on interannual, decadal, and longer time scales, profoundly impacting natural systems and agricultural communities. Some of this variability arises in response to sea surface temperature (SST) variability in the Indo-Pacific linked to both El Niño–Southern Oscillation (ENSO) and the interdecadal Pacific oscillation (IPO). Here we use observations to investigate unresolved issues regarding the influence of the IPO and ENSO on AUMR. Specifically, we show that during negative IPO phases, central Pacific (CP) El Niño events are associated with below-average rainfall over northeast Australia, an anomalous anticyclonic pattern to the northwest of Australia, and eastward moisture advection toward the date line. In contrast, CP La Niña events (distinct from eastern Pacific La Niña events) during negative IPO phases drive significantly wet conditions over much of northern Australia, a strengthened Walker circulation, and large-scale moisture flux convergence. During positive IPO phases, the impact of CP El Niño and CP La Niña events on AUMR is weaker. The influence of central Pacific SSTs on AUMR has been stronger during the recent (post-1999) negative IPO phase. The extent to which this strengthening is associated with climate change or merely natural internal variability is not known.

El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate fluctuations with wide-ranging socioeconomic and environmental impacts. Understanding the eastern Pacific (EP) and central Pacific (CP) El Niño response to a warmer climate is paramount, yet the role of internal climate variability in modulating their response is not clear. Using large ensembles, we find that internal variability generates a spread in the standard deviation and skewness of these two El Niño types that is similar to the spread of 17 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) that realistically simulate ENSO diversity. Based on 40 Community Earth System Model Large Ensemble (CESM-LE) and 99 Max Planck Institute for Meteorology Grand Ensemble (MPI-GE) members, unforced variability can explain more than 90% of the historical EP and CP El Niño standard deviation and all of the ENSO skewness spread in the 17 CMIP5 models. Both CESM-LE and the selected CMIP5 models show increased EP and CP El Niño variability in a warmer climate, driven by a stronger mean vertical temperature gradient in the upper ocean and faster surface warming of the eastern equatorial Pacific. However, MPI-GE shows no agreement in EP or CP standard deviation change. This is due to weaker sensitivity to the warming signal, such that when the eastern equatorial Pacific surface warming is faster, the change in upper ocean vertical temperature gradient tends to be weaker. This highlights that individual models produce a different ENSO response in a warmer climate, and that considerable uncertainty within the CMIP5 ensemble may be caused by internal climate variability.

From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods. During the first week of February, when the event had its greatest impact in northwest Queensland, record-breaking precipitation accumulations were observed in several locations, accompanied by strong winds, substantial cold maximum temperature anomalies and related wind chill. In spite of the extreme nature of the event, the monthly rainfall outlook for February issued by Australia’s Bureau of Meteorology on 31st January provided no indication of the event. In this study, we evaluate the dynamics of the event and assess how predictable it was across a suite of ensemble model forecasts using the UK Met Office numerical weather prediction (NWP) system, focussing on a one week lead time. In doing so, we demonstrate the skill of the NWP system in predicting the possibility of such an extreme event occurring. We further evaluate the benefits derived from running the ensemble prediction system at higher resolution than used operationally at the Met Office and with a fully coupled dynamical ocean. We show that the primary forecast errors are generated locally, with key sources of these errors including atmosphere-ocean coupling and a known bias associated with the behaviour of the convection scheme around the coast. We note that a relatively low resolution ensemble approach requires limited computing resource, yet has the capacity in this event to provide useful information to decision makers with over aweek’s notice, beyond the duration of many operational deterministic forecasts.

This research analyses the observed relationship between eastern and central Pacific El Niño Southern Oscillation (ENSO) events and Australian monsoon rainfall (AUMR) on a decadal timescale during the December to March monsoon months. To assess the decadal influence of the different flavours of ENSO on the AUMR, we focus on the phases of the Interdecadal Pacific Oscillation (IPO) over the period 1920 to 2020. The AUMR is characterized by substantial decadal variability, which appears to be linked to the positive and negative phases of the IPO. During the past two historical negative IPO phases, significant correlations have been observed between central Pacific sea surface temperature (SST) anomalies and AUMR over both the northeast and northwest of Australia. This central Pacific SST-AUMR relationship has strengthened from the first negative IPO phase (mid-1940s to the mid-1970s) to the second (late 1990s to mid-2010s), while the eastern Pacific SST-AUMR influence has weakened. Composite rainfall anomalies over Australia reveal a different response of AUMR to central Pacific El Niño/La Niña and eastern Pacific La Niña events during positive IPO and negative IPO phases. This research clearly shows that ENSO's influence on AUMR is modulated by Pacific decadal variability, however this teleconnection, in itself, can change between similar decadal Pacific states. Going forward, as decadal prediction systems improve and become more mainstream, the IPO phase could be used as a potential source for decadal predictability of the tendency of AUMR.

The development of the Australian Community Climate and Earth-System Simulator-Seasonal prediction system version 1 (ACCESS-S1) signifies a major step towards addressing predictive limitations in multi-week to seasonal forecasting throughout Australia. It is anticipated that moving to ACCESS-S1 will provide improved skill in rainfall prediction during the dry to wet season transition period across tropical northern Australia. This is an important time for northern Australian livestock producers in terms of the decisions they make around pasture and livestock management. This study quantifies the hindcast skill of ACCESS-S1 for the northern rainfall onset (NRO), defined as the date when 50 mm of precipitation has accumulated at a given location from the 1st of September, heralding the shift towards greener pastures. We evaluate the raw model hindcasts, and compare them to hindcasts corrected for mean biases and those calibrated against observations. It is found that the raw ACCESS-S1 hindcasts broadly replicate the observed median NRO over the period 1990–2012, despite a ten- dency for earlier than observed onsets. In terms of forecasting the interannual variability of the NRO, the ca- librated hindcasts show the greatest skill, with the largest improvements over a climatological forecast in their probabilistic forecasts of an earlier or later than usual onset, with a large portion of northern Australian showing more than 10% improvement. With real-time NRO forecasts now generated by ACCESS-S1, it is expected that the calibrated predictions will help northern Australian graziers make better informed decisions around livestock management prior to the wet season.

The severe drought of the 1930s Dust Bowl decade coincided with record-breaking summer heatwaves that contributed to the socio-economic and ecological disaster over North America’s Great Plains. It remains unresolved to what extent these exceptional heatwaves, hotter than in historically forced coupled climate model simulations, were forced by sea surface temperatures (SSTs) and exacerbated through human-induced deterioration of land cover. Here we show, using an atmospheric-only model, that anomalously warm North Atlantic SSTs enhance heatwave activity through an association with drier spring conditions resulting from weaker moisture transport. Model devegetation simulations, that represent the wide-spread exposure of bare soil in the 1930s, suggest human activity fueled stronger and more frequent heatwaves through greater evaporative drying in the warmer months. This study highlights the potential for the amplification of naturally occurring extreme events like droughts by vegetation feedbacks to create more extreme heatwaves in a warmer world., In the 1930s, the US was hit by a severe drought and record-breaking heatwaves in a period known as the Dust Bowl. Here, the authors present model experiments that suggest that warm North Atlantic temperatures and human devegetation played key roles in making these heatwaves particularly strong.

The development of the Australian Community Climate Earth-System Simulator-Seasonal version 1 (ACCESS-S1) prediction system signifies a major step in addressing predictive limitations in multi-week to seasonal forecasting. It is anticipated that ACCESS-S1 will provide greater skill in its prediction of the wet season onset and intensity, which are crucial to the viability of cattle grazing across northern Australia. We evaluate the hindcast skill of the ACCESS-S1 for the northern rainfall onset, defined as the date when 50 mm of precipitation has accumulated at a given location from the 1st of September, heralding the start of the seasonal dry-to-wet transition over northern Australia. We show that the raw ACCESS-S1 hindcasts, regridded to a 5 km observed grid, capture the broad-scale features of the median onset, including an early October onset over the western Top End and southeast Queensland. However, the hindcasts fail to capture the later December onsets over central Australia. The greatest improvement in onset skill comes from first calibrating the hindcasts using observations, which outperform the raw model and bias corrected hindcasts over central Australia and the far west in the Pilbara-Gascoyne basin. Based on its simulation of realistic northern rainfall onset dates and variability alone, ACCESS-S1’s prediction performance can be considered an improvement over the older predictive system. As the real-time onset forecasts have were issued using ACCESS-S1 in July 2019, it is expected that the calibrated predictions will help improve the resilience of cattle producers and graziers to drought across northern Australia.

Substantial warming occurred across North America, Europe and the Arctic over the early twentieth century1, including an increase in global drought2, that was partially forced by rising greenhouse gases (GHGs)3. The period included the 1930s Dust Bowl drought4–7 across North America’s Great Plains that caused widespread crop failures4,8, large dust storms9 and considerable out-migration10. This coincided with the central United States experiencing its hottest summers of the twentieth century11,12 in 1934 and 1936, with over 40 heatwave days and maximum temperatures surpassing 44 °C at some locations13,14. Here we use a large-ensemble regional modelling framework to show that GHG increases caused slightly enhanced heatwave activity over the eastern United States during 1934 and 1936. Instead of asking how a present-day heatwave would behave in a world without climate warming, we ask how these 1930s heatwaves would behave with present-day GHGs. Heatwave activity in similarly rare events would be much larger under today’s atmospheric GHG forcing and the return period of a 1-in-100-year heatwave summer (as observed in 1936) would be reduced to about 1-in-40 years. A key driver of the increasing heatwave activity and intensity is reduced evaporative cooling and increased sensible heating during dry springs and summers. The United States experienced two of its hottest recorded summers in 1934 and 1936, amplified by drier soils associated with the Dust Bowl drought. A large regional climate model ensemble estimates present-day GHGs would cause similarly extreme, 1-in-100-year heatwaves to occur about every 40 years.

In late January to early February 2019, wide-spread flooding, strong winds and relatively cold temperatures over the north-eastern Australian state of Queensland led to the loss of an estimated 625,000 cattle and 48,000 sheep. The system that caused these impacts was a quasi-stationary monsoon depression that lasted close to 10 days, bringing weekly rainfall totals above 1000 mm in some locations, maximum temperatures 8–12°C below average, and sustained wind speeds of 30-40 km/h. The same weather event caused inundation and damage to more than 3000 homes over the eastern Queensland coastal city of Townsville with an insurance cost of over $1.2 billion AUD (https://www.afr.com/companies/financial-services/insurers-reveal-townsville-flood-cost-warn-region-is-unprofitable-20190804-p52do5). Observations and reanalysis confirm that an active Madden-Julian Oscillation pulse stalled over the western Pacific during the period of the flooding. To the south, a blocking anticyclone over the northern Tasman Sea promoted onshore easterly flow, and with it, the relatively low apparent temperatures (Cowan et al. 2019).In the days before the event, the Australian Bureau of Meteorology issued the monthly rainfall outlook for February which provided little indication of the upcoming extreme event. At the time of the event, there was a 50% chance of an El Niño developing during the boreal spring, meaning a tendency towards warmer and drier conditions across the northeast. Here we show that forecasts from the Bureau's newly developed dynamical subseasonal-to-seasonal (S2S) prediction system – Australian Community Climate Earth-System Simulator Seasonal version 1 (ACCESS-S1) – of the weekly-averaged conditions were more skilful. The ACCESS-S1 99-member ensemble forecast a more than doubling of the probability of extreme weekly rainfall totals a week prior to the floods, along with increased probabilities of extremely low maximum temperatures and high winds. Ensemble-mean weekly rainfall amounts, however, were considerably underestimated by ACCESS-S1, even in forecasts initialised at the start of the peak flooding week. This is consistent with other state-of-the-art dynamical S2S prediction systems. Yet one individual ensemble member of ACCESS-S1 managed to forecast close to 85% of the rainfall magnitude across the most heavily impacted region of northwest Queensland in a week 2 forecast. This suggests current S2S prediction systems like ACCESS-S1 are capable at getting close to predicting record-breaking events with at least one week's lead-time. It also appears that accurate prediction beyond two weeks (i.e., a week 3 forecast) of an event like the northern Queensland floods is more difficult to achieve.Reference:Cowan et al. (2019): Forecasting the extreme rainfall, low temperatures, and strong winds associated with the northern Queensland floods of February 2019, Weather and Climate Extremes, 26, 100232, https://doi.org/10.1016/j.wace.2019.100232.

Record-breaking summer heat waves were experienced across the contiguous United States during the decade-long “Dust Bowl” drought in the 1930s. Using high-quality daily temperature observations, the Dust Bowl heat wave characteristics are assessed with metrics that describe variations in heat wave activity and intensity. Despite the sparser station coverage in the early record, there is robust evidence for the emergence of exceptional heat waves across the central Great Plains, the most extreme of which were preconditioned by anomalously dry springs. This is consistent with the entire twentieth-century record: summer heat waves over the Great Plains develop on average ~15–20 days earlier after anomalously dry springs, compared to summers following wet springs. Heat waves following dry springs are also significantly longer and hotter, indicative of the importance of land surface feedbacks in heat wave intensification. A distinctive anomalous continental-wide circulation pattern accompanied exceptional heat waves in the Great Plains, including those of the Dust Bowl decade. An anomalous broad surface pressure ridge straddling an upper-level blocking anticyclone over the western United States forced substantial subsidence and adiabatic warming over the Great Plains, and triggered anomalous southward warm advection over southern regions. This prolonged and amplified the heat waves over the central United States, which in turn gradually spread westward following heat wave emergence. The results imply that exceptional heat waves are preconditioned, triggered, and strengthened across the Great Plains through a combination of spring drought, upper-level continental-wide anticyclonic flow, and warm advection from the north.

Outputs from new state‐of‐the‐art climate models under the Coupled Model Inter‐comparison Project phase 6 (CMIP6) promise improvement and enhancement of climate change projections information for Australia. Here we focus on three key aspects of CMIP6: what is new in these models, how the available CMIP6 models evaluate compared to CMIP5, and their projections of the future Australian climate compared to CMIP5 focussing on the highest emissions scenario. The CMIP6 ensemble has several new features of relevance to policymakers and others, for example, the integrated matrix of socioeconomic and concentration pathways. The CMIP6 models show incremental improvements in the simulation of the climate in the Australian region, including a reduced equatorial Pacific cold tongue bias, slightly improved rainfall teleconnections with large‐scale climate drivers, improved representation of atmosphere and ocean extreme heat events, as well as dynamic sea level. However, important regional biases remain, evident in the excessive rainfall over the Maritime Continent and rainfall pattern biases in the nearby tropical convergence zones. Projections of Australian temperature and rainfall from the available CMIP6 ensemble broadly agree with those from CMIP5, except for a group of CMIP6 models with higher climate sensitivity and greater warming and increase in some extremes after 2050. CMIP6 rainfall projections are similar to CMIP5, but the ensemble examined has a narrower range of rainfall change in austral summer in Northern Australia and austral winter in Southern Australia. Overall, future national projections are likely to be similar to previous versions but perhaps with some areas of improved confidence and clarity.

From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods, killing an estimated 625,000 head of cattle in northwest Queensland, and inundating over 3 000 homes in the coastal city of Townsville. The monsoon depression lasted ~10 days, driving daily rainfall accumulations exceeding 200 mm/day, maximum temperatures 8–10 °C below normal, and wind gusts above 70 km/h. In this study, the atmospheric conditions during the event and its predictability on the weekly to subseasonal range are investigated. Results show that during the event, the tropical convective signal of the Madden-Julian Oscillation was over the western Pacific, and likely contributed to the heavy rainfall, however the El Niño-Southern Oscillation was not in the usual phase for increased rainfall over Queensland. Over the northern Tasman Sea, an anticyclone helped maintain a positive phase of the Southern Annular Mode and promote onshore easterly flow. Somewhat consistent with these climate drivers, the monthly rainfall outlook for February issued by the Australian Bureau of Meteorology on 31 January provided no indication of the event, yet forecasts, not available to the public, of weekly-averaged conditions by the Bureau's dynamical subseasonal-to-seasonal (S2S) prediction system were more successful. For the week of 31 January to 6 February the prediction system forecast a more than doubling of the probability of extreme (highest quintile) weekly rainfall a week prior to the event, along with increased probabilities of extremely low (lowest quintile) maximum temperatures and extreme (highest quintile) wind speeds. Ensemble-mean weekly rainfall amounts, however, were considerably underestimated by the prediction system, even in forecasts initialised at the start of the peak flooding week, consistent with other state-of-the-art dynamical S2S prediction systems. Despite this, one of the individual ensemble members of the Bureau's prediction system did manage to forecast close to 85% of the magnitude of the rainfall across the most heavily impacted region of northwest Queensland a week before the event. Predicting this exceptional event beyond two weeks appears beyond our current capability despite the dynamical system forecasts showing good skill in forecasting the broad-scale atmospheric conditions north of Australia a week prior. Keywords: Extreme, Rainfall, Temperature, Flood, Forecast, Skill, Madden-Julian Oscillation, Subseasonal

This review addresses the causes of observed climate variations across the industrial period, from 1750 to present. It focuses on long-term changes, both in response to external forcing and to climate variability in the ocean and atmosphere. A synthesis of results from attribution studies based on palaeoclimatic reconstructions covering the recent few centuries to the 20th century, and instrumental data shows how greenhouse gases began to cause warming since the beginning of industrialization, causing trends that are attributable to greenhouse gases by 1900 in proxy-based temperature reconstructions. Their influence increased over time, dominating recent trends. However, other forcings have caused substantial deviations from this emerging greenhouse warming trend: volcanic eruptions have caused strong cooling following a period of unusually heavy activity, such as in the early 19th century; or warming during periods of low activity, such as in the early-to-mid 20th century. Anthropogenic aerosol forcing most likely masked some global greenhouse warming over the 20th century, especially since the accelerated increase in sulphate aerosol emissions starting around 1950. Based on modelling and attribution studies, aerosol forcing has also influenced regional temperatures, caused long-term changes in monsoons and imprinted on Atlantic variability. Multi-decadal variations in atmospheric modes can also cause long-term climate variability, as apparent for the example of the North Atlantic Oscillation, and have influenced Atlantic ocean variability. Long-term precipitation changes are more difficult to attribute to external forcing due to spatial sparseness of data and noisiness of precipitation changes, but the observed pattern of precipitation response to warming from station data supports climate model simulated changes and with it, predictions. The long-term warming has also led to significant differences in daily variability as, for example, visible in long European station data. Extreme events over the historical record provide valuable samples of possible extreme events and their mechanisms.

The science of extreme event attribution has rapidly expanded in recent years, with numerous studies dedicated to determining whether and to what extent anthropogenic climate change has increased the likelihood of specific extreme weather events occurring. However, the majority of such studies have focussed on extreme events which have occurred in the recent past (usually within the past 10 years) while minimal research efforts have considered the multitude of high-impact extreme climatic events which occurred throughout the instrumental record. This study proposes a framework to quantify how the likelihood of witnessing meteorological characteristics reminiscent of the 1947 Central European heatwave have evolved over time. We specifically examine circulation analogues as a tool to understand the relative role of dynamical and thermodynamic contributions to changes in the probability of experiencing similar heatwave events. Using a reanalysis-based dataset, our results show changes in the frequency of 1947-like extreme heat throughout the twentieth century to be highly sensitive to methodological choices, particularly in the context of disaggregating dynamic and thermodynamic changes in the risk of extreme heat. Evidence also suggests clear decadal variability in the occurrence of circulation patterns conducive to the 1947 heatwaves. Finally, we discuss how to appropriately consider the time-evolution of attribution statements, as well as the broader limitations of employing circulation analogues as a method to interrogate the dynamical contribution to the probability ratio of an extreme event.

Despite global warming, total Antarctic sea ice coverage increased over 1979–2013. However, the majority of Coupled Model Intercomparison Project phase 5 models simulate a decline. Mechanisms causing this discrepancy have so far remained elusive. Here we show that weaker trends in the intensification of the Southern Hemisphere westerly wind jet simulated by the models may contribute to this disparity. During austral summer, a strengthened jet leads to increased upwelling of cooler subsurface water and strengthened equatorward transport, conducive to increased sea ice. As the majority of models underestimate summer jet trends, this cooling process is underestimated compared with observations and is insufficient to offset warming in the models. Through the sea ice-albedo feedback, models produce a high-latitude surface ocean warming and sea ice decline, contrasting the observed net cooling and sea ice increase. A realistic simulation of observed wind changes may be crucial for reproducing the recent observed sea ice increase., Mechanisms responsible for the recent increase in Antarctic sea ice cover remain elusive. Here, the authors show that model underestimates of changes in wind-induced ocean circulation may contribute, in part, to the failure of CMIP5 models to accurately capture modern Antarctic sea ice trends.

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960–2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land–atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution.

The Indian Ocean Dipole (IOD) is the dominant mode of interannual variability over the tropical Indian Ocean (IO) and its future changes are projected to impact the climate and weather of Australia, East Africa, and Indonesia. Understanding the response of the IOD to a warmer climate has been largely limited to studies of individual coupled general circulation models or multi-model ensembles. This has provided valuable insight into the IOD’s projected response to increasing greenhouse gases but has limitations in accounting for the role of internal climate variability. Using the Community Earth System Model Large Ensemble (CESM-LE), the IOD is examined in thirty-five present-day and future simulations to determine how internal variability influences properties of the IOD and their response to a warmer climate. Despite small perturbations in the initial conditions as the only difference between ensemble members, significant relationships between the mean state of the IO and the IOD arise, leading to a spread in the projected IOD responses to increasing greenhouse gases. This is driven by the positive Bjerknes feedback, where small differences in mean thermocline depth, which are caused by internal climate variability, generate significant variations in IOD amplitude, skewness, and the climatological zonal sea surface temperature gradient.

The tropical Indian Ocean has experienced a faster warming rate in the west than in the east over the twentieth century. The warming pattern resembles a positive Indian Ocean dipole (IOD) that is well captured by climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), forced with the two main anthropogenic forcings, long-lived greenhouse gases (GHGs), and aerosols. However, much less is known about how GHGs and aerosols influence the IOD asymmetry, including the negative sea surface temperature (SST) skewness in the east IOD pole (IODE). Here, it is shown that the IODE SST negative skewness is more enhanced by aerosols than by GHGs using single-factor forcing experiments from 10 CMIP5 models. Aerosols induce a greater mean zonal thermocline gradient along the tropical Indian Ocean than that forced by GHGs, whereby the thermocline is deeper in the east relative to the west. This generates strong asymmetry in the SST response to thermocline anomalies between warm and cool IODE phases in the aerosol-only experiments, enhancing the negative IODE SST skewness. Other feedback processes involving zonal wind, precipitation, and evaporation cannot solely explain the enhanced SST skewness by aerosols. An interexperiment comparison in one model with strong skewness confirms that the mean zonal thermocline gradient across the Indian Ocean determines the magnitude of the SST–thermocline asymmetry, which in turn controls the SST skewness strength. The findings suggest that as aerosol emissions decline and GHGs increase, this will likely contribute to a future weakening of the IODE SST skewness.

International audience; An attribution study has been performed to investigate the degree to which the unusually cold European winter of 2009/10 was modified by anthropogenic climate change. Two different methods have been included for the attribution: one based on large HadGEM3-A ensembles and one based on a statistical surrogate method. Both methods are evaluated by comparing simulated winter temperature means, trends, standard deviations, skewness, return periods, and 5% quantiles with observations. While the surrogate method performs well, HadGEM3-A in general underestimates the trend in winter by a factor of ⅔. It has a mean cold bias dominated by the mountainous regions and also underestimates the cold 5% quantile in many regions of Europe. Both methods show that the probability of experiencing a winter as cold as 2009/10 has been reduced by approximately a factor of 2 because of anthropogenic changes. The method based on HadGEM3-A ensembles gives somewhat larger changes than the surrogate method because of differences in the definition of the unperturbed climate. The results are based on two diagnostics: the coldest day in winter and the largest continuous area with temperatures colder than twice the local standard deviation. The results are not sensitive to the choice of bias correction except in the mountainous regions. Previous results regarding the behavior of the measures of the changed probability have been extended. The counterintuitive behavior for heavy-tailed distributions is found to hold for a range of measures and for events that become more rare in a changed climate

Atmospheric and oceanic conditions associated with southern Australian heat waves are examined using phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. Accompanying work analyzing modeled heat wave statistics for Australia finds substantial increases in the frequency, duration, and temperature of heat waves by the end of the twenty-first century. This study assesses the ability of CMIP5 models to simulate the synoptic and oceanic conditions associated with southern Australian heat waves, and examines how the classical atmospheric setup associated with heat waves is projected to change in response to mean-state warming. To achieve this, near-surface temperature, mean sea level pressure, and sea surface temperature (SST) from the historical and high-emission simulations are analyzed. CMIP5 models are found to represent the synoptic setup associated with heat waves well, despite showing greater variation in simulating SST anomalies. The models project a weakening of the pressure couplet associated with future southern Australian heat waves, suggesting that even a non-classical synoptic setup is able to generate more frequent heat waves in a warmer world. A future poleward shift and strengthening of heat wave–inducing anticyclones is confirmed using a tracking scheme applied to model projections. Model consensus implies that while anticyclones associated with the hottest future southern Australian heat waves will be more intense and originate farther poleward, a greater proportion of heat waves occur in association with a weaker synoptic setup that, when combined with warmer mean-state temperatures, gives rise to more future heat waves.

Extremes such as summer heat waves and winter warm spells have a significant impact on the climate of Australia, with many regions experiencing an increase in the frequency and duration of these events since the mid-twentieth century. With the availability of Coupled Model Intercomparison Project phase 5 (CMIP5) climate models, projected changes in heat waves and warm spells are investigated across Australia for two future emission scenarios. For the historical period encompassing the late twentieth century (1950–2005) an ensemble mean of 15 models is able to broadly capture the observed spatial distribution in the frequency and duration of summer heat waves, despite overestimating these metrics along coastal regions. The models achieve a better comparison to observations in their simulation of the temperature anomaly of the hottest heat waves. By the end of the twenty-first century, the model ensemble mean projects the largest increase in summer heat wave frequency and duration to occur across northern tropical regions, while projecting an increase of ~3°C in the maximum temperature of the hottest southern Australian heat waves. Model consensus suggests that future winter warm spells will increase in frequency and duration at a greater rate than summer heat waves, and that the hottest events will become increasingly hotter for both seasons by century’s end. Even when referenced to a warming mean state, increases in the temperature of the hottest events are projected for southern Australia. Results also suggest that following a strong mitigation pathway in the future is more effective in reducing the frequency and duration of heat waves and warm spells in the southern regions compared to the northern tropical regions.

Australia has been exposed to a vast array of extreme weather regimes over the past few years, and the frequency and intensity of these events are expected to increase as a result of anthropogenic climate change. However, the predictability of extreme droughts, heat waves (HWs), bushfires and floods, is still hampered by our inability to fully understand how these weather systems interact with each other and with the climate system. This study brings new insight into the regional and large scale dynamics of some extreme events in Australia, by describing and comparing the climate signature of summer HWs and extreme rainfall events which have occurred in the states of Victoria and Queensland respectively, during 1979–2013. Our analyses highlight the importance of mid-latitude dynamics operating during HWs, in contrast with more tropical interactions at play during extreme rainfall events. A ‘common’ blocking high pressure system is observed over the Tasman Sea during the two types of extreme events, and may explain why some southeastern HWs (only about 25 %) occur in close succession with floods in Queensland. However, our results suggest that there is no dynamical link between these two types of events, since the HW-related anticyclone evolves as part of a baroclinic wave train, whereas in the case of rainfall events, this structure emerges as an equivalent barotropic response to tropical convection. Sub-regional surface temperatures and air–sea fluxes also suggest that distinct processes may be operating in the lead up to these two events. Indeed, HWs tend to occur when the wave train propagates from the south Indian to the Pacific Ocean, inducing a quasi-stationary blocking high system over the Tasman Sea. This anticyclonic anomaly can then advect hot dry air towards the southern Victorian coast, where it produces HW conditions. On the other hand, extreme rainfall events mostly occur when the background conditions correspond to a La Nina state. The convection induced in the western Pacific can trigger a tropical–extratropical teleconnection over Queensland. This may generate an anticyclonic anomaly over the Tasman Sea, able to divert air parcels over a warm and humid area where conditions are, this time, favorable for more extreme rainfall along the Queensland coast.

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.

The European summer of 1816 has often been referred to as a ‘year without a summer’ due to anomalously cold conditions and unusual wetness, which led to widespread famines and agricultural failures. The cause has often been assumed to be the eruption of Mount Tambora in April 1815, however this link has not, until now, been proven. Here we apply state-of-the-art event attribution methods to quantify the contribution by the eruption and random weather variability to this extreme European summer climate anomaly. By selecting analogue summers that have similar sea-level-pressure patterns to that observed in 1816 from both observations and unperturbed climate model simulations, we show that the circulation state can reproduce the precipitation anomaly without external forcing, but can explain only about a quarter of the anomalously cold conditions. We find that in climate models, including the forcing by the Tambora eruption makes the European cold anomaly up to 100 times more likely, while the precipitation anomaly became 1.5–3 times as likely, attributing a large fraction of the observed anomalies to the volcanic forcing. Our study thus demonstrates how linking regional climate anomalies to large-scale circulation is necessary to quantitatively interpret and attribute post-eruption variability.

In recent decades, Southern Hemisphere midlatitude regions such as southern Africa, southeastern Australia, and southern Chile have experienced a reduction in austral autumn precipitation; the cause of which is poorly understood. This study focuses on the ability of global climate models that form part of the Coupled Model Intercomparison Project phase 5 to simulate these trends, their relationship with extratropical and subtropical processes, and implications for future precipitation changes. Models underestimate both the historical autumn poleward expansion of the subtropical dry zone and the positive southern annular mode (SAM) trend. The multimodel ensemble (MME) is also unable to capture the spatial pattern of observed precipitation trends across semiarid midlatitude regions. However, in temperate regions that are located farther poleward such as southern Chile, the MME simulates observed precipitation declines. The MME shows a strong consensus in twenty-first-century declines in autumn precipitation across southern Chile in both the medium–low and high representative concentration pathway (RCP) scenarios and across southern Africa in the high RCP scenario, but little change across southeastern Australia. Projecting a strong positive SAM trend and continued subtropical dry-zone expansion, the models converge on large SAM and dry-zone-expansion-induced precipitation declines across southern midlatitudes. In these regions, the strength of future precipitation trends is proportional to the strength of modeled trends in these phenomena, suggesting that unabated greenhouse gas–induced climate change will have a large impact on austral autumn precipitation in such midlatitude regions.

Relationships of the Indian Ocean dipole (IOD), El Niño–Southern Oscillation (ENSO), and the southern annular mode (SAM) with atmospheric blocking are investigated using a linear framework over the austral autumn–spring (cool) seasons for southeast Australia (SEA). Positive blocking events occurring at 130°–140°E increase the likelihood of cutoff low pressure systems developing that generate significant rainfall totals across SEA. In mid to late austral autumn (April–May), blocking is coherent with negative IOD events. During this season, a negative IOD event and blocking are associated with warm sea surface temperature anomalies in the eastern tropical Indian Ocean and a blocking high pressure cell south of Australia. An anomalous cyclonic pressure center over southern Australia directs tropical moisture flux anomalies to the region. Despite this, only a small portion of a negative IOD's impact on SEA rainfall comes through blocking events. During austral winter, ENSO is coherent with blocking; anomalous tropical moisture fluxes from the western Pacific during a La Niña merge with anomalous cyclonic flows centered over SEA, delivering enhanced rainfall via cutoff lows. The low pressure cell constitutes a center of the Southern Oscillation associated with ENSO. This ENSO-blocking coherence is considerably weaker in austral spring, whereby circulation anomalies associated with blocking resemble a SAM-like pattern. As such, a large portion of the SAM's impact on SEA spring rainfall occurs in conjunction with blocking events. The relative importance of associations between the dominant climate modes and blocking in generating the drought-breaking cool season precipitation in 2010 across SEA is discussed.

[1] Multidecadal trends in the large-scale ocean circulation are influenced by changes in radiative forcings such as long-lived greenhouse gases, volcanic aerosols, and solar irradiance. Model simulations suggest that anthropogenic aerosols can also force circulation changes, including delaying the weakening of the North Atlantic thermohaline circulation, altering the interhemispheric sea surface temperature gradient, and inducing a pan-oceanic heat redistribution. The extent to which aerosols from different regions contribute to these oceanic changes is currently unknown. Using specifically designed 20th century coupled climate model experiments that separate Asian and non-Asian aerosol impacts, it is shown that the non-Asian aerosol component, predominantly sulfate aerosols, accounts for much of the simulated aerosol-induced oceanic changes. These include delaying the weakening of the global meridional circulation, increasing the northward heat transport across the equatorial Atlantic, and inducing a subsurface cooling in the subtropical southern Indian Ocean. As global sulfate aerosol levels peaked in the 1980s, these trends may be starting to reverse. This study highlights the importance of Northern Hemisphere non-Asian anthropogenic aerosols in driving remote changes in Southern Hemisphere subtropical and extratropical oceans. Citation: Cowan, T., and W. Cai (2013), The response of the large-scale ocean circulation to 20th century Asian and non-Asian aerosols, Geophys. Res. Lett., 40, 2761–2767

[1] The Indian Ocean Dipole (IOD) affects weather and climate in many parts of the world, but a realistic simulation of the IOD in state-of-the-art climate models remains a challenge. In most models, IOD peak-season amplitudes are systematically larger than that of the observed, a bias that deterministically affects climate projections in IOD-affected regions. Understanding the cause of this bias is therefore essential for alleviating model errors and reducing uncertainty in climate projections. Here it is shown that most Coupled Model Intercomparison Project Phase Three (CMIP3) and CMIP5 models produce too strong a Bjerknes feedback in the equatorial Indian Ocean, leading to the IOD bias. The thermocline-sea surface temperature (SST) feedback exerts the strongest influence on the simulated IOD amplitude; models simulating a stronger thermocline-SST feedback systematically generate a greater IOD amplitude. The strength of the thermocline-SST feedback in most models is predominantly controlled by the climatological west-east slope of the equatorial thermocline, which features an unrealistic mean slope tilting upward toward the eastern Indian Ocean. The unrealistic thermocline structure is accompanied by too strong a mean easterly wind and an overly strong west-minus-east SST gradient. The linkage of the mean climatic conditions, feedback strength, and projected climate highlights the fundamental importance of realistically simulating these components of the climate system for reducing uncertainty in climate change projections in IOD-affected regions.

Since the 1950s annual rainfall over southeastern Australia (SEA) has decreased considerably with a maximum decline in the austral autumn season (March–May), particularly from 1980 onward. The understanding of SEA autumn rainfall variability, the causes, and associated mechanisms for the autumn reduction remain elusive. As such, a new plausible mechanism for SEA autumn rainfall variability is described, and the dynamics for the reduction are hypothesized. First, there is no recent coherence between SEA autumn rainfall and the southern annular mode, discounting it as a possible driver of the autumn rainfall reduction. Second, weak trends in the subtropical ridge intensity cannot explain the recent autumn rainfall reduction across SEA, even though a significant relationship exists between the ridge and rainfall in April and May. With a collapse in the relationship between the autumn subtropical ridge intensity and position in recent decades, a strengthening in the influence of the postmonsoonal winds from north of Australia has emerged, as evident by a strong post-1980 coherence with SEA mean sea level pressure and rainfall. From mid to late autumn, there has been a replacement of a relative wet climate in SEA with a drier climate from northern latitudes, representing a climate shift that has contributed to the rainfall reduction. The maximum baroclinicity, as indicated by Eady growth rates, has shifted poleward. An associated poleward shift of the dominant process controlling SEA autumn rainfall has further enhanced the reduction, particularly across southern SEA. This observed change over the past few decades is consistent with a poleward shift of the ocean and atmosphere circulation.

As part of a special issue on natural hazards, this paper reviews the currentstate of scientific knowledge of Australian heatwaves. Over recent years, progress has been made in understanding both the causes of and changes to heatwaves. Relationships between atmospheric heatwaves and large-scale and synoptic variability have been identified, with increasing trends in heatwave intensity, frequency and duration projected to continue throughout the 21st century. However, more research is required to further our understanding of the dynamical interactions of atmospheric heatwaves, particularly with the land surface. Research into marine heatwaves is still in its infancy, with little known about driving mechanisms, and observed and future changes. In order to address these knowledge gaps, recommendations include: focusing on a comprehensive assessment of atmospheric heatwave dynamics; understandinglinks with droughts; working towards a unified measurement framework; and investigating observed and future trends in marine heatwaves. Such work requires comprehensive and long-term collaboration activities. However, benefits will extend to the international community, thus addressing global grand challenges surrounding these extreme events.

This paper highlights some caveats in using composite analyses to form physical hypotheses on the associations between environmental variables. This is illustrated using a specific example, namely the apparent links between heat waves (HWs) and sea surface temperatures (SSTs). In this case study, a composite analysis is performed to show the large-scale and regional SST conditions observed during summer HWs in Perth, southwest Australia. Composite results initially point to the importance of the subtropical South Indian Ocean, where physically coherent SST dipole anomalies appear to form a necessary condition for HWs to develop across southwest Australia. However, sensitivity tests based on pattern correlation analyses indicate that the vast majority of days when the identified SST pattern appears are overwhelmingly not associated with observed HWs, which suggests that this is definitely not a sufficient condition for HW development. Very similar findings are obtained from the analyses of 15 coupled climate model simulations. The results presented here have pertinent implications and applications for other climate case studies, and highlight the importance of applying comprehensive statistical approaches before making physical inferences on apparent climate associations.

The annual SST lag for the world ocean is obtained from a Fourier analysis of the HadISST (1870-2008) and NOAA WOA05 (1900-2005) monthly SST data series. The main properties are a mean of 73 days and a standard deviation of 16 days, with tongues of high SST lag extending poleward and eastward from the equatorial regions where a maximum in lag of about 110 days occurs. The SST lag is the sum of an atmospheric surface heat flux lag and an ocean heat storage lag which is the dominant contributor and provides direct estimates of the damping time for air/sea heat exchange, which are in good agreement with observations in the eastern North Atlantic Ocean, and also predictions of the phase lag of the mid-latitude ocean surface temperature field to El Nino-Southern Oscillation (ENSO) forcing. Hence, SST lag can be used to diagnose global climate variability. Local differences in lag of up to about 15 days occur between the 1991-2005 and 1976-1990 periods, which are accompanied by significant changes in regional climate. The lag time series for grid points in the eastern Indian Ocean, North Pacific Ocean and North Atlantic Ocean show that the variability can be interpreted in terms of bounded random walks of length about 20 years. The CSIRO Mk. 3.5 run for Scenario A2 over the period 1871-2100 has a similar random structure and also shows a secular increase in SST lag in the temperate oceans which is attributable to an expansion of the tropical belt. © 2012 Royal Meteorological Society.

Recent research has shown that the climatic impact from El Niño–Southern Oscillation (ENSO) on middle latitudes west of the western Pacific (e.g., southeast Australia) during austral spring (September–November) is conducted via the tropical Indian Ocean (TIO). However, it is not clear whether this impact pathway is symmetric about the positive and negative phases of ENSO and the Indian Ocean dipole (IOD). It is shown that a strong asymmetry does exist. For ENSO, only the impact from El Niño is conducted through the TIO pathway; the impact from La Niña is delivered through the Pacific–South America pattern. For the IOD, a greater convection anomaly and wave train response occurs during positive IOD (pIOD) events than during negative IOD (nIOD) events. This “impact asymmetry” is consistent with the positive skewness of the IOD, principally due to a negative skewness of sea surface temperature (SST) anomalies in the east IOD (IODE) pole. In the IODE region, convection anomalies are more sensitive to a per unit change of cold SST anomalies than to the same unit change of warm SST anomalies. This study shows that the IOD skewness occurs despite the greater damping, rather than due to a breakdown of this damping as suggested by previous studies. This IOD impact asymmetry provides an explanation for much of the reduction in spring rainfall over southeast Australia during the 2000s. Key to this rainfall reduction is the increased occurrences of pIOD events, more so than the lack of nIOD events.

In recent decades, southeast Australia (SEA) has experienced a severe rainfall decline, with a maximum reduction in the austral autumn season. The cause(s) of this decline remain unclear. This study examines the interaction between remote large-scale climate modes and an atmospheric phenomenon known as the subtropical ridge (STR) at the local scale. A focus is placed on the utility of using the STR as a bridge for understanding how these remote climate drivers influence SEA rainfall through a response in local atmospheric conditions. Using observational data since 1979, it is found that a strong seasonality exists in the impact of the STR on SEA rainfall. In austral autumn, because SEA rainfall is poorly correlated with the STR intensity (STRI) and STR position (STRP) on an interannual basis, it follows that most of the autumn rainfall reduction cannot be explained by the STRI changes in this season. There is also no clear relationship between the autumn STR and known remote modes of variability. Reductions in SEA rainfall have occurred in the austral winter and spring seasons; however, neither is significant. During winter, although El Niño–Southern Oscillation (ENSO) has little impact on the STR, there is a significant influence from the Indian Ocean dipole (IOD) and the southern annular mode (SAM). The IOD impact is conducted through equivalent-barotropic Rossby wave trains stemming from the eastern Indian Ocean in response to the IOD-induced anomalous convection and divergence. These wave trains modify the intensity and position of the ridge over SEA. The impact from the SAM is similarly projected onto the STRI and STRP. The STR trend accounts for the entire observed decline in SEA winter rainfall, 80% of which is contributed by the upward trend of the IOD; the SAM exhibits virtually no trend over the 30-yr period in this season. In spring, SEA rainfall shows strong interannual variability and is well correlated with the STRI; the ridge itself is influenced by the IOD and ENSO but not by the SAM. The Indian Ocean is a major pathway for ENSO’s impact on SEA rainfall in this season, which is conducted by two wave trains emanating from the east and west poles of the IOD. These wave train patterns share an anomalously high surface pressure center south of Australia, which does not align with the STR over SEA. As such, only a small portion of the STRI variance is accounted for by fluctuations in ENSO and the IOD. Long-term changes in the STRI account for about 90% of the observed decline in SEA spring rainfall, all of which are due to a recent increased frequency in the number of positive IOD events (upward IOD trend); ENSO shows no long-term trend over the 30-yr period. In summary, variability and change in winter and spring rainfall across SEA can be understood through the impact of remote climate modes, such as ENSO, the IOD, and the SAM, on the STR. This approach, however, offers no utility for understanding what drives the long-term SEA autumn rainfall decline, the dynamics of which remain elusive.

Impacts of El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) on Australian rainfall are diagnosed from the perspective of tropical and extratropical teleconnections triggered by tropical sea surface temperature (SST) variations. The tropical teleconnection is understood as the equatorially trapped, deep baroclinic response to the diabatic (convective) heating anomalies induced by the tropical SST anomalies. These diabatic heating anomalies also excite equivalent barotropic Rossby wave trains that propagate into the extratropics. The main direct tropical teleconnection during ENSO is the Southern Oscillation (SO), whose impact on Australian rainfall is argued to be mainly confined to near-tropical portions of eastern Australia. Rainfall is suppressed during El Niño because near-tropical eastern Australia directly experiences subsidence and higher surface pressure associated with the western pole of the SO. Impacts on extratropical Australian rainfall during El Niño are argued to stem primarily from the Rossby wave trains forced by convective variations in the Indian Ocean, for which the IOD is a primary source of variability. These equivalent-barotropic Rossby wave trains emanating from the Indian Ocean induce changes to the midlatitude westerlies across southern Australia, thereby affecting rainfall through changes in mean-state baroclinicity, west–east steering, and possibly orographic effects. Although the IOD does not mature until austral spring, its impact on Australian rainfall during winter is also ascribed to this mechanism. Because ENSO is largely unrelated to the IOD during austral winter, there is limited impact of ENSO on rainfall across southern latitudes of Australia in winter. A strong impact of ENSO on southern Australia rainfall in spring is ascribed to the strong covariation of ENSO and the IOD in this season. Implications of this pathway from the tropical Indian Ocean for impacts of both the IOD and ENSO on southern Australian climate are discussed with regard to the ability to make seasonal climate predictions and with regard to the role of trends in tropical SST for driving trends in Australian climate.

Severe rainfall deficiencies have plagued southern and eastern Australian regions over the past decades, where the long-term rainfall is projected to decrease. By contrast, there has been an increase over northwest Australia (NWA) in austral summer, which, if it continues, could be an important future water resource. If increasing anthropogenic aerosols contribute to the observed increase in summer rainfall, then, as anthropogenic aerosols are projected to decrease, what will the likely impact over NWA be? This study uses output from 24 climate models submitted to phase 3 of the Coupled Model Intercomparison Project (CMIP3) with a total of 75 experiments to provide a multimodel perspective. The authors find that none of the ensemble averages, either with both the direct and indirect anthropogenic aerosol effect (10 models, 32 experiments) or with the direct effect only (14 models, 43 experiments), simulate the observed NWA rainfall increase. Given this, it follows that a projected rainfall reduction is not due to a projected decline in future aerosol concentrations. The authors show that the projected NWA rainfall reduction is associated with an unrealistic and overly strong NWA rainfall teleconnection with the El Niño–Southern Oscillation (ENSO). The unrealistic teleconnection is primarily caused by a model equatorial Pacific cold tongue that extends too far into the western Pacific, with the ascending branch of the Walker circulation situated too far west, exerting an influence on rainfall over NWA rather than over northeast Australia. Models with a greater present-day ENSO amplitude produce a greater reduction in the Walker circulation and hence a greater reduction in NWA rainfall in a warming climate. Hence, the cold bias and its impact represent a source of uncertainty for climate projections.

Simulations of individual global climate drivers using models from the Coupled Model Intercomparison Project phase 3(CMIP3) have been examined; however, the relationship among them has not been assessed. This is carried out to address several important issues, including the likelihood of the southern annular mode (SAM) forcing Indian Ocean dipole (IOD) events and the possible impact of the IOD on El Niño–Southern Oscillation (ENSO) events. Several conclusions emerge from statistics based on multimodel outputs. First, ENSO signals project strongly onto the SAM, although ENSO-forced signals tend to peak before ENSO. This feature is similar to the situation associated with the IOD. The IOD-induced signal over southern Australia, through stationary equivalent Rossby barotropic wave trains, peak before the IOD itself. Second, there is no control by the SAM on the IOD, in contrast to what has been suggested previously. Indeed, no model produces a SAM–IOD relationship that supports a positive (negative) SAM driving a positive (negative) IOD event. This is the case even in models that do not simulate a statistically significant relationship between ENSO and the IOD. Third, the IOD does have an impact on ENSO. The relationship between ENSO and the IOD in the majority of models is far weaker than the observed. However, the ENSO’s influence on the IOD is boosted by a spurious oceanic teleconnection, whereby ENSO discharge–recharge signals transmit to the Sumatra–Java coast, generating thermocline anomalies and changing IOD properties. Without the spurious oceanic teleconnection, the influence of the IOD on ENSO is comparable to the impact of ENSO on the IOD. Other model deficiencies are discussed.

An asymmetry, and its multidecadal variability, in a rainfall teleconnection with the El Niño–Southern Oscillation (ENSO) are described. Further, the breakdown of this relationship since 1980 is offered as a cause for a rainfall reduction in an ENSO-affected region, southeast Queensland (SEQ). There, austral summer rainfall has been declining since around the 1980s, but the associated process is not understood. It is demonstrated that the rainfall reduction is not simulated by the majority of current climate models forced with anthropogenic forcing factors. Examination shows that ENSO is a rainfall-generating mechanism for the region because of an asymmetry in its impact: the La Niña–rainfall relationship is statistically significant, as SEQ summer rainfall increases with La Niña amplitude; by contrast, the El Niño–induced rainfall reductions do not have a statistically significant relationship with El Niño amplitude. Since 1980, this asymmetry no longer operates, and La Niña events no longer induce a rainfall increase, leading to the observed SEQ rainfall reduction. A similar asymmetric rainfall teleconnection with ENSO Modoki exists and shares the same temporal evolutions. This breakdown is caused by an eastward shift in the Walker circulation and the convection center near Australia’s east coast, in association with a post-1980 positive phase of the interdecadal Pacific oscillation (IPO). Such a breakdown occurred before 1950, indicating that multidecadal variability alone could potentially be responsible for the recent SEQ rainfall decline. An aggregation of outputs from climate models to distill the impact of climate change suggests that the asymmetry and the breakdown may not be generated by climate change, although most models do not perform well in simulating the ENSO–rainfall teleconnection over the SEQ region.

The relationship between the interannual changes in streamflow, precipitation and temperature of the Murray-Darling basin is investigated by using a two-parameter climate elasticity of streamflow approach. The non-linear relationship between streamflow and both precipitation and temperature indicates a greater streamflow sensitivity to precipitation than to temperature but a more significant impact of temperature change on streamflow than previously reported. The physical mechanisms producing high streamflow sensitivity to temperature change are not well understood, but may relate to concurrent changes in sub-annual precipitation characteristics such as seasonality, spatial distribution and intensity. Thus these characteristics need to be assessed and accounted for when attempting to project how streamflow, and hence water availability, may change in a future warmer world.

Significant warming has occurred across many of the world’s oceans throughout the latter part of the twentieth-century. The increase in the oceanic heat content displays a considerable spatial difference, with a maximum in the 35°–50°S midlatitude band. The relative importance of wind and surface heat flux changes in driving the warming pattern is the subject of much debate. Using wind, oceanic temperature, and heat flux outputs from twentieth-century multimodel experiments, conducted for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), the authors were able to reproduce the fast, deep warming in the midlatitude band; however, this warming is unable to be accounted for by local heat flux changes. The associated vertical structure and zonal distribution are consistent with a Sverdrup-type response to poleward-strengthening winds, with a poleward shift of the Southern Hemisphere (SH) supergyre and the Antarctic Circumpolar Current. However, the shift is not adiabatic and involves a net oceanic heat content increase over the SH, which can only be forced by changes in the net surface heat flux. Counterintuitively, the heat required for the fast, deep warming is largely derived from the surface heat fluxes south of 50°S, where the surface flux into the ocean is far larger than that of the midlatitude band. The heat south of 50°S is advected northward by an enhanced northward Ekman transport induced by the poleward-strengthening winds and penetrates northward and downward along the outcropping isopycnals to a depth of over 1000 m. However, because none of the models resolve eddies and given that eddy fluxes could offset the increase in the northward Ekman transport, the heat source for the fast, deep warming in the midlatitude band could be rather different in the real world.

The present study assesses the ability of climate models to simulate rainfall teleconnections with the El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD). An assessment is provided on 24 climate models that constitute phase 3 of the World Climate Research Programme’s Coupled Model Intercomparison Project (WCRP CMIP3), used in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The strength of the ENSO–rainfall teleconnection, defined as the correlation between rainfall and Niño-3.4, is overwhelmingly controlled by the amplitude of ENSO signals relative to stochastic noise, highlighting the importance of realistically simulating this parameter. Because ENSO influences arise from the movement of convergence zones from their mean positions, the well-known equatorial Pacific climatological sea surface temperature (SST) and ENSO cold tongue anomaly biases lead to systematic errors. The climatological SSTs, which are far too cold along the Pacific equator, lead to a complete “nonresponse to ENSO” along the central and/or eastern equatorial Pacific in the majority of models. ENSO anomalies are also too equatorially confined and extend too far west, with linkages to a weakness in the teleconnection with Hawaii boreal winter rainfall and an inducement of a teleconnection with rainfall over west Papua New Guinea in austral summer. Another consequence of the ENSO cold tongue bias is that the majority of models produce too strong a coherence between SST anomalies in the west, central, and eastern equatorial Pacific. Consequently, the models’ ability in terms of producing differences in the impacts by ENSO from those by ENSO Modoki is reduced. Similarly, the IOD–rainfall teleconnection strengthens with an intensification of the IOD relative to the stochastic noise. A significant relationship exists between intermodel variations of IOD–ENSO coherence and intermodel variations of the ENSO amplitude in a small subset of models in which the ENSO anomaly structure and ENSO signal transmission to the Indian Ocean are better simulated. However, using all but one model (defined as an outlier) there is no systematic linkage between ENSO amplitude and IOD–ENSO coherence. Indeed, the majority of models produce an ENSO–IOD coherence lower than the observed, supporting the notion that the Indian Ocean has the ability to generate independent variability and that ENSO is not the only trigger of the IOD. Although models with a stronger IOD amplitude and rainfall teleconnection tend to have a greater ENSO amplitude, there is no causal relationship; instead this feature reflects a commensurate strength of the Bjerknes feedback in both the Indian and Pacific Oceans.

Since 1950, there has been an increase in rainfall over North West Australia (NWA), occurring mainly during the Southern Hemisphere (SH) summer season. A recent study using twentieth-century multimember ensemble simulations in a global climate model forced with and without increasing anthropogenic aerosols suggests that the rainfall increase is attributable to increasing Northern Hemisphere aerosols. The present study investigates the dynamics of the observed trend toward increased rainfall and compares the observed trend with that generated in the model forced with increasing aerosols. It is found that the observed positive trend in rainfall is projected onto two modes of variability. The first mode is associated with an anomalously low mean sea level pressure (MSLP) off NWA instigated by the enhanced sea surface temperature (SST) gradients toward the coast. The associated cyclonic flows bring high-moisture air to northern Australia, leading to an increase in rainfall. The second mode is associated with an anomalously high MSLP over much of the Australian continent; the anticyclonic circulation pattern, over northern Australia, determines that when rainfall is anomalously high, west of 130°E, rainfall is anomalously low east of this longitude. The sum of the upward trends in these two modes compares well to the observed increasing trend pattern. The modeled rainfall trend, however, is generated by a different process. The model suffers from an equatorial cold-tongue bias: the tongue of anomalies associated with El Niño–Southern Oscillation extends too far west into the eastern Indian Ocean. Consequently, there is an unrealistic relationship in the SH summer between Australian rainfall and eastern Indian Ocean SST: the rise in SST is associated with increasing rainfall over NWA. In the presence of increasing aerosols, a significant SST increase occurs in the eastern tropical Indian Ocean. As a result, the modeled rainfall increase in the presence of aerosol forcing is accounted for by these unrealistic relationships. It is not clear whether, in a model without such defects, the observed trend can be generated by increasing aerosols. Thus, the impact of aerosols on Australian rainfall remains an open question.

Simulations by the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) models on the Southern Hemisphere (SH) circulation are assessed over the period 1950–99, focusing on the seasonality of the trend and the level of its congruency with the southern annular mode (SAM) in terms of surface zonal wind stress. It is found that, as a group, the models realistically produce the seasonality of the trend, which is strongest in the SH summer season, December–February (DJF). The modeled DJF trend is principally congruent with the modeled SAM trend, as in observations. The majority of models produce a statistically significant positive trend, with decreasing westerlies in the midlatitudes and increasing westerlies in the high latitudes. The trend pattern from an all-experiment mean achieves highest correlation with that from the National Centers for Environmental Prediction (NCEP) data. A total of 48 out of the 71 experiments were run with ozone-depletion forcing, which offers an opportunity to assess the importance of ozone depletion in driving the late-twentieth-century trends. The AR4 model ensemble that contains an ozone-depletion forcing produces an averaged trend that is comparable to the trend from the NCEP outputs corrected by station-based observations. The trend is largely generated after the mid-1970s. Without ozone depletion the trend is less than half of that in the corrected NCEP, although the errors in the observed trend are large. The impact on oceanic circulation is inferred from wind stress curl in the group with ozone-depletion forcing. The result shows an intensification of the southern midlatitude supergyre circulation, including a strengthening East Australian Current flowing through the Tasman Sea. Thus, ozone depletion also plays an important role in the subtropical gyre circulation change over the past decades.

International audience; Natural modes of variability centred in the tropics, such as the El Nino/Southern Oscillation and the Indian Ocean Dipole, are a significant source of interannual climate variability across the globe. Future climate warming could alter these modes of variability. For example, with the warming projected for the end of the twenty-first century, the mean climate of the tropical Indian Ocean is expected to change considerably. These changes have the potential to affect the Indian Ocean Dipole, currently characterized by an alternation of anomalous cooling in the eastern tropical Indian Ocean and warming in the west in a positive dipole event, and the reverse pattern for negative events. The amplitude of positive events is generally greater than that of negative events. Mean climate warming in austral spring is expected to lead to stronger easterly winds just south of the Equator, faster warming of sea surface temperatures in the western Indian Ocean compared with the eastern basin, and a shoaling equatorial thermocline. The mean climate conditions that result from these changes more closely resemble a positive dipole state. However, defined relative to the mean state at any given time, the overall frequency of events is not projected to change [mdash] but we expect a reduction in the difference in amplitude between positive and negative dipole events.

The South Pacific convergence zone (SPCZ) is the Southern Hemisphere's most expansive and persistent rain band, extending from the equatorial western Pacific Ocean southeastward towards French Polynesia(1,2). Owing to its strong rainfall gradient, a small displacement in the position of the SPCZ causes drastic changes to hydroclimatic conditions and the frequency of extreme weather events-such as droughts, floods and tropical cyclones-experienced by vulnerable island countries in the region(1-7). The SPCZ position varies from its climatological mean location with the El Nino/Southern Oscillation (ENSO), moving a few degrees northward during moderate El Nino events and southward during La Nina events(2,5,6). During strong El Nino events, however, the SPCZ undergoes an extreme swing-by up to ten degrees of latitude toward the Equator-and collapses to a more zonally oriented structure(5) with commensurately severe weather impacts(5,8-11). Understanding changes in the characteristics of the SPCZ in a changing climate is therefore of broad scientific and socioeconomic interest. Here we present climate modelling evidence for a near doubling in the occurrences of zonal SPCZ events between the periods 1891-1990 and 1991-2090 in response to greenhouse warming, even in the absence of a consensus on how ENSO will change(12-14). We estimate the increase in zonal SPCZ events from an aggregation of the climate models in the Coupled Model Intercomparison Project phases 3 and 5 (CMIP3(15) and CMIP5) multi-model database that are able to simulate such events. The change is caused by a projected enhanced equatorial warming in the Pacific(16) and may lead to more frequent occurrences of extreme events across the Pacific island nations most affected by zonal SPCZ events.

[1] Record low austral winter rainfall totals over southwest Western Australia (SWWA) in 2010 saw a continuation of the multidecade-long winter drought plaguing the region. During this season, the highest recorded positive Southern Annular Mode (SAM) value was measured, adding weight to an association of a positive SAM with anomalously low SWWA winter rainfall (SWR), and vice-versa. However, such a SAM-SWR teleconnection has been recently questioned. Using observational data in the post-1979 satellite era, it is shown that such a SAM influence does exist. This coherence is confirmed with 1150 years of modelled 20th century SWR anomalies and SAM values from 23 climate models, showing that a nonlinear impact operates: the influence from a negative SAM is greater than that from a positive SAM. This explains why a small positive shift in the SAM can cause a large SWR reduction, as has been observed. A further test shows that models with a greater positive SAM trend systematically produce a greater future SWR reduction. As all climate models project an increase in the SAM these results suggest that as global warming continues unabated, SWWA winter droughts will be more persistent as atmospheric conditions become more unfavourable for drought-breaking rains.

[1] Studies into the impact of anthropogenic aerosols on regional summer monsoon rainfall have focused on a black carbon‐induced enhancement and a sulfate‐induced suppression. The latter encompasses significant Asian and non‐Asian sources, but their relative roles in forcing historical global and regional monsoon trends are largely unexplored. Using targeted 20th century coupled climate simulations, designed to isolate the impact from anthropogenic aerosols, we show that Asian aerosols induce a weak suppression of global summer monsoon, confined to the East Asian region. The addition of non‐Asian aerosols generates an enhancement and broadening of cooler temperatures over Europe and Asia relative to the ambient oceans, supporting stronger northerly flows that further suppress Asian monsoon rainfall. Furthermore, atmospheric convection is directed away from the Asian monsoon regions, resulting in an equatorward shift in rainfall. Our results highlight the importance of the non‐Asian aerosols in exacerbating the impact of Asian aerosols on global monsoon rainfall, particularly across Asia. Citation: Cowan, T., and W. Cai (2011), The impact of Asian and non‐Asian anthropogenic aerosols on 20th century Asian summer monsoon, Geophys. Res. Lett., 38, L11703, doi:10.1029/ 2011GL047268.

A multi-model average shows that 21st century warming over the eastern Indian Ocean (IO) is slower than that to the west, but with strong inter-model variations. Is the simulation of the Indian Ocean Dipole (IOD) relevant to the inter-model variations? We demonstrate that inter-model variations of this future warming are consistent with how well models simulate historical IOD properties; models with a stronger IOD amplitude systematically produce a slower eastern IO warming rate with greater future rainfall changes in IOD-affected regions. These models also produce a stronger Bjerknes-like positive feedback, involving sea surface temperatures (SSTs), winds and a shoaling thermocline in the eastern IO. As warming proceeds, models with a stronger positive feedback induce a greater response to warming-induced changes such as easterly trends associated with the Walker circulation, generating a smaller warming in the eastern IO. Simulating the present-day IOD properties is, therefore, a relevant criterion for selecting models for climate projections.

[1] Trends in global oceanic heat content (OHC) over the late 20th century as simulated by climate models that incorporate all radiative forcing factors are smaller than the observed, but the causes are not clear. Given the cooling effect associated with increasing anthropogenic aerosols and natural forcing (i.e., volcanic aerosols), we examine their respective roles in the simulated global OHC trend and the associated ocean temperature structure, using targeted experiments from two models, designed to separate the individual impacts of these forcing components. We show that it is more likely that the indirect effect of aerosols, not volcanic aerosols alone, is the reason for the bulk of weaker modelled OHC trends. Further, anthropogenic aerosols are essential for simulating the structure of the observed temperature changes, including a concentrated cooling in the Southern Hemisphere subtropical latitudes, consistent with a more stable global Conveyer, a greater strengthening of the subtropical gyre circulation, and a stronger Southern Annular Mode trend in targeted experiments with anthropogenic aerosol forcing.