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Australia is one of the regions strongly affected by the El Niño‐Southern Oscillation (ENSO). The recent 2020–2023 La Niña event was marked by record‐breaking rainfall and flooding across eastern Australia. The continuous wet conditions during the triple La Niña motivated us to explore the impacts of single‐year and multi‐year ENSO events on Australian rainfall using observational data sets. We find that, while there is no difference in the rainfall impacts during single or double El Niño events, Australian rainfall tends to increase in the third year of triple La Niña events compared to the first and second years. The enhanced rainfall impact during the third La Niña year occurs despite no strengthening of La Niña in the tropical Pacific, suggesting that other processes such as local rainfall‐soil moisture feedback may play a role in prolonging the effects of multi‐year La Niña events in Australia. Plain Language Summary: Australia is strongly affected by the El Niño‐Southern Oscillation (ENSO), with rainfall more likely to increase during La Niña and below‐average rainfall more common during El Niño. The recent 2020–2023 multi‐year La Niña was marked by continuous wet conditions across eastern Australia, leading to record‐breaking rainfall and flooding. Multi‐year La Niña events, where La Niña occurs in two or three consecutive austral summers, happened in about 50% of all La Niña events, including five triple La Niña events since 1900. We explored the impacts of multi‐year ENSO events on Australian rainfall and found that, while there is no difference in the rainfall impacts during single or double El Niño events, rainfall tends to increase in the third year of triple La Niña events compared to the first and second years. This rainfall increase occurs despite no strengthening of La Niña in the tropical Pacific Ocean, suggesting that local processes such as feedback between high/saturated soil moisture and rainfall may play a role in prolonging the effects of multi‐year La Niña events in Australia. Key Points: Eastern Australia tends to experience record‐breaking rainfall and flooding during La Niña eventsRainfall impact of multi‐year El Niño‐Southern Oscillation (ENSO) persists during double and triple events, despite no strengthening of ENSOAustralian rainfall increases in the third year of triple La Niña likely due to soil moisture‐rainfall feedback [ABSTRACT FROM AUTHOR]

The interannual relationships between the southern subtropical cell (SSTC) in the Indian Ocean (IO) and the El Niño‐Southern Oscillation (ENSO) are examined. The results demonstrate that the impacts of ENSO on the boreal winter IO SSTC display a notable negative skewness, with the amplification of the SSTC during La Niña being far stronger than its reduction during El Niño. This difference is mainly attributed to an asymmetry in anomalous meridional geostrophic transport, characterized by more robust southward (weaker northward) geostrophic transport anomalies during La Niña (El Niño) events. Further analyses reveal that the differing longitudinal positions of the ENSO‐related sea surface temperature anomaly (SSTA) are the primary drivers of the asymmetry in anomalous meridional geostrophic transport via the oceanic and atmospheric teleconnections. Compared to the warm SSTA in El Niño events, the La Niña‐related cool SSTA in the central‐eastern equatorial Pacific displays a greater westward extension, which induces stronger surface easterlies over the western equatorial Pacific, and then initiates a more substantial sea surface height anomaly (SSHA) in the southeast Indian Ocean (SEIO) through oceanic waveguides. This leads to a heightened zonal SSHA gradient over the southern IO, resulting in a larger anomalous meridional geostrophic transport. On the other hand, the westward extension of negative SSTA during La Niña winters triggers anomalous cyclonic northerlies along the western coast of Australia by shifting the Walker circulation westward. These coastal northerlies amplify the positive SSHA signals in the SEIO and enhance the anomalous meridional geostrophic transport, ultimately contributing to a more robust IO SSTC response. Plain Language Summary: The southern subtropical cell (SSTC), driven by wind over the Indian Ocean (IO), is characterized by southward surface flow, subduction in the subtropics, and upwelling in the tropics. This study revealed that the boreal winter SSTC weakens during El Niño and enhances during La Niña, with the latter exhibiting a notably stronger response, contrary to the expected El Niño/La Niña amplitudes. These asymmetric ENSO impacts predominantly result from disparities in anomalous meridional geostrophic transport. In‐depth analysis further uncovered that the distinct longitudinal positions of ENSO‐related sea surface temperature anomalies (SSTA) primarily drive the asymmetry in anomalous meridional geostrophic transport. During La Niña events, the cool SSTA in the central‐eastern equatorial Pacific extends significantly westward compared to the El Niño‐related warm SSTA, which is evident during both the preceding season and the contemporaneous winter. During the preceding season, this westwardly extended SSTA leads to a more substantial anomalous meridional geostrophic transport in the subsequent winters through the propagation of oceanic waveguides. In La Niña winters, the westward extension of negative SSTA further amplifies the anomalous meridional geostrophic transport by shifting the Walker circulation westward. These intensified meridional geostrophic transport anomalies ultimately result in a more pronounced SSTC response during La Niña events. Key Points: The boreal winter southern subtropical cell (SSTC) in the Indian Ocean displays a negative skewness in response to El Niño‐Southern Oscillation (ENSO)Such asymmetric SSTC responses are primarily attributed to an asymmetry in anomalous meridional geostrophic transportDiffering longitudes of ENSO‐related sea surface temperature anomaly cause the asymmetric meridional geostrophic transport via oceanic and atmospheric teleconnections [ABSTRACT FROM AUTHOR]

Forecasting using artificial neural networks (ANNs) has previously been demonstrated to provide skilful monthly and seasonal rainfall forecasts for many parts of the world, including Australia. However, few rainfall forecasting studies have been reported for lead times beyond 12 months, which can be very useful for flood and drought management, management of dam infrastructure for hydroelectricity generation and for agriculture This investigation examines monthly rainfall forecasts using ANNs for Gympie, Lismore and Brisbane in eastern Australia, locations that have experienced severe flooding associated with very heavy rainfall during the past two decades, as well as periods of drought. These locations have long continuous rainfall records extending back more than 100 years. Monthly rainfall forecasts were generated for these locations for each month using ANNs provided by Neurosolutions Infinity. Input variables comprised both local values of rainfall and temperatures and large-scale climate indices including the Southern Oscillation Index and the Inter-Decadal Pacific Oscillation. The study shows that lead times using ANNs can be extended without significant loss in forecast skill. Average monthly rainfall forecast skill with lead times of 12, 36, 60 and 84 months for the three sites lay in the range 34.8–54.1% relative to climatology. This compares very favourably with reported skill using methods based on physical climate models where skill is often about equivalent to climatology (0%). At longer lead times between 108 and 156 months the skill scores using ANNs decline into the range 10.8–26.6%. The application of ANN forecasting can be very valuable in providing the public with much better warnings of flood and drought conditions than currently given by the Australian Bureau of Meteorology, allowing sufficient lead time to take appropriate action. [ABSTRACT FROM AUTHOR]

The El Niño‐Southern Oscillation (ENSO) is considered an important driver of rainfall variability in Australia, amongst many other global locations. Despite knowledge of the expected modulation of seasonal rainfall by ENSO, there is no consistently used method to quantify the role that specific ENSO events play in driving the observed anomalous rainfall. In this manuscript we adapt the Fraction of Attributable Risk (FAR) method, commonly used to identify the anthropogenic impact on a particular event, to quantify the impact of ENSO on the occurrence of monthly rainfall anomalies. We also explicitly calculate the ENSO induced change in risk and the FAR for all observed spring rainfall rates for our eastern Australian regions. A prominent role for ENSO in driving the large spring 2022 rainfall anomalies is identified. Though we choose to focus on ENSOs impact on rainfall in various Eastern Australian regions, the results are applicable to other climate modes, regions and climatic variables. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) is considered an important driver of rainfall variability in Australia, amongst many other global locations. Despite understanding how ENSO is expected to alter rainfall, we do not currently quantify the role ENSO played in driving a observed rainfall anomaly in any given season. In this manuscript we adapt a method that is commonly used to identify the anthropogenic impact on a particular event; and instead, we quantify the impact of ENSO on the occurrence of monthly rainfall anomalies. We then calculate the ENSO‐induced change in risk for all observed spring rainfall rates for our selected eastern Australian regions. A prominent role for ENSO in driving large rainfall anomalies of spring 2022 is also identified. Though we choose to focus on ENSOs impact on rainfall in various eastern Australian regions in this study, the results are applicable to other climate modes, regions and climatic variables. Key Points: We adapt the commonly used Fraction of Attributable Risk method to attribute rainfall variability to the El Niño‐Southern OscillationWe present the ENSO induced change in risk and the FAR for all observed spring rainfall rates for three eastern Australian regionsThe increased spring 2022 East Australian rainfall was >5 times more likely, and largely attributed to the La Niña conditions present [ABSTRACT FROM AUTHOR]

This paper uses a 30 m record of valley alluviation in the Lockyer Creek, a major tributary of the mid-Brisbane River in Southeast Queensland, to document the timing and nature of Quaternary fluvial response. A combination of radiocarbon and optically stimulated luminescence dating reveals a sequence of major cut and fill episodes. The earliest aggradation phase is represented by a basal gravel unit, dating to ~220 ka (marine isotope sub-stage 7d), and although little evidence supports higher fluvial discharges during MIS 5, a MIS 3 fluvial episode characterised by incision and aggradation dates to ~60 ka. A penultimate phase of incision to a depth of 30 m prior to ~14 ka saw the lower Lockyer occupy its current position within the valley floor. The Lockyer Creek shows evidence of only minor fluvial activity during MIS 2, suggesting a drier LGM climate. The appearance of alternating fine- and coarse-grained units at about 2 ka is notable and may represent higher-energy flood conditions associated with a strengthening of El Niño Southern Oscillation activity as observed in the flood of 2011. The aggradation rate for this Holocene floodplain unit is ~11 times higher than the long-term rate. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) is often characterized through the use of sea surface temperature (SST) departures from their climatological values, as in the Niño-3.4 index. However, this approach is problematic in a changing climate when the climatology itself is varying. To address this issue, van Oldenborgh et al. proposed a relative Niño-3.4 SST index, which subtracts the tropical mean SST anomaly from the Niño-3.4 index and multiplies by a scaling factor. We extend their work by providing a simplified calculation procedure for the scaling factor, and confirm that the relative index demonstrates reduced sensitivity to climate change and multidecadal variability. In particular, we show in three observational SST datasets that the relative index provides a more consistent classification of historical El Niño and La Niña oceanic conditions that is more robust across climatological periods compared to the nonrelative index. Forecast skill of the relative Niño-3.4 index in the North American Multimodel Ensemble (NMME) and ACCESS-S2 is slightly reduced for targets during the first half of the year because subtracting the tropical mean removes a source of additional skill. For targets in the second half of the year, the relative and nonrelative indices are equally skillful. Observed ENSO teleconnections in 200-hPa geopotential height and precipitation during key seasons are sharper and explain more variability over Australia and the contiguous United States when computed with the relative index. Overall, the relative Niño-3.4 index provides a more robust option for real-time monitoring and forecasting ENSO in a changing climate. Significance Statement: The goal of this study is to further explore a relative sea surface temperature index for monitoring and prediction of El Niño–Southern Oscillation. Sea surface temperature indices are typically computed as a difference from a 30-yr climatological average, and El Niño and La Niña events occur when values exceed a certain threshold. This method is suitable when the climate is stationary. However, because of climate change and other lower-frequency variations, historical El Niño and La Niña events are reclassified depending on which climatological period is selected. A relative index is investigated to ameliorate this problem. [ABSTRACT FROM AUTHOR]

Fire danger poses a pressing threat to ecosystems and societies worldwide. Adequate preparation and forewarning can help reduce these threats, but these rely on accurate prediction of extreme fire danger. With the knowledge that climatic conditions contribute heavily to overall fire danger, this study evaluates the skill with which episodes of extreme fire danger in Australia can be predicted from the activity of large-scale climate driver patterns. An extremal dependence index for extreme events is used to depict the historical predictive skill of the Australian Bureau of Meteorology's subseasonal climate prediction system in replicating known relationships between the probability of top-decile fire danger and climate driver states at a lead time of 2–3 weeks. Results demonstrate that the El Niño Southern Oscillation, Southern Annular Mode, persistent modes of atmospheric blocking, Indian Ocean Dipole and Madden-Julian Oscillation are all key for contributing to predictability of fire danger forecasts in different regions during critical fire danger periods. Northwest Australia is found to be particularly predictable, with the highest mean index differences (>0.50) when certain climate drivers are active, compared with the climatological index mean. This integrated approach offers a valuable resource for decision-making in fire-prone regions, providing greater confidence to users relying on fire danger outlooks for key management decisions, such as those involved in the sectors of national park and forest estate management, agriculture, emergency services, health and energy. Furthermore, the results highlight strengths and weaknesses in both the Australian Fire Danger Rating System and the operational climate model, contributing additional information for improving and refining future iterations of these systems. [ABSTRACT FROM AUTHOR]

Aims: We investigate the associations between major Australian climate drivers and extreme weekly fire danger throughout the year. Methods: We use a composite-based approach, relating the probability of top-decile observed potential fire intensity to the positive and negative modes of the El Niño Southern Oscillation, Indian Ocean Dipole, Madden–Julian Oscillation, Southern Annular Mode, split-flow blocking and Subtropical Ridge Tasman Highs, both concurrently and at a variety of lag times. Key results: The chance of extreme fire danger increases over broad regions of the continent in response to El Niño and positive Indian Ocean Dipole events, the negative mode of the Southern Annular Mode, split-flow Blocking Index and Subtropical Ridge Tasman High, and Madden–Julian Oscillation phases 5, 6, 2 and 8 in Austral summer, autumn, winter and spring respectively. These relationships exist not only concurrently, but also when a climate event occurs up to 6 months ahead of the season of interest. Conclusions: These findings highlight the importance of considering the influence of diverse climate drivers, at a range of temporal lag periods, in understanding and predicting extreme fire danger. Implications: The results of this study may aid in the development of effective fire management strategies and decision-making processes to mitigate the impacts of fire events in Australia. This paper explores the relationships between the major forces influencing Australian weather and climate, and the chance of severe fire seasons. The findings could be valuable in decision making and preparation for upcoming fire seasons to avoid more seasons with devastating outcomes such as the 2019–2020 Black Summer. This article belongs to the Collection Fire and Climate. [ABSTRACT FROM AUTHOR]

Salinity in the Indonesian seas integrates regional oceanographic and atmospheric processes, such as Indonesian Throughflow (ITF) and monsoon rainfall. Here we present a multicentury (1777–1983) δ18O coral record from Nightcliff Reef, located in the Timor Passage off the coast of northern Australia, which we use to infer local salinity change. We show that Australian monsoon rainfall and ITF influence salinity at the study site. These reconstructed salinity changes in the Timor Passage correlate with changes in Pacific sea surface temperature (SST) modes, including the El Niño Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO). While environmental stress creates challenging conditions for coral growth, this record particularly tracks the central Pacific signature of ENSO‐driven interannual variability, in agreement with reconstructions of rainfall across northern Australia. The strength of interannual variance in the record follows fluctuations in other local ENSO‐sensitive rainfall reconstructions, demonstrating a strong regional ENSO signature. However, this regional pattern differs from variance in composite ENSO reconstructions, suggesting that the multi‐site nature of these reconstructions may create biases. Salinity variability on decadal and longer time scales occurs throughout the record. Some of these oscillations are consistent with other ITF‐sensitive coral records. Our new salinity record adds a strongly Pacific‐sensitive record to the existing suite of regional paleoclimate reconstructions. Relationships among these records highlight the complexity of salinity in the Indonesian seas and the controls on its variability. Plain Language Summary: Ocean circulation and rainfall control salinity in the Indonesian seas that link the eastern Indian and western Pacific Ocean. A major ocean current, the Indonesian Throughflow, transports comparatively warm and fresh water from the Pacific through this complex geographic "gateway" into the Indian Ocean, and the monsoon‐season rainfall introduces freshwater to surface waters across the region. Here we investigate changes in salinity off northern Australia using geochemical records from a coral core that spans more than 200 years (1777–1983). We show that coral oxygen isotopes reflect changes in Australian monsoon rainfall and Indonesian Throughflow strength. Our record reveals that salinity is strongly linked to Pacific sea surface temperature variability, with the strongest ties to the central Pacific. We find similarities between our record and other regional rainfall records, highlighting the important influence of Pacific climate systems (notably the El Niño Southern Oscillation, ENSO) on rainfall across northern Australia. Our record suggests periods of high and low ENSO variance that differs from those obtained by combining multiple records of ENSO. We suggest that combining data sets introduces inherent biases, which our approach avoids. The relationship between our record and Indonesian Throughflow records from other coral studies is strongest on decadal‐multidecadal timescales. Key Points: Coral δ18O from northern Australia reflects salinity changes that are driven by the Indonesian Throughflow and regional rainfallReconstructed salinity variations correlate with Pacific variability, particularly ENSO and central Pacific sea surface temperatureMultidecadal variations in the strength of interannual variability are consistent with local rainfall reconstructions [ABSTRACT FROM AUTHOR]

Anthropogenic alterations to river flow could have repercussions for flow-dependent species downstream but few studies account for these dynamic relationships or quantify impacts of altered river flow. Scylla serrata— a widely distributed portunid crab—was used as an example of a flow-dependent species to model impacts of altered flow on species abundance and catch. Crab population dynamics were modelled across a large semi-enclosed tropical sea in northern Australia. Environmental drivers, primarily river flow, but also temperature and the Southern Oscillation Index were linked to crab dynamics to explain variability in historical catches. Catch and abundance could then be predicted under altered flow scenarios. River flow significantly improved the ability to explain historical catches for some regions but not all, and the strength of this relationship varied across catchments. Altered flows had negligible effects for perennial rivers but for ephemeral and temporally variable rivers, predicted decreases in abundance and catch ranged from 36 to 46% on average. Our modelling approach showcases a way to dynamically and rigorously quantify impacts of altered river flow on a key species with potential to help inform natural resource management, including policy decisions on the timing, quantity, and method of water removed from rivers. [ABSTRACT FROM AUTHOR]

Generating plausible future climate time series is needed for bottom-up climate impact modeling, as well as downscaling climate model output for hydrological applications. A novel method for generating multisite daily stochastic climate series is developed based on 1) linear regression between climate teleconnection time series (e.g., IPO/SOI) and annual rainfall, 2) clustered method of fragments for subannual disaggregation, and 3) a regression-based approach to daily potential evapotranspiration (PET) for hydrological modeling. We demonstrate that bias (i.e., oversampling) occurs with the standard method of fragments disaggregation in the multisite context and show that selection of an analog year from clustered rainfall amounts provides better sampling properties than the standard method of fragments. Using hydrological data for southeastern Australia, we model runoff from observed and simulated rainfall and PET using the GR4J (Génie Rural à 4 paramètres Journalier) model. Simulated annual and daily rainfall and runoff characteristics from the new method are similar to existing methods, with improvements demonstrated in wet–wet transition probabilities and spatial (between-site) correlations. Significance Statement: In this paper we develop a novel method for generating multisite daily stochastic climate series regressing climate teleconnections (e.g., ENSO, IPO) to annual site rainfall, and disaggregation using a clustered version of the method of fragments. The modular nature of the method also allows for the possibility of the generation of replicates from GCM output of climate teleconnections, as well as perturbed climate futures for scenario-neutral modeling. Results demonstrate that rainfall and runoff metrics of interest for water resource modeling are reproduced well using the model. [ABSTRACT FROM AUTHOR]

This study examines the multiscale modulation of mean and extreme rainfall in Northeast (NE) Australia under different background modes of variability, which is a new aspect given the high-resolution and long-term observational datasets. Daily rainfall probability is significantly modified by the Madden–Julian oscillation (MJO), and its influence varies with the seasons and is associated with atmospheric circulation anomalies. Rainfall generally decreases during El Niño and increases during La Niña years; however, there is a notable spatial nuance to El Niño–Southern Oscillation (ENSO)-associated extreme rainfall, with some locations showing the opposite precipitation response to the typical ENSO–rainfall relationship. Despite more precipitation overall in La Niña years, the mean and extreme precipitation responses to the MJO appear to be stronger and more often statistically significant during El Niño compared to La Niña periods. The impact of ENSO on the MJO–rainfall relationship is stronger than the variation of the MJO itself with ENSO, and likely reflects a change in the MJO modulation of rain-bearing atmospheric processes. During El Niño periods, diurnal rainfall amplitude is generally stronger in the central and southern subtropical parts of the study area than during La Niña periods, while the opposite tendency occurs in the northern tropical part. The diurnal cycle of both mean and extreme precipitation is amplified during suppressed convection phases compared to enhanced convection phases of the MJO. In general, the peak time of diurnal cycle does not change with MJO regimes, but there are some notable differences in rainfall propagation between enhanced and suppressed MJO phases. Significance Statement: This study presents a new perspective on the relationship between precipitation in Northeast (NE) Australia and two important climate modes, the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO). Rainfall in NE Australia is strongly influenced by the MJO, ENSO, and their interaction, suggesting that climate models need to capture both individual climate modes and their interactions for reliable rainfall projections. These findings have societal climate risk implications, as NE Australia is an area prone to catastrophic flooding due to extreme rainfall. [ABSTRACT FROM AUTHOR]

The difficulties in using conventional mitigation techniques to maintain global mean temperatures well below 2 °C compared with preindustrial levels have been well documented, leading to so-called 'climate intervention' or 'geoengineering' research whereby the planetary albedo is increased to counterbalance global warming and ameliorate some impacts of climate change. In the scientific literature, the most prominent climate intervention proposal is that of stratospheric aerosol injection (SAI), although proposals for marine cloud brightening (MCB) have also received considerable attention. In this study, we design a new MCB experiment (G6MCB) for the UKESM1 Earth system model which follows the same baseline and cooling scenarios as the well-documented G6sulfur SAI scenario developed by the Geoengineering Model Intercomparison Project (GeoMIP) and compare the results from G6MCB with those from G6sulfur. The deployment strategy used in G6MCB injects sea-salt aerosol into four cloudy areas of the eastern Pacific. Despite MCB being intended as a technique to modify clouds, much of the radiative effect in G6MCB is found to derive from the direct interaction of the injected sea-salt aerosols with solar radiation. The results show that while G6MCB can achieve its target in terms of reducing high-end global warming to moderate levels, there are several side-effects. Some are common to SAI, including overcooling of the tropics, and residual warming of mid-and high latitudes. Others side effects specific to common choices of MCB regions include changes in monsoon precipitation, year-round increases in precipitation over Australia and the maritime continent and increased sea-level rise around western Australia and the maritime continent; these results are all consistent with a permanent and very strong La Niña-like response being induced in G6MCB. It should be stressed that the results are extremely dependent upon the strategy chosen for MCB deployment. As demonstrated by the development of SAI strategies which can achieve multiple temperature targets and ameliorate some of the residual impacts of climate change, much further work is required in multiple models to obtain a robust understanding of the practical scope, limitations, perils and pitfalls of any proposed MCB deployment. [ABSTRACT FROM AUTHOR]

Banding has historically been the most efficient method of marking individuals to gather large datasets on bird movement, especially in seabirds which spend a large proportion of their life-cycle at sea. The Australian Bird and Bat Banding Scheme has gathered such long-term records, including for the Australasian Gannet (Morus serrator). Between 1954 and 2022, a total of 12,583 bands were deployed at seven breeding sites in Australia, of which 522 were recovered dead. An additional 325 individuals from four banding sites in New Zealand were recovered along the Australian coastline. The effects of broadscale environmental indices on movement (inferred from banding recoveries) during the post-breeding period were investigated at two colonies with the most banding effort (Pope's Eye, Lawrence Rocks). Individuals >1 year old and those from Pope's Eye were recovered closer to their banding site. There were negative effects of current-year Southern Oscillation Index (SOI) and 1-year lagged Southern Annular Mode (SAM) on recovery distances for Lawrence Rocks individuals, while 2-year lagged SAM positively and negatively affected recovery distance and direction, respectively, for Pope's Eye individuals. The number of chicks banded (index of chick production) at Pope's Eye was negatively influenced by 1-year lagged SAM and 2-year lagged SOI, while the likelihood of recoveries of first-year individuals was positively influenced by 1-year lagged SAM. The results of the present study revealed a potential effect of environmental conditions on post-breeding movement with seemingly contrasting effects between colonies, and on reproduction, highlighting the usefulness of long-term banding and recovery efforts. [ABSTRACT FROM AUTHOR]

Most of Australia was in severe drought from 2018 to early 2020. Here we link this drought to the Pacific and Indian Ocean sea surface temperature (SST) modes associated with Central Pacific (CP) El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Over the last 20 years, the occurrence frequency of CP El Niño has increased. This study extends the previous understanding of eastern Pacific (EP) El Niño-Australian rainfall teleconnections, exhibiting that CP El Niño can bring much broader and stronger rainfall deficiencies than EP El Niño during austral spring (September–November) over the northern Australia (NAU), central inland Australia and eastern Australia (EAU). The correlations between SST fields and rainfall in three Cluster regions divided by clustering analysis also confirm this, with rainfall variability in most of Australia except southern Australia (SAU) most significantly driven by CP ENSO. Also, we demonstrate that the CP El Niño affects rainfall in extratropical EAU via the Pacific-South American (PSA) pattern. While the influence of EP El Niño is only confined in tropical NAU because its PSA pattern sits far too east to convey its variability. With the development of ENSO diversity since 2000, the footprint of El Niño on Australian rainfall has become more complex. [ABSTRACT FROM AUTHOR]

The Australian monsoon delivers seasonal rain across a vast area of the continent stretching from the far northern tropics to the semi‐arid regions. This article provides a review of advances in Australian monsoon rainfall (AUMR) research and a supporting analysis of AUMR variability, observed trends, and future projections. AUMR displays a high degree of interannual variability with a standard deviation of approximately 34% of the mean. AUMR variability is mostly driven by the El Niño‐Southern Oscillation (ENSO), although sea surface temperature anomalies in the tropical Indian Ocean and north of Australia also play a role. Decadal AUMR variability is strongly linked to the Interdecadal Pacific Oscillation (IPO), partially through the IPO's impact on the strength and position of the Pacific Walker Circulation and the South Pacific Convergence Zone. AUMR exhibits a century‐long positive trend, which is large (approximately 20 mm per decade) and statistically significant over northwest Australia. The cause of the observed trend is still debated. Future changes in AUMR over the next century remain uncertain due to low climate model agreement on the sign of change. Recommendations to improve the understanding of AUMR and confidence in AUMR projections are provided. This includes improving the representation of atmospheric convective processes in models, further explaining the mechanisms responsible for AUMR variability and change. Clarifying the mechanisms of AUMR variability and change would aid with creating more sustainable future agricultural systems by increasing the reliability of predictions and projections. This article is categorized under:Paleoclimates and Current Trends > Modern Climate Change [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The East Australian Current (EAC) is the western boundary current of the South Pacific Subtropical Gyre that transports warm tropical waters to higher southern latitudes and significantly impacts the climate of Australia and New Zealand. Modern observations show that the EAC has strengthened with rising global temperatures. However, little is known about the pre‐industrial variability of the EAC and the forcing mechanisms. Planktic foraminifera Globigerinoides ruber (white) Mg/Ca‐based sea surface temperature reconstructions offshore northeastern Australia between 15° and 26°S reveal an increase by ∼1.2°C after ∼1400 CE. We infer that the increase in temperature is related to a stronger EAC heat transport that is likely driven by a strengthening of the Southern Hemisphere subtropical gyre circulation due to a progressive shift of the Southern annular mode toward its positive phase and of El Niño‐Southern Oscillation toward more El Niño‐like conditions. Plain Language Summary: The East Australian Current (EAC) transports large amounts of heat out of the Western Pacific Warm Pool into the subtropics and subpolar regions, thereby regulating the local and global climate. The few existing reconstructions of past changes in transport and temperature of the EAC are contradictory resulting in a knowledge gap in long‐term variability of the southwest Pacific currents, which in turn hampers a reliable projection of future tropical and subtropical climate development. We use sea surface temperature reconstructions along the EAC path off northeastern Australia to estimate changes in the EAC heat transport over the past 4,000 years and its potential driving mechanisms. Our results reveal an increase in temperature after ∼1400 CE, which we relate to an intensification of the EAC strength. The strengthening of the EAC after ∼1400 CE is likely associated with a strengthening of the Southern Hemisphere subtropical gyre circulation due to a progressive shift of the Southern annular mode toward its positive phase and of El Niño‐Southern Oscillation toward more El Niño‐like conditions. Key Points: Mg/Ca‐based sea surface temperature reconstructions reveal an intensification of the East Australian Current (EAC) after ∼1400 CEA stronger EAC is likely driven by strengthening of the Southern Hemisphere subtropical gyre due to a Southern Annular Mode shift toward its positive phaseMore El Niño‐like conditions may also strengthen the EAC by an equatorward shift of the South Equatorial Current bifurcation latitude [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems are fully coupled with the climate. The planet has been greening owing to the increased vegetation growth in response to the changing atmosphere, which in turn has feedback on the climate. Greening has slowed down the rise in global land-surface air temperature mainly through a coincident increase of evapotranspiration and precipitation in wet regions. In dry regions, greening intensifies the decrease in soil moisture induced by greening-enhanced transpiration. Uncertain, however, is how the climate effects of greening in semi-arid lands might differ for variable wet and dry conditions. Here, we focus on the biosphere–atmosphere interactions in Australia by modeling the perturbation of vegetation changes under various states of sea surface temperature (SST), including the climatology mean, El Niño, and La Niña conditions. For the dry conditions of El Niño, greening exacerbates water stress and largely depletes the soil moisture, while for the wet conditions of La Niña, greening-enhanced evapotranspiration and precipitation resupply the soil moisture. For the normal conditions using the climatology mean SST, a small decrease in soil moisture occurs but with large spatial contrast because of heterogeneous changes of evapotranspiration and precipitation induced by greening. We emphasize that the alternating dry and wet conditions modulated by the large-scale climate variability are vital to understanding the response of climate to greening. Furthermore, vegetation-based warming mitigation policies need to be cautious when inferring distinct climate effects associated with greening. [ABSTRACT FROM AUTHOR]

Over the past few decades, Southeast Australia has experienced severe regional climatic events and some of the most extreme droughts on record, linked in part to influences from both the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). In this article, the extent to which austral winter rainfall anomalies, in years leading into co‐occurring ENSO and IOD events, are communicated specifically through variations in atmospheric fronts is quantified. The most extreme wet (dry) conditions occur in winters characterized by sea surface temperature anomaly patterns exhibiting features of La Niña‐Negative IOD (El Niño‐Positive IOD). It is found that most of these precipitation anomalies are related to changes in the precipitation associated with the passing of atmospheric fronts specifically. Although there is some suggestion that there are accompanying changes in the frequency of atmospheric fronts, the response appears to be dominated by changes in the amount of precipitation per individual atmospheric front. In addition, the distribution in the dynamic strength of individual atmospheric fronts remains relatively unchanged. [ABSTRACT FROM AUTHOR]

Short‐lived, fast‐growing species that contribute greatly to global capture fisheries are sensitive to fluctuations in the environment. Uncertainties in exact stock–environment relationships have meant that environmental variability and extremes have been difficult to integrate directly into fisheries management. We applied a management strategy evaluation approach for one of Australia's large prawn stocks to test the robustness of harvest control rules to environmental variability. The model ensemble included coupled environmental‐population models and an alternative catchability scenario fitted to historical catch per unit effort data. We compared the efficacy of alternative management actions to conserve marine resources under a variable environment while accounting for fisher livelihoods. Model fits to catch per unit effort were reasonably good and similar across operating models (OMs). For models that were coupled to the environment, environmental parameters for El Niño years were estimated with good associated precision, and OM3 had a lower AIC score (77.61) than the base model (OM1, 80.39), whereas OM2 (AIC 82.41) had a similar AIC score, suggesting the OMs were all plausible model alternatives. Our model testing resulted in a plausible subset of management options, and stakeholders selected a permanent closure of the first fishing season based on overall performance of this option; ability to reduce the risk of fishery closure and stock collapse; robustness to uncertainties; and ease of implementation. Our simulation approach enabled the selection of an optimal yet pragmatic solution for addressing economic and conservation objectives under a variable environment with extreme events. Article Impact statement: Simulation testing shows a seasonal closure protects fisher livelihoods and the stock in years with extreme environmental conditions. [ABSTRACT FROM AUTHOR]

• Large-scale climate drivers are tested for non-stationarity with extreme rainfall. • Extreme rainfall changes are well represented with a global temperature covariate. • Continental temperature fails to covary with short duration rainfall maxima. Flood estimates used in engineering design are commonly based on intensity–duration–frequency (IDF) curves derived from historical extreme rainfalls. Under global warming these extreme rainfalls are increasing, threatening the capacity of existing infrastructure to resist failure as IDF curves traditionally assume no change in rainfall magnitude. Hence, there is a need to investigate the implications of non-stationarity in extreme rainfalls used to derive IDFs across storm durations and annual exceedance probabilities (AEPs). One way of doing this is to incorporate covariates into the fitted probability distribution. However, there are few studies which examine non-stationarity in extreme rainfall using large-scale climate drivers as covariates, with little consensus on which covariate is the most appropriate. Here we evaluate non-stationarity in extreme rainfall across different durations, from the 1 in 5 AEP to the 1 in 100 AEP, using potential large-scale climate drivers including global and continental mean temperature, continental diurnal temperature range, continental dewpoint temperature, continental precipitable water, the Indian Ocean Dipole, the El Niño Southern Oscillation, and the Southern Annular Mode. These covariates are linked to the three parameters of the Generalized Extreme Value distribution to identify the most appropriate form of non-stationary probability model. We analyse 16 different storm durations from 6 min to 7 day annual maxima across 46 stations in Australia. Based on the Akaike Information Criteria, precipitable water is the superior covariate at a large proportion of stations irrespective of storm duration. However, when the modelled quantile changes are inspected, only global temperature is able to adequately capture the variability in changes across both storm duration and annual exceedance probability. Further, when regional average values of mean temperature, diurnal temperature range, dewpoint temperature and precipitable water were used as covariates, there was no improvement in the model performance compared to continental-wide covariates, particularly for short durations. The results using a mean global temperature covariate show that stationary historical rainfall quantile estimates are underestimated by 12 % – 9 % for frequent (1 in 5 AEP) and 23 % – 13 % for rare (1 in 100 AEP) short duration (6 min – 30 min) events. Moving forward our results suggests infrastructure design needs to incorporate non-stationarity in IDFs to ensure infrastructure and flood planning levels are not under-designed. [ABSTRACT FROM AUTHOR]

Wildfire can cause significant adverse impacts to society and the environment. Weather and climate play an important role in modulating wildfire activity. We explore the joint occurrence of global fire weather and meteorological drought using a compound events framework. We show that, for much of the globe, burned area increases when periods of heightened fire weather compound with dry antecedent conditions. Regions associated with wildfire disasters, such as southern Australia and the western USA, are prone to experiencing years of compound drought and fire weather. Such compound events have increased in frequency for much of the globe, driven primarily by increases in fire weather rather than changes in precipitation. El Ni n ̃ o Southern Oscillation is associated with widespread, spatially compounding drought and fire weather. In the Northern Hemisphere, a La Ni n ̃ a signature is evident, whereas El Ni n ̃ o is associated with such events in the tropics and, to a lesser degree, the Southern Hemisphere. Other climate modes and regional patterns of atmospheric circulation are also important, depending on the region. We show that the lengths of the fire weather seasons in eastern Australia and western North America have increased substantially since 2000, raising the likelihood of overlapping fire weather events in these regions. These cross-hemispheric events may be linked to the occurrence of El Ni n ̃ o, although the sea-surface temperature magnitudes are small. Instead, it is likely that anthropogenic climate change is the primary driver of these changes. [ABSTRACT FROM AUTHOR]

Wildfire magnitude and frequency have greatly escalated on a global scale. Wildfire products rich in biogenic elements can enter the ocean through atmospheric and river inputs, but their contribution to marine phytoplankton production is poorly understood. Here, using geochemical paleo-reconstructions, a century-long relationship between wildfire magnitude and marine phytoplankton production is established in a fire-prone region of Kimberley coast, Australia. A positive correlation is identified between wildfire and phytoplankton production on a decadal scale. The importance of wildfire on marine phytoplankton production is statistically higher than that of tropical cyclones and rainfall, when strong El Niño Southern Oscillation coincides with the positive phase of Indian Ocean Dipole. Interdecadal chlorophyll-a variation along the Kimberley coast validates the spatial connection of this phenomenon. Findings from this study suggest that the role of additional nutrients from wildfires has to be considered when projecting impacts of global warming on marine phytoplankton production. Wildfires are expected to increase in frequency and severity. Here the authors use geochemical paleo-reconstructions to show that over decadal timescales in Earth history wildfires are positively correlated with phytoplankton production off the coast of Australia. [ABSTRACT FROM AUTHOR]

Tick paralysis resulting from bites from Ixodes holocyclus and I. cornuatus is one of the leading causes of emergency veterinary admissions for companion animals in Australia, often resulting in death if left untreated. Availability of timely information on periods of increased risk can help modulate behaviors that reduce exposures to ticks and improve awareness of owners for the need of lifesaving preventative ectoparasite treatment. Improved awareness of clinicians and pet owners about temporal changes in tick paralysis risk can be assisted by ecological forecasting frameworks that integrate environmental information into statistical time series models. Using an 11-year time series of tick paralysis cases from veterinary clinics in one of Australia's hotspots for the paralysis tick Ixodes holocyclus, we asked whether an ensemble model could accurately forecast clinical caseloads over near-term horizons. We fit a series of statistical time series (ARIMA, GARCH) and generative models (Prophet, Generalised Additive Model) using environmental variables as predictors, and then combined forecasts into a weighted ensemble to minimise prediction interval error. Our results indicate that variables related to temperature anomalies, levels of vegetation moisture and the Southern Oscillation Index can be useful for predicting tick paralysis admissions. Our model forecasted tick paralysis cases with exceptional accuracy while preserving epidemiological interpretability, outperforming a field-leading benchmark Exponential Smoothing model by reducing both point and prediction interval errors. Using online particle filtering to assimilate new observations and adjust forecast distributions when new data became available, our model adapted to changing temporal conditions and provided further reduced forecast errors. We expect our model pipeline to act as a platform for developing early warning systems that can notify clinicians and pet owners about heightened risks of environmentally driven veterinary conditions. Author summary: Tick-borne illnesses constitute a diverse group of debilitating conditions for pet dogs and cats around the world. In Australia, thousands of domestic dogs are admitted to emergency veterinary clinics due to tick paralysis each year. These admissions are highly seasonal and may be associated with changing environmental conditions, suggesting models that learn from environmental patterns to forecast the oncoming tick season could inform pet owners and clinicians about changing risks. In this paper we use a series of statistical forecasting models to analyse and predict tick paralysis admissions to veterinary clinics in a tick paralysis hotspot in Queensland, Australia. Our approach is novel in that we combine individual models into a superior ensemble that is trained to reduce forecast uncertainty, giving more accurate estimates of what the coming tick season will look like. Our model consistently outperforms a field-leading benchmark while uncovering important patterns about environmental drivers of paralysis tick exposure, including changes to levels of moist vegetation and maximum temperature. We also demonstrate how our model can be used to automatically produce forecasts of tick paralysis admissions as new data become available. This can have important implications for designing improved early warning systems for tick-borne illness. [ABSTRACT FROM AUTHOR]

Climate change is expected to significantly impact bird species through changes to breeding and survival. Malleefowl (Leipoa ocellata) are threatened mound-building birds that persist in uncleared mallee and shrubland vegetation in semi-arid parts of southern Australia. Our aim was to understand the relationship between environmental factors and mound breeding activity (a proxy for population trends) to identify likely climate change impacts and possible proactive management actions. We compared annual activity at grids that encompassed groups of mounds at six sites in South Australia for up to 24 years with a range of environmental and habitat variables, focussing on variables predicted to change with a warming climate. Mound activity declined significantly over the study period at five of the six sites. Activity was positively associated with increased cumulative rain in the previous 2 years, lower average maximum temperatures in the winter, higher-than-average Southern Oscillation Index (i.e. more rain) 2 years before breeding and greater winter vegetation cover. These results suggest that moisture and vegetation cover are important for higher breeding activity. Climate change is predicted to lead to drier conditions and more frequent fires in our study region, suggesting that Malleefowl populations will continue to decline. We urge conservation practitioners to minimise climate change impacts through implementing proactive management actions that increase habitat quality for Malleefowl: fire management to reduce the scale of fire events and controlling introduced and overabundant native herbivores to preserve vegetation cover, retain soil moisture, increase food resources and protect from temperature extremes. [ABSTRACT FROM AUTHOR]

This paper presents the development of the Wavelet Artificial Neural Networks (WANN) model to forecast seasonal rainfall in Queensland, Australia, using the Inter-decadal Pacific Oscillation (IPO), Southern Oscillation Index (SOI), and Nino3.4 climate indices as predictors. Eight input sets with different combinations of predictive variables from 1908 to 2016 were considered to develop forecast models for ten selected rainfall stations in Queensland, Australia. The outcomes of WANN modeling are compared with Artificial Neural Networks (ANN). Moreover, the skillfulness of the WANN in comparison to the current climate prediction system used by the Australian Community Climate Earth-System Simulator–Seasonal (ACCESS–S) and climatology forecasts are investigated. Besides, the WANN predictions are compared with two other conventional approaches like autoregressive integrated moving average (ARIMA) and multiple linear regression (MLR) for further investigations. The comparisons indicated that the WANN achieves the lower average root mean square error (RMSE) in all the stations with 112.2mm compared to ANN with 178.9mm, ACCESS-S with 281.8mm, climatology prediction with 279.7mm, MLR with 195.1mm, and ARIMA with 187.7mm. The WANN seasonal rainfall forecasts are more accurate than the ANN, ACCESS-S, Climatology, MLR, and ARIMA by 37%, 60%, 53%, 42%, and 40%, respectively. It was also found that the ACCESS-S underestimates the extreme seasonal rainfall during the testing period up to 80%, while it is limited to 21% for the WANN among the selected stations. The results show that the WANN model outperforms the MLR, ARIMA, climatology, ACCESS-S, and ANN forecasts in all the selected stations. [ABSTRACT FROM AUTHOR]

Fire is an essential component of tropical savannas, driving key ecological feedbacks and functions. Indigenous manipulation of fire has been practiced for tens of millennia in Australian savannas, and there is a renewed interest in understanding the effects of anthropogenic burning on savanna systems. However, separating the impacts of natural and human fire regimes on millennial timescales remains difficult. Here we show using palynological and isotope geochemical proxy records from a rare permanent water body in Northern Australia that vegetation, climate, and fire dynamics were intimately linked over the early to mid-Holocene. As the El Niño/Southern Oscillation (ENSO) intensified during the late Holocene, a decoupling occurred between fire intensity and frequency, landscape vegetation, and the source of vegetation burnt. We infer from this decoupling, that indigenous fire management began or intensified at around 3 cal kyr BP, possibly as a response to ENSO related climate variability. Indigenous fire management reduced fire intensity and targeted understory tropical grasses, enabling woody thickening to continue in a drying climate. [ABSTRACT FROM AUTHOR]

Summary: To identify patterns in the temporal dynamics and spatial organization of kangaroo subpopulations that are commercially harvested, we fitted multivariate autoregressive state‐space (MARSS) models to time series of kangaroo abundance from the main harvest zones of eastern Australia (1990–2019 for New South Wales and 1984–2019 for Queensland). We found that the responses of most populations to process variation, that is variation due to environmental or demographic stochasticity were correlated and that populations responded synchronously to environmental changes. Furthermore, we examined the influence of the covariates lagged rainfall, Southern Oscillation Index (SOI) and harvest rate on kangaroo abundance. We found that lagged rainfall had a positive influence, SOI and harvest rate had negative influences but the influence of covariates was not consistent across species or between subpopulations. In terms of population spatial structure, the analysis identified two subpopulations of Red Kangaroo (Osphranter rufus) in New South Wales and four subpopulations of grey kangaroos (a combination of Eastern Grey Kangaroo (Macropus giganteus) and Western Grey Kangaroo (Macropus fuliginosus)), which appeared to be associated with a rainfall gradient from east‐west. In Queensland, separate subpopulations were identified in each of the three main harvest management zones for both Red Kangaroo and Eastern Grey Kangaroo. The implications of these results for the management of commercially harvested kangaroos are discussed. [ABSTRACT FROM AUTHOR]

Freshwater is a critical input to estuaries but is under increasing demand to support upstream human activities. In this study, otolith biochronology was used to quantify the relationship between river discharge and juvenile growth rates of barramundi (Lates calcarifer) in three regions of the Gulf of Carpentaria in northern Australia. In all regions, river discharge had a strong positive effect on juvenile growth rates. Models were also developed which incorporated the Southern Oscillation Index (SOI) and the Madden–Julian Oscillation (MJO). SOI values corresponding to La Niña events had strong positive consequences for juvenile barramundi growth rates in all regions, and the intensity of positive wet season MJO pulses had a strong positive effect on growth rates in the perennially flowing river, but not the intermittently flowing rivers. The consequences of three hypothetical water development scenarios were estimated for the perennial river. The model predicted a 12%, 8% and 1% reduction in annual barramundi growth rates under proposed scenarios for 18%, 8%, and 3% reduction in river discharge, respectively. Fish growth is a robust, quantitative metric that can be monitored pre and post water resource development to identify the least impactful development scenario and monitor its compliance and success through time. [ABSTRACT FROM AUTHOR]

This study investigates the underlying climate processes behind the largest recorded mangrove dieback event along the Gulf of Carpentaria coast in northern Australia in late 2015. Using satellite-derived fractional canopy cover (FCC), variation of the mangrove canopies during recent decades are studied, including a severe dieback during 2015–2016. The relationship between mangrove FCC and climate conditions is examined with a focus on the possible role of the 2015–2016 El Niño in altering favorable conditions sustaining the mangroves. The mangrove FCC is shown to be coherent with the low-frequency component of sea level height (SLH) variation related to the El Niño Southern Oscillation (ENSO) cycle in the equatorial Pacific. The SLH drop associated with the 2015–2016 El Niño is identified to be the crucial factor leading to the dieback event. A stronger SLH drop occurred during austral autumn and winter, when the SLH anomalies were about 12% stronger than the previous very strong El Niño events. The persistent SLH drop occurred in the dry season of the year when SLH was seasonally at its lowest, so potentially exposed the mangroves to unprecedented hostile conditions. The influence of other key climate factors is also discussed, and a multiple linear regression model is developed to understand the combined role of the important climate variables on the mangrove FCC variation. [ABSTRACT FROM AUTHOR]

Sea surface height (SSH) along the west coast of Australia is key to local climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. This study provides a method to predict interannual variability in SSH along the west coast of Australia using a simple 1.5‐layer dynamical ocean model forced by a statistical atmospheric model for ENSO‐related winds. The model has realistic coastlines and is driven by reanalysis surface winds regressed onto an ENSO index. The model when run in hindcast mode to predict past variability can simulate tide gauge observations at Fremantle along the west coast of Australia up to 13 months in advance, which outperforms persistence. We conclude that this methodology can be useful as a baseline for gauging the performance of more sophisticated forecast models for predicting SSH variations along the west coast of Australia. Plain Language Summary: Sea surface height (SSH) along the west coast of Australia is key to regional climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. Previous studies predicted interannual variability in SSH in this region using sophisticated ocean‐atmosphere coupled general circulation models, but their ocean models had coarse horizontal resolution, required to reduce computational burden. This study provides a much simpler method to predict SSH variability along the west coast of Australia using a simple ocean dynamical model with realistic coastlines forced by ENSO‐related atmospheric winds. Our model, run in hindcast mode to predict past SSH variability, is able to simulate SSH anomalies along the west coast of Australia up to 13 months in advance. A true forecast system to predict future variations would also require prediction of ENSO. However, this methodology can be useful as a baseline for gauging the performance of more sophisticated model forecast systems. Key Points: Interannual variability in sea level along the west Australian coast can be predicted up to 13 months in advance using a simple ocean modelTo illustrate, the model is run in hindcast mode forced remotely by Pacific surface winds related to El Niño Southern OscillationModel hindcasts generally outperform persistence forecasts in terms of anomaly correlation and root‐mean‐squared differences [ABSTRACT FROM AUTHOR]

Decadal and multidecadal variability in the ERSSTv5 global SST dataset are studied in terms of implicit fast (noise) and slow (signal) processes that affect variability on decadal time scales. Using a new method that better estimates the fast, or noise, component of decadal variability, estimates of the modes of variability in the slow component are possible. The fast component of decadal variability has a leading fast mode, which explains 62% of the variance, and it is shown that this fast variability, or decadal climate noise, is well represented by any of the indices associated with intradecadal or interannual variability in the tropical Pacific Ocean. Three slow modes are identified, representing 69% of the slow multidecadal variance, after removing the radiative forcing trend. These modes are shown to be related to variability in the Atlantic multidecadal oscillation (AMO) and SST multidecadal variability in the central western Pacific and in the Indian Ocean gyre region, respectively. The first and third slow modes represent two phases of a propagating mode with a period of about 80 years. The second slow mode represents multidecadal variability of the western Pacific warm pool, which is less robust than the other two and shown to be weakly related to the AMO with a lag of about 30 years; fast variability in this region is related to the leading fast mode. Three regions of significant slow variability are identified south of Australia, south of Africa, and near the Drake Passage in association with the Antarctic Circumpolar Current. [ABSTRACT FROM AUTHOR]

Australia, the driest inhabited continent, is prone to natural disasters, such as droughts, floods, bushfires, and heatwaves. Strong climate variability causes recurring threats to water supply, agriculture, and the environment. Improving our insight into changes in hydroclimatic patterns is required to provide useful information for society. Previous studies mainly focused on the causes of extreme wet or dry events in specific periods and their impacts on agriculture and ecosystems. An understanding of long‐term spatio‐temporal patterns of wetting and drying in Australia is still lacking. Here we show, based on analyses of Gravity Recovery and Climate Experiment satellite derived terrestrial water storage and extended datasets, that there are four consecutive periods of seesaw wetting and drying between eastern and western Australia in the past five decades. The seesaw phenomenon is characterized by eastern Australia gaining water, while western Australia is losing water, and vice versa. Strong La Niña induced continent‐wide wetting, resets this pattern, leaving each seesaw to last for 11 ± 5 years. We provide one possible mechanism related to vegetation response to climate variability and its feedback on hydrological processes to explain the seesaw pattern. The identified recurring seesaw pattern indicates that society would need to become more adaptive in managing forest, water, and disaster risks in the wake of a next strong La Niña induced continent‐wide wetting in Australia. Plain Language Summary: Here, we report for the first time a vegetation mediated seesaw wetting/drying phenomenon between eastern and western Australia. The seesaw phenomenon is characterized by eastern Australia gaining water, while western Australia is losing water, and vice versa. It is reset by strong La Niña induced continent‐wide wetting. The seesaw phase seems to depend on vegetation cover anomaly prior to the strong La Niña event, and can be explained by subsequent vegetation and soil moisture interactions. This finding provides society with valuable reference for managing forest, water, and disaster risks in the wake of a next strong La Niña induced continent‐wide wetting in Australia. Key Points: A seesaw wetting/drying phenomenon between eastern and western Australia is revealed for the first timeThis terrestrial water storage (TWS) seesaw pattern is reset by strong La Niña induced continent‐wide wettingThe TWS seesaws appear to be resulting from vegetation mediated hydrological responses to decadal precipitation variability [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) affects global climate and ecosystems, but a recent shift toward more frequent central Pacific (CP) El Niño events could alter these relationships. Here, we show strong responses of the terrestrial carbon cycle to CP ENSO, exceeding even those to canonical eastern Pacific (EP) ENSO. Annual GPP of both global tropical forests and semiarid ecosystems were reduced by ∼0.3–0.5 Pg C yr−1 K−1 increase in CP sea surface temperatures (SSTs), which also reduced net ecosystem production of key tropical and semiarid regions like the Amazon and Australia, but with smaller (and generally not significant) responses to EP SSTs. Given these large negative responses of ecosystem production to CP SSTs, our results suggest that a recent shift toward CP‐dominated ENSO events could further alter Earth's terrestrial carbon cycle, especially when coupled with possible increases in ENSO amplitude with continued warming. Plain Language Summary: El Niño (warmer‐than‐normal tropical Pacific sea surface temperatures [SSTs]) usually causes warming of air temperatures across most of Earth's surface and enhanced dryness in many tropical regions, while La Niña (cooler‐than‐normal tropical Pacific SSTs) usually has the opposite effect. Global photosynthesis is usually reduced following El Niño but enhanced following La Niña. However, not all El Niño and La Niña events are the same: some are dominated by temperature changes in the eastern Pacific (EP), some by changes in the central Pacific (CP), and some by mixtures of the two. We show that global photosynthesis, especially in tropical forests and semiarid ecosystems, is particularly sensitive to CP SSTs, likely reflecting enhanced air temperature and dryness throughout most of the tropics following CP El Niño. Forecasts of both climate and vegetation activity often rely on knowledge of El Niño, but these forecasts might be improved using information on which "type" of El Niño is dominant. Further, CP El Niños have recently become more common than EP El Niños. Key Points: Responses of gross primary production to central Pacific El Niño are generally stronger and more coherent than to eastern Pacific El NiñoTropical forests and semiarid ecosystems in South America, Africa, and Australia respond most negatively to central Pacific El NiñoThe Sahel was the only region with consistently stronger responses to eastern than to central Pacific sea surface temperatures [ABSTRACT FROM AUTHOR]

Using an extended 120‐year record of El Niño events, we distinguish between central Pacific (CP) and eastern Pacific (EP) types to show that the strength of CP events is a factor in the amplitude and sign of the impact on rainfall over southeastern Australia. Both weak and strong CP events cause widespread rainfall deficits in Australia during the onset phase from April to September. However, this relationship reverses over southeastern Australia including the Murray Darling Basin river catchment region for the strongest CP events after October, leading to positive rainfall anomalies during the mature phase of strong CP El Niños. This reversal can be explained by a change in the circulation over eastern Australia from drier, more westerly orientated flow to moister, more easterly onshore flow. These findings may help with seasonal prediction efforts to predict drought‐breaking rain such as occurred in early 2020. Plain Language Summary: El Niño Southern Oscillation events are extremely important for many countries around the world due to their impacts on rainfall. By separating El Niño into central Pacific (CP) and eastern Pacific (EP) events, we show that the strength of a CP event controls the rainfall amount for southeastern Australia. The stronger a CP event is, the drier it is over Australia during the onset phase from April to September. But after October during the mature phase of El Niño, the strongest CP events lead to more rainfall than normal over the southeast Australian river catchment known as the Murry Darling Basin, whereas the weakest CP events lead to less rainfall than normal. This relationship is strongest in January to March around the time that the CP event is fully developed. For the strongest CP events, this can be explained by a change in the circulation from drier, more westerly flow during the onset phase to moister, more easterly onshore flow during the mature phase. This finding is important for agricultural and water resources planning efforts in the Murry Darling Basin region and may help with seasonal prediction efforts to predict drought‐breaking rain such as occurred in early 2020. Key Points: The strength of central Pacific (CP) El Niño events has a significant impact on rainfall over southeastern AustraliaStrong CP events cause Australian rainfall deficits during onset but enhanced rainfall over southeastern Australia during the mature phaseThis can be explained by a circulation change over eastern Australia from drier, more westerly flow to moister, more easterly onshore flow [ABSTRACT FROM AUTHOR]

The hydroxyl radical (OH) is the primary atmospheric oxidant responsible for removing many important trace gases, including methane, from the atmosphere. Although robust relationships between OH drivers and modes of climate variability have been shown, the underlying mechanisms between OH and these climate modes, such as the El Niño–Southern Oscillation (ENSO), have not been thoroughly investigated. Here, we use a chemical transport model to perform a 38 year simulation of atmospheric chemistry, in conjunction with satellite observations, to understand the relationship between tropospheric OH and ENSO, Northern Hemispheric modes of variability, the Indian Ocean Dipole, and monsoons. Empirical orthogonal function (EOF) and regression analyses show that ENSO is the dominant mode of global OH variability in the tropospheric column and upper troposphere, responsible for approximately 30 % of the total variance in boreal winter. Reductions in OH due to El Niño are centered over the tropical Pacific and Australia and can be as high as 10 %–15 % in the tropospheric column. The relationship between ENSO and OH is driven by changes in nitrogen oxides in the upper troposphere and changes in water vapor and O1D in the lower troposphere. While the correlations between monsoons or other modes of variability and OH span smaller spatial scales than for ENSO, regional changes in OH can be significantly larger than those caused by ENSO. Similar relationships occur in multiple models that participated in the Chemistry–Climate Model Initiative (CCMI), suggesting that the dependence of OH interannual variability on these well-known modes of climate variability is robust. Finally, the spatial pattern and r2 values of correlation between ENSO and modeled OH drivers – such as carbon monoxide, water vapor, lightning, and, to a lesser extent, NO2 – closely agree with satellite observations. The ability of satellite products to capture the relationship between OH drivers and ENSO provides an avenue to an indirect OH observation strategy and new constraints on OH variability. [ABSTRACT FROM AUTHOR]

This study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December–February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS of prior seasons and DJF rainfall, we note that SSS of the Indo-Pacific warm pool region [SSSP (150°E–165°W and 10°S–10°N) and SSSI (50°–95°E and 10°S–10°N)] covaries with Australian rainfall, particularly in the northeast region. Composite analysis that is based on high or low SSS events in the SSSP and SSSI regions is performed to understand the physical links between the SSS and the atmospheric moisture originating from the regions of anomalously high or low, respectively, SSS and precipitation over Australia. The composites show the signature of co-occurring La Niña and negative Indian Ocean dipole with anomalously wet conditions over Australia and conversely show the signature of co-occurring El Niño and positive Indian Ocean dipole with anomalously dry conditions there. During the high SSS events of the SSSP and SSSI regions, the convergence of incoming moisture flux results in anomalously wet conditions over Australia with a positive soil moisture anomaly. Conversely, during the low SSS events of the SSSP and SSSI regions, the divergence of incoming moisture flux results in anomalously dry conditions over Australia with a negative soil moisture anomaly. We show from the random-forest regression analysis that the local soil moisture, El Niño–Southern Oscillation (ENSO), and SSSP are the most important precursors for the northeast Australian rainfall whereas for the Brisbane region ENSO, SSSP, and the Indian Ocean dipole are the most important. The prediction of Australian rainfall using random-forest regression shows an improvement by including SSS from the prior season. This evidence suggests that sustained observations of SSS can improve the monitoring of the Australian regional hydrological cycle. [ABSTRACT FROM AUTHOR]

Indian Ocean Dipole (IOD), a major climate variability in the tropics which drives the abiotic stress associated with heavy rainfalls and severe droughts, is not much understood in terms of its role in the carbon cycle, while El Niño‐Southern Oscillation (ENSO)‐related terrestrial carbon cycle variation has been intensively studied. Here, we investigate IOD's impact on land photosynthesis over the Indian ocean rim countries during austral spring using satellite‐based gross primary productivity (GPP) and Earth System Model simulations produced in the Coupled Model Intercomparison Project Phase 6 (CMIP6). IOD independently affects GPP with significant positive partial correlation coefficients (pcor) over most of Africa and India, and negative pcor over southern China, Indo‐China peninsula, maritime continent, and Australia, mostly driven by precipitation variations; this obviously differs from the widespread significant negative pcor pattern induced by ENSO. The recent extremely positive IOD in 2019 caused the canonical IOD‐affected GPP patterns, however, with its extreme impacts. Furthermore, though large inter‐model spreads exist, the CMIP6 multimodel median can basically capture the main characteristics of IOD‐affected precipitation and GPP patterns. Importantly, IOD is predicted to occur more frequently in future warming scenarios. Model future projections suggest that it will exert larger impacts on GPP variations over central and eastern Africa, Sumatra, western and southeastern Australia with stronger pcor and enhanced explained variance, but less impacts over southern Africa, east India, Indo‐China peninsula, and northeastern Australia. Therefore, besides ENSO, understanding the IOD impacts can provide us new insights into regional and global carbon cycle interannual variability. Plain Language Summary: Indian ocean dipole (IOD) is a major climate variability in the tropics, acting as an important determinant of regional climate variations. However, its role in the carbon cycle received less attention. Here we explore the impact of IOD events on land photosynthesis over the Indian ocean rim countries during austral spring based on satellite‐based gross primary productivity (GPP) and historical and future simulations in 10 Earth System models. We suggest that IOD can positively impact on GPP over most of Africa and India, but negatively impact over southern China, Indo‐China peninsula, maritime continent, and Australia, which are mostly driven by heavy rainfalls and severe droughts associated with its two sea surface temperature poles. The recent extremely positive IOD in 2019 resulted in the canonical but extreme IOD‐affected GPP patterns. Furthermore, multimodel future projections suggest that the occurrence of IOD events will be more frequent in future warming scenario. IOD will exert larger impacts on GPP variations over the central and eastern Africa, Sumatra, western and southeastern Australia, but lower impacts over southern Africa, east India, the Indo‐China peninsula, and northeastern Australia. Understanding the IOD impacts can provide us new insights into regional and global carbon cycle interannual variability. Key Points: Indian Ocean dipole can exert contrasting impacts on gross primary productivity (GPP) over Indian Ocean rim countries driven by precipitation variationsThe recent extremely positive Indian Ocean Dipole (IOD) in 2019 caused the canonical but extreme IOD‐affected GPP patternsMultimodel future projections suggest that IOD will occur more frequently with larger impacts on GPP, especially over eastern Africa [ABSTRACT FROM AUTHOR]

Australia plays an important role in the global terrestrial carbon cycle on inter-annual timescales. While the Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations of net biome production (NBP) and the carbon stored in vegetation between 1901 to 2018 from 13 DGVMs (TRENDY v8 ensemble). We focused our analysis on both Australia's short-term (inter-annual) and long-term (decadal to centennial) terrestrial carbon dynamics. The TRENDY models simulated differing magnitudes of NBP on inter-annual timescales, and these differences contributed to carbon accumulation in the vegetation on decadal to centennial timescales (-4.7-9.5 PgC). We compared the TRENDY ensemble to several satellite-derived datasets and showed that the spread in the models' simulated carbon storage resulted from varying changes in carbon residence time rather than differences in net carbon uptake. Differences in simulated long-term accumulated NBP between models were mostly due to model responses to land-use change. The DGVMs also simulated different sensitivities to atmospheric carbon dioxide (CO2) concentration, although notably, the models with nutrient cycles did not simulate the smallest NBP response to CO2. Our results suggest that a change in the climate forcing did not have a large impact on the carbon cycle on long timescales. However, the inter-annual variability in precipitation drives the year-to-year variability in NBP. We analysed the impact of key modes of climate variability, including the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on NBP. While the DGVMs agreed on sign of the response of NBP to El Nino and La Nina, and to positive and negative IOD events, the magnitude of inter-annual variability in NBP differed strongly between models. In addition, we identified differences in the timing of simulated phenology and fire dynamics associated with differences in simulated/prescribed vegetation composition and process representation. Model disagreement in simulated vegetation carbon, phenology and apparent carbon residence time, indicates the models have different types of vegetation cover across Australia (whether prescribed or emergent). Our study highlights the need to evaluate parameter assumptions and the key processes that drive vegetation dynamics, such as phenology, mortality and fire, in an Australian context to reduce uncertainty across models. [ABSTRACT FROM AUTHOR]

Understanding recruitment variability in marine fisheries has benefits for the stock management and dependent fishers' ability to plan their income. Here, we overview past and new research on the complex recruitment dynamics of redleg banana prawns Penaeus indicus in Australia's Joseph Bonaparte Gulf to assess themes dating back to the time of Hjort and identify new challenges. During 2015 and 2016, redleg prawn catches and catch per unit effort decreased to anomalously low levels, suggesting a substantial decrease in prawn biomass. We hypothesized that low catches could be explained by temporary drops in sea level and rainfall potentially reducing the ability of postlarvae to reach their nursery ground. We contend that very bad prawn catch years may be predicted using two variables that are possible drivers of recruitment—the January Southern Oscillation Index and the combined January to February cumulative rainfall. However, due to challenges in verifying and defining such environmental relationships for inclusion in a stock assessment, we propose development of a harvest strategy framework to support management recommendations. Our study highlights the increasing role of anthropogenic climate change in exaggerating the impacts of environmental drivers on recruitment processes and the need to also focus on multidisciplinary research. [ABSTRACT FROM AUTHOR]

Australia suffered a long‐lasting extensive drought in 2019 with catastrophic wildfires creating about $4.4 billion damages, the worst record in the recent four decades. Concurrent with this extreme drought, the tropical Indo‐Pacific oceans exhibited an extraordinary combination of sea surface temperature (SST) anomalies, characterized by a Central‐Pacific (CP) El Niño event with westernmost location and the third strongest positive Indian Ocean Dipole (IOD) event. We here show evidence that this unique combination was responsible for the pan‐Australian drought as a westward located CP El Niño event and a strong positive IOD event can exacerbate precipitation reduction in northeastern and southern Australia, respectively. These continent‐wide extreme droughts could become more frequent over Australia in a warming world, considering projected increases in both CP El Niño and extreme positive IOD events superimposed on secular warming and drying trends. Plain Language Summary: Australia is the driest inhabited continent in the world, 70% of which is either arid or semiarid land. During 2019, Australia was ravaged by the worst drought in decades with devastating wildfires destroying around 3,000 homes and affecting about one billion animals. The physical mechanisms driving this extreme drought remains unclear. Concurrent with this long‐lasting continent‐wide drought, the Indo‐Pacific oceans showed pronounced sea surface temperature anomalies associated with a record westernmost‐located Central Pacific (CP) El Niño event and the third strongest Indian Ocean Dipole (IOD) event co‐occurring. Our observational diagnostics and numerical model experiments show that these two compounding events caused atmospheric circulation anomalies that were responsible for the extreme precipitation deficiencies over Australia. With global warming, both CP El Niño and extreme positive IOD events are projected to become more frequent, which hints to increased risk of the severe Australian droughts in the future. Key Points: Australia suffered a long‐lasting extensive drought in 2019, the worst record in the recent four decadesThis extreme drought can be well explained by combined effects of the westernmost‐located CP El Niño and third strongest positive Indian Ocean Dipole (IOD) eventsSevere Australian droughts could occur more frequently in a warming world with projected increases in both CP El Niño and extreme IOD events [ABSTRACT FROM AUTHOR]

Shorelines respond to a number of "drivers" operating on a variety of time‐scales. For some time‐scales (e.g., seasonal), the driver‐shoreline relationship is often evident; however, at longer time‐scales (e.g., multiannual), the shoreline changes may be superimposed on changes at shorter time‐scales and thus are difficult to identify. Here, we predict shoreline evolution from storm events to decadal time‐scales, using a novel approach based on the Complete Ensemble Empirical Mode Decomposition. This approach identifies and links the primary time‐scales in the model drivers (large‐scale sea level pressure [SLP] and/or waves) with the same time‐scales in the shoreline position. The multiscale approach reproduced shoreline changes at two beaches more skillfully than a common shoreline model when SLP and wave information were used in combination. In addition, the analysis can be applied to climate indices, providing the opportunity to link longer time‐scales with climate patterns (e.g., El Niño Southern Oscillation). Plain Language Summary: Beaches are changing constantly, advancing or retreating depending for instance, on the climate and ocean conditions. Beach retreat and advance may occur in cycles (seasonally, annually, or over several decades) or because of particular events such as storms. All these changes are superimposed and difficult to disentangle. Therefore, the same beach can look completely different in summer or winter, and the changes are not the same year after year. Therefore, predicting the beach state over the following months, years, or decades is a daunting task. Here, we introduce a new approach to the prediction of shoreline changes and test it at two beaches (one in New Zealand and the other in Australia). The new approach relates changes in shoreline position with "drivers" (waves and atmospheric patterns) decomposed into time‐scales (e.g., seasonal, annual, and bi‐annual) and uses these connections to predict shoreline changes. Key Points: A novel modeling approach to shoreline prediction is presented and compared with an established model at two study sitesA decomposition of different time‐scales (from storm to climate anomalies) in shoreline and drivers is used to predict shoreline changeThe addition of sea level pressure information to wave bulk parameters as model inputs improves shoreline predictions [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the role of Australian climate scientists in advancing the state of knowledge about the causes and mechanisms of climatic change and variability in the Southern Hemisphere during the 1970 and 1980s. Design/methodology/approach: The paper uses the methods and insights of environmental history and the history of science to analyse archival and published data pertaining to research on atmospheric pollution, the Southern Oscillation and the regional impacts of climate change. Findings: Australia's geopolitical position, political interests and environmental sensitivities encouraged Australian scientists and policymakers to take a leading role in the Southern Hemisphere in the study of global environmental change. Originality/value: This article builds on critiques of the ways in which planetary and global knowledge and governance disguise the local and situated scientific and material processes that construct, sustain and configure them. [ABSTRACT FROM AUTHOR]

The seasonal cycle of the evaporative stress index (ESI) over Australia, and its relationship to observed rainfall and temperature, is examined. The ESI is defined as the standardized anomaly of the ratio of actual evapotranspiration to potential evapotranspiration, and as such, is a measure of vegetation moisture stress associated with agricultural or ecological drought. The ESI is computed using the daily output of version 6 of the Bureau of Meteorology's landscape water balance model [Australian Water Resource Assessment Landscape (AWRA-L)] on a 5-km horizontal grid over a 45-yr period (1975-2019). Here we show that the ESI exhibits marked spatial and seasonal variability and can be used to accurately monitor drought across Australia, where ESI values less than negative one indicate drought. While the ESI is highly correlated with rainfall as expected, its relationship with temperature only becomes significant during the warmer seasons, suggesting a threshold above which temperature may affect vegetation stress. Our analysis also shows that the ESI tends to be strongly negative (i.e., indicating drought) during El Niño and positive phases of the Indian Ocean dipole (IOD), when conditions tend to be anomalously hot and dry. A negative phase of the southern annular mode also tends to drive negative ESI values during austral spring with a one-month delay. [ABSTRACT FROM AUTHOR]

The 2019 positive Indian Ocean Dipole (IOD) was the strongest event since the 1960s which developed independently without coinciding El Niño. The dynamics is not fully understood. Here we show that in March–May, westward propagating oceanic Rossby waves, a remnant consequence of the weak 2018 Pacific warm condition, led to anomalous sea surface temperature warming in the southwest tropical Indian Ocean (TIO), inducing deep convection and anomalous easterly winds along the equator, which triggered the initial cooling in the east. In June–August, the easterly wind anomalies continued to evolve through ocean‐atmosphere coupling involving Bjerknes feedback and equatorial nonlinear ocean advection, until its maturity in September–November. This study clarifies the contribution of oceanic Rossby waves in the south TIO in different dynamic settings and reveals a new triggering mechanism for extreme IOD events that will help to understand IOD diversity. Plain Language Summary: The Indian Ocean Dipole (IOD) is an ocean‐atmosphere coupled climatic phenomenon which can cause severe social and economic losses in the surrounding regions such as drought in the Maritime Continent/Australia and flooding in East Africa. The IOD features a see‐saw structure accompanied by an anomalous sea surface temperature gradient, winds, and oceanic adjustments. The El Niño–Southern Oscillation in the Pacific is an important trigger to a strong IOD event. However, an extreme positive IOD event occurred in 2019 without a concurrent or ensuing El Niño. We show that the thermocline warming associated with anomalous ocean downwelling in the southwest tropical Indian Ocean triggered atmospheric convection, inducing anomalous easterly winds along the equator and hence, positive feedbacks associated with an IOD event. This study may help to understand the evolution of extreme IOD and improve IOD predictability. Key Points: The oceanic downwelling Rossby waves in the south tropical Indian Ocean is key to the 2019 extreme positive Indian Ocean Dipole (IOD)The Rossby waves induced thermocline warming, triggering wind‐evaporation‐SST feedback thus anomalous easterly winds along the equatorThe easterly wind anomalies further triggered the Bjerknes feedback and other positive feedbacks and established an extreme IOD [ABSTRACT FROM AUTHOR]

The El Niño-Southern Oscillation (ENSO) drives substantial variability in precipitation and drought risk over Australia. Understanding the combined effect of anthropogenic forcing and ENSO on Australian precipitation extremes over the coming century can assist adaptation efforts. Here we use 24 CMIP5 climate models to examine externally forced changes in the frequency of "droughts", when precipitation falls below the pre-industrial Decile 1 threshold. We focus on June to November (i.e., southern hemisphere Winter–Spring season) because precipitation during this period is important for agricultural production and recharging reservoirs in many parts of the country. The analysis in this paper is based on two 90-year simulations (1900–1989 and 2010–2099) for Historical and RCP8.5 scenarios. We show that the frequency of droughts, including droughts occurring in consecutive Winter–Spring seasons, is projected to increase in the twenty-first century under the RCP8.5 scenario in all eight Natural Resource Management (NRM) "clusters". Approximately 60% of years are projected to be drought years in Perth, 35% in Adelaide, 30% in Melbourne, and approximately 20–25% of years in Sydney, Canberra and Brisbane. The relative frequency distributions of seasonally averaged Winter–Spring precipitation shift to lower values in all NRM clusters. However, apart from the Southern and Southwestern Flatlands, the shifts are accompanied by changes in the shape of the distributions whereby the high end of the distributions do not shift as much as other parts of the distribution and the wettest seasons become marginally wetter. This means that in most locations generally drier conditions are projected to be infrequently punctuated by seasons that are just as wet or wetter than the wettest years experienced during the twentieth century. While the models generally do a poor job in simulating ENSO precipitation teleconnections over Australia, an increase in ENSO-driven variability is suggested for the Wet Tropics, the Monsoonal North, the Central Slopes and the Southern and Southwestern Flatlands. [ABSTRACT FROM AUTHOR]

Grown in water-limited environments, sorghum (Sorghum bicolor (L.) Moench) is often exposed to water deficits of varying extent and timing. One of the impacts of water stress on sorghum production is lodging; however, there has been no published study quantifying the temporal and spatial frequency and severity of lodging in grain sorghum in Australia. In this study, we investigated the frequency and severity of lodging, using a dataset of 83 advanced yield-testing trials of the sorghum pre-breeding program grown in the seven major sorghum-production environments in Australia over 14 summer growing seasons. Lodging occurred in most production regions but with varying frequency and severity. Lodging was significantly greater in regions that were more prone to water stress (e.g. Central Highlands in Queensland) and significantly lower in regions that were less likely to suffer from water stress (e.g. Liverpool Plains in northern New South Wale) compared with the overall average across regions. The severity of lodging also varied across regions, with the most severe lodging (>20%) occurring in Central Highlands and Western Downs in Queensland. In addition, seasonal patterns of lodging frequency and severity were also observed. Over the 14 growing seasons, the frequency of lodging varied from 0% to 100%, with the most severe lodging (>20%) observed in 2005, 2016 and 2017. The Southern Oscillation Index explained 29% of the seasonal variation in lodging frequency. The findings of this study clearly support a link between lodging incidence and water stress across regions and seasons. Our data also showed that although there was a substantial turnover of commercial hybrids during the period of this study, the level of resistance to lodging appeared not to have improved. It is possible that this is due to plant breeders trading off improvements in lodging resistance to increase grain yield. Lodging often occurs in sorghum in Australia owing to water limitation; however, no published study has quantified lodging occurrence. Our study revealed that lodging frequency and severity varied geographically and seasonally, that lodging frequency was associated with the SOI, and that lodging resistance has not improved in commercial hybrids over 14 years. This is the first study to document lodging occurrence in Australia and provides a more thorough understanding of the causes of this potentially devastating and intractable trait. [ABSTRACT FROM AUTHOR]