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We assess seasonally varying impacts of the Madden–Julian oscillation (MJO) on Australian maximum and minimum temperature anomalies and extremes, and their modulation by El Niño–Southern Oscillation (ENSO), for the period June 1974–May 2022. Our composite-based approach uses observed temperatures from the Australian Gridded Climate Data, and 850-hPa wind data from the NCEP–NCAR reanalysis, to show how relationships to temperature and circulation evolve over the eight-phase life cycle of the MJO, which we derive from the real-time multivariate MJO index. The MJO has significant impacts on Australian temperatures and winds in all parts of the country at various times throughout the year, and to varying degrees. Two of the most pronounced impacts are 1) daytime warming across southeastern Australia in MJO phase 3 during spring associated with a strong anomalous anticyclone and 2) nighttime cooling over Queensland in MJO phase 7 during winter associated with anomalous advection of cool dry continental air. La Niña acts to significantly lessen both of these impacts, while El Niño enhances both the phase 3 warming over southern Australia in spring and the phase 7 overnight cooling over southern Queensland in winter. We show how the MJO can combine with El Niño and La Niña to have strong compounding influences, thus highlighting the importance of understanding interactions between multiple modes of climate variability and how they relate to Australian temperatures and extremes.

This study first re-examines the impact of the Madden–Julian oscillation (MJO) on weekly rainfall probabilities and wind anomalies across Australia, motivated by the need for a contemporary understanding of the MJO’s influence on Australian rainfall, whether this has changed from a previous assessment published in 2009. With an extra 15 years of observations, we show that the strong impact of MJO phases 5 and 6 on northern Australia’s austral summer rainfall has weakened by around 5% over Australia’s Top End. In addition, austral spring has seen a weakening of the suppressed rainfall teleconnection with MJO phases 2 and 3 over southeast Australia. The weakened relationships make it a little harder to use the MJO to explain rainfall variations over northern Australia in summer and southeast Australia in spring in the current climate. The study’s second motivation is to further document the combined influence of El Niño–Southern Oscillation (ENSO) and the MJO on rainfall. In summer during El Niño, as compared with La Niña or neutral ENSO conditions, there are stronger reductions in rainfall probabilities over northern Australia associated with the dry MJO phases 8, 1, and 2, but the significantly increased rainfall probabilities in MJO phases 5 and 6 remain much the same. Indeed, the MJO dominates over ENSO in its influence on weekly rainfall probabilities in the north in summer. In contrast, ENSO tends to dominate across subtropical and southern Australia in spring. The updated probability maps are an important resource for estimating the intraseasonal influence of the MJO and ENSO on Australian rainfall. Significance Statement Accompanying forecasts of multiweek rainfall, the Australian Bureau of Meteorology provide average condition maps showing the long-term relationship between the Madden–Julian oscillation (MJO) and Australian weekly rainfall. Motivated by discussions with northern Australian beef producers, we updated the maps using high-resolution data and found that in the austral summer, the association between the MJO and northern rainfall has weakened in the past 15 years. Despite this, the MJO still dominates over El Niño–Southern Oscillation (ENSO) as a driver of changes in week-to-week rainfall over northern Australia in summer, although ENSO dominates farther south in spring. This study gives users an improved understanding of what to expect in terms of upcoming weekly weather when interpreting rainfall and MJO predictions.

Since 2017, the Northern Australia Climate Program (NACP) has assisted the pastoral grazing industry to better manage drought risk and climate variability. The NACP funding is sourced from the beef cattle industry, government, and academia, representing the program’s broad range of aims and target beneficiaries. The program funds scientists in the United Kingdom and Australia, in addition to extension advisers called “Climate Mates” across a region that supports 15 million head of cattle. Many Climate Mates are employed in the cattle sector and have existing relationships in their communities and capacity to meaningfully engage with the program’s intended beneficiaries—red meat producers. The NACP is a prime example of a successful end-to-end program, integrating climate model improvements (research) with tailored forecast products (development), through to direct stakeholder engagement (extension), on-ground application of technologies (adoption), and improvement in industry and community resilience (impact). The climate information needs of stakeholders also feed back to the research and development components, ensuring the scientific research directly addresses end-user requirements. For any scientific research program, ensuring that research output has measurable real-world impact represents a key challenge. This is more difficult in cases where the scientific research is several steps away from the customer’s needs. This paper gives an overview of the NACP and research highlights, discussing how the end-to-end framework could be adapted and applied in other regions and industries. It seeks to provide a roadmap for other groups to follow to produce more targeted research with identifiable real-world benefits.

The expectations of the public and policymakers for accurate climate projections have grown with improvements in climate models. Internal variability, however, poses an inherent limit on climate predictability and, thus, accurate future climate projections of temperature and precipitation. This challenge is further amplified at a regional scale where internal variability can even dominate over forced anthropogenic climate change. In this study, we focused on the contribution of decadal climate variability and anthropogenic forcing (greenhouse gases and aerosols) on past precipitation changes over Australia since the 1970s. Using observational data, we find that the variance explained on decadal to multi-decadal timescales is comparable to that on sub-decadal scales across Australia, underlining the importance of examining Australian trends in the context of variability. While decadal and longer precipitation trends over Australia’s east coast are dominated by internal variability, significant drying trends in the austral winter (June to August) over southwest Western Australia and wettening trends in summer (December to February) over northwest Australia are evident. We further disentangle the influence of internal variability from that of different anthropogenic forcing agents on these trends using simulations from the CESM2 Large Ensemble and idealised anthropogenic aerosol simulations from PDRMIP (Precipitation Driver Response Model Intercomparison Project). Our findings provide additional evidence for the significant role of internal variability on regional climate change and also underline the importance of a focused dialogue between scientists, policymakers and the public to ensure realistic expectations for regional future climate projections.

This study describes flash drought (FD) inferred from the Evaporative Stress Index (ESI) over Australia and its relationship to vegetation. During 1975-2020, FD occurrence ranges from less than one per decade in the central arid regions to 10 per decade toward the coasts. Although FD can occur in any season, its occurrence is more frequent in summer in the north, winter in the southern interior and southwest, and across a range of months in the far southeast and Tasmania. With a view towards real-time monitoring, FD “declaration” is defined as the date when the ESI declines to at least -1, i.e., drought conditions, after at least 2 weeks of rapid decline. Composite analysis shows that evaporative demand begins to increase about 5-6 weeks before declaration with an increase in solar radiation, while evapotranspiration initially increases with evaporative demand but then decreases in response to the soil moisture depletion. Solar radiation increases simultaneously with precipitation deficit, both reaching their peak around declaration. FD intensity peaks with soil moisture depletion, 2-3 weeks after declaration. The composite wind speed only shows a modest increase around declaration. The composite FD ends 4 weeks after rapid decreases in solar radiation and increases in precipitation. Satellite-derived vegetation health composites show pronounced decline in the non-forested regions, peaking about 4-8 weeks after FD declaration, followed by a recovery period lasting about 12 weeks after flash drought ends. The forest-dominated regions, however, are little impacted. Modelled pasture growth data shows reduced values for up to 3 months after the declaration month covering the main agricultural areas of Australia.

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.

Objective To determine the incidence of clinically significant prostate cancer (csPCa) detected exclusively in the anterior prostate using transperineal prostate biopsy. Patients and methods Histopathology results of all patients who underwent transperineal prostate biopsy between February 2016 and March 2018 at a single institution were assessed for distribution of cancer within the prostate. Patients with cancer found exclusively in the anterior prostate were then compared to those with any cancer found in the posterior or lateral prostate with International Society of Urological Pathology Grade Group 2-5 cancers being considered csPCa. Results A total of 508 patients were included. Overall, 12.0% of the cohort had csPCa detected only in anterior biopsies. When stratified by prostate-specific antigen (PSA) level, 6.6% of men with a PSA level of 4.1-10.0 ng/mL and 8.2% of men with a PSA level of >10.0 ng/mL had csPCa detected in the anterior prostate alone. Conclusion Transperineal biopsy has the ability to diagnose anteriorly located csPCa that would potentially have been missed by the transrectal approach.

We analyse the decadal variability in the relationship between Australian monsoon rainfall (AUMR) and the El Niño Southern Oscillation (ENSO). A composite analysis is conducted to examine monsoon season (December to March) rainfall anomalies over northern Australia during central and eastern Pacific ENSO events between 1920 to 2020. These composites are evaluated separately for positive and negative phases of the Interdecadal Pacific Oscillation (IPO) and reveal differences in AUMR anomalies with respect to ENSO event diversity. During central Pacific (CP) El Niño events, the key month is February, in which the AUMR is above average in positive IPO phases and below average during negative IPO phases. This is due to low-level circulation anomalies northwest of Australia, which are cyclonic in the positive IPO phases and anticyclonic in negative IPO phases, in addition to moisture fluxes directed towards the central Pacific, away from northern Australia. During CP La Niña events, there are insignificant rainfall anomalies over northern Australia in December during positive IPO phases. In contrast, during negative IPO phases, strong and significant positive rainfall anomalies cover much of northern and eastern Australia, which relate to large-scale convergence of moisture and an intensification of the Walker Circulation. In summary, AUMR anomalies during CP ENSO events differ between positive and negative phases of the IPO due to variability in the large-scale atmospheric circulation.

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.

To determine the incidence of clinically significant prostate cancer (csPCa) detected exclusively in the anterior prostate using transperineal prostate biopsy.Histopathology results of all patients who underwent transperineal prostate biopsy between February 2016 and March 2018 at a single institution were assessed for distribution of cancer within the prostate. Patients with cancer found exclusively in the anterior prostate were then compared to those with any cancer found in the posterior or lateral prostate with International Society of Urological Pathology Grade Group 2-5 cancers being considered csPCa.A total of 508 patients were included. Overall, 12.0% of the cohort had csPCa detected only in anterior biopsies. When stratified by prostate-specific antigen (PSA) level, 6.6% of men with a PSA level of 4.1-10.0 ng/mL and 8.2% of men with a PSA level of10.0 ng/mL had csPCa detected in the anterior prostate alone.Transperineal biopsy has the ability to diagnose anteriorly located csPCa that would potentially have been missed by the transrectal approach.

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.

The central United States experienced the hottest summers of the twentieth century in 1934 and 1936, with over 40 heat wave days and maximum temperatures surpassing 44°C at some locations like Kansas and Oklahoma. In fact, as of 2019, the summer of 1936 is still the hottest on record. The heat waves coincided with the decade-long Dust Bowl drought, that caused wide-spread crop failures, dust storms that penetrated to New York and considerable out-migration. In a very-large ensemble regional modelling framework, we show that greenhouse gas increases slightly enhanced the frequency and duration of the Dust Bowl heat waves, and would strongly enhance similar heat waves in the present day under current, further elevated greenhouse gas levels. Specifically, present-day atmospheric greenhouse gas forcing would reduce the return period of a rare (less than once in a century) heat wave summer as observed in 1936 to about 1-in 40-years, with further contribution by sea surface warming. Here, we show that a key driver of this elevated heat wave risk is the reduction in evaporative cooling and increase in sensible heating during dry springs and summers. Hence, we conclude that a warmer world is creating the potential for future extreme heat in moisture-limited regions, with potentially very damaging impacts.

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.

x; "> The catchments in the Loess Plateau, in China ’ s middle reaches of the Yellow River Basin, experienced unprecedented land use changes in the last 50 years as a result of large-scale soil conservation measure to control soil erosion. The climate of the region also exhibited some levels of change with decreased precipitation and increased temperature. This study combined the time-trend analysis method with a sensitivity-based approach and found that annual stream fl ow in the Loess Plateau decreased signi fi cantly since the 1950s and surface runoff trends appear to dominate the stream fl ow trends in most of the catchments. Annual base fl ow exhibited mostly downward trends, but signi fi cant upward trends were also observed in 3 out of 38 gauging stations. Mean annual stream fl ow during 1979 2010 decreased by up to 65% across the catchments compared with the period of 1957 1978, indicating signi fi cant changes in the hydrological regime of the Loess Plateau. It is estimated that 70% of the stream fl ow reduction can be attributed to land use change, while the remaining 30% is associated with climate variability. Land use change because of the soil conservation measures and reduction in precipitation are the key drivers for the observed stream fl ow trends. These fi ndings are consistent with results of previous studies for the region and appear to be reasonable given the accelerated level of the soil conservation measures implemented since the late 1970s. Changes in sea surface temperature in the Paci fi c Ocean, as indicated by variations in El Nino – Southern Oscillation and phase shifts of the Paci fi c Decadal Oscillation, appear to have also affected the annual stream fl ow trends. The framework described in this study shows promising results for quantifying the effects of land use change and climate variability on mean annual stream fl ow of catchments within the Loess Plateau.

The catchments in the Loess Plateau in China have experienced significant land use change since the 1950s with a great number of soil conservation measures such as revegetation being implemented. Such soil conservation measures and climate variability have had considerable impacts on the annual streamflow from these catchments. However, much less is known about changes in groundwater storage as the period of direct groundwater storage measurements is too short to reliably infer groundwater storage trends. For this study, annual values of groundwater storage from 38 catchments in the Loess Plateau were estimated from daily streamflow records based on groundwater flow theory. It was found that over the period of record (viz. 1955 to 2010), statistically significant (p < 0.1) downward trends have been identified in 20 selected catchments with an average reduction of −0.0299 mm per year,mostly located in the northern part of the Loess Plateau. Upward groundwater storage trendswere observed in 10 catchments with an average increase of 0.00467 mm per year; these upward trends occurred in southern parts of the study area. Groundwater storage showed no statistically significant trends in 8 out of the 38 selected catchments. Soil conservation measures implemented in the Loess Plateau such as large-scale revegetation may have contributed to the estimated groundwater storage trends. Changes in sea surface temperature in the tropical Pacific Ocean, as indicated by shifts in climate variability modes such as El Niño-Southern Oscillation and the Pacific Decadal Oscillation, appear to have also contributed to the decreasing trends in groundwater storage in this region.

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

The most pronounced warming in the historical global climate record prior to the recent warming occurred over the first half of the 20th century and is known as the Early Twentieth Century Warming (ETCW). Understanding this period and the subsequent slowdown of warming is key to disentangling the relationship between decadal variability and the response to human influences in the present and future climate. This review discusses the observed changes during the ETCW and hypotheses for the underlying causes and mechanisms. Attribution studies estimate that about a half (40–54%; p > .8) of the global warming from 1901 to 1950 was forced by a combination of increasing greenhouse gases and natural forcing, offset to some extent by aerosols. Natural variability also made a large contribution, particularly to regional anomalies like the Arctic warming in the 1920s and 1930s. The ETCW period also encompassed exceptional events, several of which are touched upon: Indian monsoon failures during the turn of the century, the “Dust Bowl” droughts and extreme heat waves in North America in the 1930s, the World War II period drought in Australia between 1937 and 1945; and the European droughts and heat waves of the late 1940s and early 1950s. Understanding the mechanisms involved in these events, and their links to large scale forcing is an important test for our understanding of modern climate change and for predicting impacts of future change. This article is categorized under:Paleoclimates and Current Trends > Modern Climate Change

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.

Flash drought is a term and concept that has gained increasing attention in the research literature and media since it was first coined in the United States in the early 2000s to describe a drought that has undergone rapid intensification. In Australia the term has recently been used in reference to the 2017/18 drought in eastern Australia. Due to its rapid intensification, the impacts of flash droughts will likely occur too quickly for many of the usual drought-coping mechanisms to be deployed. This study proposes the use of the evaporative stress index (ESI), the standardized anomaly of the actual evapotranspiration to potential evapotranspiration ratio, to identify flash droughts in Australia computed using daily outputs from the Bureau of Meteorology’s land surface water balance model AWRA-L. The case study of the January 2018 flash drought in eastern Australia is used to assess and demonstrate the suitability of the ESI. Results show that the ESI accurately highlighted the event and offered potential for flash drought pre-warning by a few weeks. In addition, the availability of long term high-resolution outputs from AWRA-L offers the ability to investigate multiple flash drought events in detail for greater understanding and to inform stakeholders.

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.