Spatio-temporal characteristics of extreme rainfall over western Java across interdecadal-to-multidecadal periods allow assessment of the impact of various large-scale climate events on the region. In this paper, we describe these characteristics using extreme rainfall indices, based on a quality-assured daily rainfall dataset from 185 rain gauges with varying temporal coverage, ranging from 1950 to 2020. The characterisation was done by calculating Sen's slopes of the extreme indices across three interdecadal (10-15 and 16-25 years) and multidecadal (>25 years) periods. Our study shows that the interdecadal and multidecadal periods were dominated by Sen's slopes with no statistical significance, and likewise for their regression with elevation. Thus, there is no compelling evidence of any spatial dependency (e.g. topographical effect) of Sen's slopes in any of the extreme indices and periods in the region despite its complex terrains and coastlines. Much steeper Sen's slopes in interdecadal compared with multidecadal periods signal regional responses to large-scale climate internal variabilities, such as the long-term modulation of the El Ni & ntilde;o-Southern Oscillation (ENSO). The significance of extreme rainfall in interdecadal periods is well exemplified by the decade 2001-10, which exhibits a larger number of locations with positive and significant Sen's slopes than 1991-2000 and later decades. The positive and significant Sen's slopes in 2001-10 may be associated with a shift towards negative phases of the Pacific Ocean climate drivers, such as La Ni & ntilde;a events. Our study suggests that interdecadal changes in extreme rainfall over western Java indicate a key regional climate impact concern that warrants mitigation efforts.
In Australia, drought has dramatic consequences for social, economic and environmental systems, making it critical to understand how this hazard may change in the future. The Australian Climate Service (ACS) is a national interagency collaboration to service Australia's climate needs. In this paper, we unpack insights from the ACS's drought and changes in aridity team derived using dynamically downscaled and bias-adjusted CMIP6 (sixth Coupled Model Intercomparison Project) projections for two emissions scenarios. By applying a global warming level framework, we report on both mean state shifts to meteorological drought, as well as outlier ensemble members useful for high-impact, low-probability event planning. Key findings indicate high-confidence increases to time spent in drought across southern and south-western parts of Australia, with some areas projected to experience meteorological droughts up to 30% longer and 75% more frequently compared to the current climate. In regions of lower confidence change, such as the tropics and parts of the Murray-Darling Basin, a range of diverging drought futures are unpacked. The findings of this analysis can enable decision makers to make informed choices in regions of higher confidence change, and to develop adaptive strategies where there may be more uncertainty. As climate change intensifies, such planning will be critical to sustaining the long-term resilience and vitality of drought-prone ecosystems and communities.
This study analysed the influence of intraseasonal variability on the persistence of generalised frost (GF) events in the Pampa H & uacute;meda, Argentina. The events were classified into three categories: no persistence (0 DP), 1-day persistence (1 DP) and 2 or more days of persistence (2 DP+). The 0-DP events were associated with short-lived synoptic systems, such as transient anticyclones and high-pressure systems, which promote temporary stability but lack dynamic support for consecutive frost days. In 1-DP events, a Rossby wave train propagating from the central Pacific Ocean to South America favoured cold air advection, with additional modulation from tropical forcing patterns linked to convective episodes in the region. The 2-DP+ events were associated with a persistent tropical forcing signal that led to the excitation of well-structured Rossby wave trains, sustaining cold air advection and stable conditions over multiple nights. Overall, the results show that short-lived frosts are driven by transient synoptic systems, whereas persistent events are more strongly linked to Rossby wave activity modulated by tropical-extratropical interactions. These findings enhance the understanding of the frost formation mechanisms in south-eastern South America and provide valuable input for improving forecasting and agricultural risk management strategies.
Fire-generated tornadic vortices (FGTVs) were observed at two high intensity fires in New South Wales during the 2019-20 'Black Summer' Australian bushfires. At the Green Valley Fire, a fully laden fire truck was lifted and overturned by a confirmed FGTV, with estimated wind speeds of similar to 300 km h(-1) (Enhanced Fujita, EF, scale rating of 3 to 4). At Wandella, impact to vehicles at the Badja Forest Fire indicates winds may have exceeded 350 km h(-1) (EF5 tornado), making it one of the strongest pyrogenic winds documented globally. We use a combination of observations and insights from simulations using the coupled fire-atmosphere model ACCESS-Fire to investigate the FGTV environments. Radar and satellite observations showed both FGTVs occurred coincident with rapid acceleration of the fire's updraft and rapid growth of pyroconvective clouds; towering pyrocumulus cloud (pyroCu) at the Green Valley FGTV and pyrocumulonimbus cloud (pyroCb) tops higher than 12 km at the Wandella FGTV. Coupled fire-atmosphere simulations resolved transient, small scale features consistent with observations, including split flow around the fire, reverse lee side inflow, fire updrafts extending to the mid-troposphere, and split fire fronts with convective towers at the head of the flanks. A likely source of vorticity for each was a zone of near ground vertical wind shear between the fire's reverse inflow in a valley, and north-westerly winds above. The case studies contribute to growing knowledge of these destructive FGTVs, highlight the benefits of fire-atmosphere modelling, and demonstrate the operational utility of radar and satellite observations to inform warnings to communities and fire-fighting operations.
The National Partnership for Climate Projections (NPCP) was established as a collaborative effort of the Australian climate projections community to develop a consistent approach to deliver future climate information. As bias correction of climate model outputs is important for many applications, a NPCP bias correction intercomparison project was initiated. The first phase of the intercomparison aimed to support the production of national-scale climate projections by the Australian Climate Service. It focused on five methods – Equidistant Cumulative Density Function matching (ECDFm), Quantile Matching for Extremes (QME), Quantile Delta Change (QDC), N-Dimensional Multi-Variate Bias Correction (MBCn) and Multivariate Recursive Nesting Bias Correction (MRNBC) – and applied them to daily timescale Coordinated Regional Climate Downscaling Experiment (CORDEX) data produced by NPCP partner organisations. Each method was assessed over a calibration period and also via cross-validation on several metrics relating to the temperature and precipitation climatology, variability, distribution, extremes and trends. The best-performing bias correction methods were QME and MRNBC. The ECDFm method also performed well on most metrics, but under certain circumstances it could dramatically increase the model bias. The QDC method is a delta change method (i.e. it perturbs the observations rather than correcting model data) and compared very favourably to the four bias correction methods. The QME, MRNBC and QDC methods were subsequently used by the Australian Climate Service to produce climate projections datasets for Australia.
A numerical weather prediction (NWP) system that represents continental Australia at a convection-permitting resolution presents both advantages and challenges. It must represent diverse weather regimes over areas of variable observation coverage, which complicates the land and atmospheric modelling and data assimilation. A single-domain prototype system, ACCESS-A (Australia Community Climate and Earth System Simulator – Australia), has been developed and tested. Compared with the current operational NWP system comprising seven small domains (ACCESS-C), ACCESS-A incorporates improvements to satellite, conventional and radar data assimilation and uses an upgraded model science configuration. ACCESS-A was extensively evaluated over two 3-month periods. Qualitative and quantitative precipitation verification indicates that ACCESS-A reproduces the seasons’ weather patterns and observed behaviour of convective precipitation. Objective verification of defined subdomains shows that forecast skill of near-surface weather is variable across the continent. It is found more skilful in better-observed regions that coincide with areas dominated by more predictable, synoptically driven weather systems. Regions with lower skill, particularly corresponding to areas not covered by ACCESS-C, suggest a focus for future research. A comparison with ACCESS-C confirmed the anticipated improved skill related to the forecast model’s upgraded land and atmospheric physics, and provides confidence in the combined impact of all upgrades implemented in ACCESS-A. ACCESS-A is demonstrated to be ready to prepare for operational NWP and ongoing research at the Australian Bureau of Meteorology.
Tasmania, Australia's largest producer of hydroelectric power, receives most of its rainfall from extratropical cyclones (ETCs) and cold fronts. Western Tasmania experiences up to 3 m of annual rainfall, primarily driven by midlatitude weather systems and their interaction with local topography, which supports hydroelectric power generation in the state. However, the weather systems influencing rainfall variability in the east - where most Tasmanians live and where rainfall is vital for agriculture - remain less studied. Using combined datasets of ETCs, cold fronts and thunderstorms spanning 1979-2015 over 5-50 degrees S and 110-160 degrees E, we examined the key weather systems driving Tasmania's spatial and temporal rainfall variability. These weather systems collectively contribute over 80% of the state's annual rainfall. A large proportion of total rainfall in eastern Tasmania is due to ETCs, whereas cold fronts play a greater role in the west. ETCs south of 40 degrees S, particularly those passing through the Tasmanian region, are associated with heavy rainfall across the state. A statistically significant decline in rainfall (1979-2023) has been observed over western Tasmania, particularly during the warm season (November-April), raising concerns for hydroelectric resources. Our findings highlight the central role of midlatitude weather systems in sustaining Tasmania's hydroclimate and underscore the need to better understand their future changes in a warming world.
In coastal areas where Southern Ocean swells are observed, the Southern Annular Mode (SAM) climate index has been shown to be a useful predictor for wave conditions. However, the relationship between SAM and beach morphology change in these areas is not well known. In this study, empirical orthogonal function statistical analysis was applied to satellite-derived shoreline data from 1987 to 2021 at Grassy Beach, King Island, Australia. The dominant modes of shoreline variability were calculated and the interconnection between SAM and shoreline position investigated. Cross-shore beach movement and seasonal beach rotation were the dominant sources of shoreline variability, accounting for similar to 64 and similar to 18% of total shoreline variability respectively. Shoreline retreat (advance) was observed at the eastern (south-western) end of the embayment during winter and, conversely, shoreline retreat (advance) at the south-western (eastern) end during summer. A clear connection between the SAM and shoreline variability was found, the SAM modulating beach rotation depending on the SAM phase. When SAM was positive, beach rotation increased with a greater difference in beach orientation between summer and winter owing to an increased shoreline retreat at the eastern end of the embayment by 4.1 m on average. This increased retreat was attributed to more powerful south-westerly waves in winter for positive SAM. This research demonstrated a strong relationship between SAM and shoreline change at a sandy embayment in southern Australia and may have implications for the current and future morphodynamics at other beaches influenced by the Southern Ocean wave climate.
Dorothea Mackellar famously wrote that Australia is 'a land of droughts and flooding rains'. But has this always been true, and will these extremes intensify in a warmer world? Australia's vast continent spans diverse hydroclimate regions - from the wet tropics in the north-east to the arid central rangelands - a land of climatic contrasts. Our study examines changes in these regions from past to future by: 1, assessing hydroclimate anomalies from 1963-2022; 2, exploring compound events and their link to disasters (1993-2022); and 3, projecting compound events under wet, dry and mid-range storylines (1976-2005 v. 2036-2065). Currently, southern and some central regions show drying trends in precipitation, runoff and soil moisture, alongside rising temperatures. Natural disasters are increasingly tied to compound events, where hazards cycle through communities already under strain. Worryingly, these events appear to be on the rise. Future projections show more frequent 'hot and dry' and 'wet and windy' extremes across all regions under at least one storyline. This suggests larger-scale droughts, longer fire seasons and more extreme fire danger days, across most of Australia as well as heavier rainfall, storms and stronger winds in the northern and central regions under the wet storyline, signalling an increased risk of flooding through extreme runoff. Our findings indicate that Australia's hydroclimate extremes are changing and compounding, with significant implications for communities and disaster preparedness.
Amid the growing challenges of climate change impact and the fairly limited availability of observations of some Earth system parameters, this article highlights the potential of ground-based Global Navigation Satellite Systems (GNSS) atmospheric monitoring as a supplementary satellite observing technique to improve the monitoring and forecasting of weather and climate extremes. It spotlights current barriers and future opportunities, aiming to heighten public and institutional awareness of the research and application status and the prospective role of GNSS atmospheric monitoring for weather and climate resilience. The innovative uptake of diverse ground-based GNSS atmospheric parameters could support improved systems and policies for risk management and climate adaptation, thus empowering communities to better withstand hazardous weather and climate extremes.
Verification of atmospheric reanalysis products is crucial for their application in extreme weather and climate-related research. This study evaluates tropical cyclone (TC) characteristics and related variables from 1990 to 2018 over Australia (95-160 degrees E and 0-30 degrees S) in three reanalysis products - the recently developed Australian Bureau of Meteorology's Atmospheric high-resolution Regional Reanalysis for Australia Version 2 (BARRA-R2), its predecessor BARRA-R (both at 12-km spatial resolution) and the widely used European Centre for Medium-Range Weather Forecasts (ECMWF)'s Global Reanalysis Version 5 (ERA5) at 31-km spatial resolution. TCs detected in these reanalyses, using the Okubo-Weiss-Zeta Parameter detection and tracking scheme, are compared with observations from the Bureau's TC database. All three products simulated more than 50% of the observed TC frequency, with ERA5 achieving a higher hit rate of 77% compared with BARRA-R2 (68%) and BARRA-R (53%). Most missed cases involved non-severe TCs. ERA5 showed a clear decline in annual TC frequency consistent with observations, whereas BARRA-R displayed a weak upward trend and BARRA-R2 a statistically insignificant decline. Large differences emerged in surface wind speed and gusts: BARRA-R represented TC surface winds better than ERA5, and BARRA-R2 produced slightly improved gusts compared with ERA-5. Case studies show that temporal evolution is generally well represented in all products, though ERA5 tends to maintain peak intensity for longer, whereas BARRA products sometimes show shifted timing of peak intensity. General discrepancies are attributed to resolution limitations, inherent differences between best-track and gridded data, underestimation of TC peak intensity and wider model forecast constraints.
This study examines over 13 years (March 2010 to May 2023) of data from 12 Southern Ocean Flux Station (SOFS) mooring deployments to explore the characteristics and temporal climatology of air–sea heat flux in the Southern Ocean. SOFS, the only currently operational moored buoy in the Southern Ocean (anchored at ~47°S, 142°E), provides high-resolution (1-min) climate-quality meteorological and marine data, facilitating detailed air–sea heat flux analysis. Before analysis, the 1-min SOFS flux data were rigorously evaluated, and their high quality confirmed by comparing net heat flux against nearby overlapping moorings and research vessels. Over the study period, the average annual net heat flux at the SOFS site is −14.6 ± 5.4 W m−2 (a net ocean heat gain). This is the first estimate of the net heat exchange at a Southern Ocean site that is based on a multi-year record of high-quality measurements, offering direct evidence of the ocean region’s absorption of heat. Seasonal heat flux variabilities and extreme heat flux events are investigated. Additionally, a case study highlights a strong horizontal sea surface temperature gradient (3.4°C over 35.5 km) that resulted in a significant net heat flux difference of up to 242.5 W m−2, which showed that the environmental conditions in this region may shift dramatically over short temporal or spatial scales.
The method of archetypal analysis is used to generate a set of monthly timescale rainfall archetypes for the Australian region. The patterns associated with the archetypes reflect continental and regional-scale wet and dry. The dominant pattern in terms of occurrence and persistence is one in which most of the continent is dry. This pattern is typically expressed over winter and spring. The next most frequent pattern is one where most of the continent is wet, mostly expressed during summer. It is rare to find periods where the whole continent is wet outside summer, though this does occur and is associated with very wet years for the continent. The archetype patterns have preferred seasonal expressions, and preferred transitions from one pattern to another. The continent-wide dry pattern is mostly followed by patterns in which both south-west and south-east Australia are wet during the autumn and winter. However, if the dry continental archetype persists through to spring, then it is usually followed by a pattern that is wet in the south-east but not the south-west. The analysis reveals pivotal months, such as April and November. These months mark the end of periods when only a few archetypes are expressed, allow expression of almost all the archetypes, and are then succeeded by periods when a smaller number of archetypes are expressed again. The archetype patterns successfully capture the large-scale spatial patterns of monthly rainfall in Australia, and provide a diagnostic tool to evaluate the onset, duration and transitions between wet and dry periods.
By using finer resolution modelling and locally representative model physics, regional climate models (RCMs) have the potential to improve the information provided by global climate models (GCMs). However, RCMs have their own biases and limitations due to remaining unresolved processes. It is therefore necessary to carefully assess RCM outputs through added value analyses. An ensemble of CMIP6-based 12–17-km regional climate projections has been produced for the Australian Climate Service (ACS) based on the Bureau of Meteorology’s regional climate modelling system (BARPA) and CSIRO’s Conformal Cubic Atmospheric Model (CCAM). The historical and potential future added value of this ensemble is assessed, focusing on extremes (cold, hot, wet and dry). Despite variations in added value across different GCM–RCM experiments, quantities, seasons and regions, BARPA and CCAM generally improve on their driving models for the historical period. Added value over ERA5 is generally small, and often negative for wet and dry extremes, especially for CCAM. The most consistent improvements in all GCM–RCM pairs are found for quantities containing daily minimum temperature, whereas hot days above 40°C show the least improvements. CNRM-ESM2-1-CCAM appears to have significant issues in most analysed quantities, especially related to maximum temperature and might not be recommended for downscaling or use by the community. Additionally, RCMs often predict different climate change signals than their driving models, for example the Murray Basin, which combined with the historical added value indicate plausible improvements in future climate projections.
Low pressure systems are associated with a number of climate hazards in Australia, including heavy rainfall, strong winds and coastal erosion. Here, we use a new ensemble of 40 CMIP6 (Sixth Coupled Model Intercomparison Project)-based regional model projections to assess future changes in low pressure systems across Australia, with a focus on vertically developed (deep) cyclones that extend between the surface and 500 hPa. Results show robust future declines in extratropical lows in southern Australia throughout the year, with large uncertainty for lows in northern Australia. Projections for strong, rapidly intensifying and slow-moving low pressure systems are also assessed, and are all projected to decline in frequency. The strongest declines in lows are identified for models that also have larger increases in the intensity of 500-hPa zonal winds to the south of Australia (40-50 degrees S), with observed trends in both indices at the high end of the model range. This suggests the potential for constraining future projections of Australian low pressure systems based on monthly mean zonal winds.
Gridded TerraClimate and ERA5-Land reanalysis datasets provide high-resolution climate data of either direct vapour pressure deficit (VPD) or its input variables at 0.04 and 0.1° spatial resolution respectively, and over extended time periods. However, there are gaps in their applicability over data-sparse regions such as East Africa. This study aims to (i) validate VPD from both gridded TerraClimate VPD and ERA5-Land reanalysis using station-derived VPD for the period 2014–2023 and (ii) compare and contrast the two datasets at a monthly timescale over the period 1984–2023 in a spatiotemporal context. We employed the root mean square error (RMSE), scatter index (SI) and correlation coefficients for accuracy evaluation against 20 meteorological stations across East Africa. For spatiotemporal comparison between the two datasets, we used the Mann–Kendall trend test, Student’s t-test and correlation analysis. Results showed that ERA5-Land reanalysis generally performed better across most parts of East Africa, as evidenced by strong correlations and low SI scores ranging within 0–30% for 95% of the stations, compared to a good-fair performance of gridded TerraClimate with SI scores of 0–50% for 95% of the stations. Finally, comparative analysis revealed strong agreement between the two datasets on trend magnitude, direction and significance as well as June-to-August seasonal means. Additionally, very strong positive correlations (0.75–1.0) were observed for most parts of East Africa, except over areas dominated by very high humidity such as mountainous areas and those surrounding lakes. Finer temporal- and spatial-scale studies are recommended, with emphasis on exploring the added value of combining the two datasets.
This paper analyses historical climate conditions and future climate projections in central-eastern Argentina, focusing on temperature and precipitation patterns. The study assesses the ability of Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models to represent historical climate variability and generates projections of precipitation and temperature under three combined socioeconomic and greenhouse gas emissions scenarios for the 21st Century. Historical analysis for the 1901–2014 period reveals high correlations between model-simulated and observed temperature. Precipitation simulations are less accurate; however, bias correction introduces notable improvements. Although the models properly recognise mean annual temperature and precipitation cycles, biases appear in the reproduction of the spatial patterns of these variables. Future projections indicate a significant increase in mean annual temperature across all scenarios, with the highest temperature rise in a fossil-fuel-intensive scenario, highlighting the importance of emissions mitigation. Precipitation is projected to increase in all scenarios, particularly in the western part of the study region, with potential implications for hydrology and agriculture. This study emphasises the need for ongoing research and monitoring to enhance our understanding of regional climate vulnerability and to inform local adaptation strategies in the face of a changing climate.
Bureau of Meteorology high-resolution Atmospheric Regional Reanalysis for Australia version 2 (BARRA2) is a new regional reanalysis, nested in ERA5 (ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis ver. 5), extending from 1979 to near present. It is developed for the Australasia domain, including Australia, New Zealand and parts of the Maritime Continent, at a horizontal grid resolution of 12 km, with a finer 4.4-km grid over Australia. Building on its predecessor (BARRA1), BARRA2 introduces significant improvements by incorporating a broader range of observations and previously unavailable pre-processed data sets. BARRA2 employs a four-dimension-variational assimilation method for the atmosphere and an extended Kalman filter for the land surface, integrating conventional observations and satellite-based radiances, atmospheric motion vector winds, satellite and ground-based Global Navigation Satellite System measurements, and satellite soil moisture data. The modelling system is based on the UK Met Office Unified Model (UM) and the Joint UK Land Simulator (JULES), with updated physics configurations that address limitations of BARRA1. This also includes a convection-permitting configuration for the 4.4-km model. This paper describes the BARRA2 system and assesses the quality of its deterministic outputs for key near-surface meteorological parameters, including temperature, wind and precipitation. The added value of BARRA2 over global reanalyses is evident in coastal and high-terrain regions and within the convection-permitting system. BARRA2 shows quality changes from approximately the year 2000, although these do not appear to negatively affect long-term temperature or rainfall trends at studied sites and regions. Remaining challenges, including modelling biases and data assimilation limitations, are discussed to inform future development.
Forestation is a feasible and cost-effective strategy to remove CO2 from the atmosphere and store it in natural reservoirs. However, it is highly uncertain how much carbon new forests can remove, how those changes will affect the climate at the local to global scales, and how a changing climate might affect the effectiveness of forestation. Here, we use the ACCESS-ESM1-5 earth system model to perform idealised global experiments of forestation to investigate the effects of additional forest cover on the Australian climate at a range of different global warming levels. Experiments include sensitivity tests that replace various fractions of existing croplands with up to 19.3 x 10(6) km(2) of forests globally (0.58 x 10(6) km(2) in Australia or similar to 8.5 times the area of Tasmania). We find that forestation on these lands can remove 40 to 80 teragrams (Tg) of carbon per year over 100 years for Australia alone compared to a scenario without forestation. For comparison, anthropogenic greenhouse gas emissions in Australia were 121.8 Tg C-CO(2)e in 2024. Depending on whether these forests are harvested for long-lived wood products, forestation could achieve a cumulative carbon sequestration of 5-14 petagrams (Pg) of carbon. A coordinated global forestation effort could cool Australia's mean climate by up to 0.1-0.4 degrees C with respect to the investigated global warming levels. However, ACCESS-ESM1-5 also projects some regional warming due to the associated decreased albedo of forested areas. With careful consideration of land cover changes to account for potential regional warming, forestation has considerable biophysical potential to remove CO2 and contribute to meeting net-zero targets in Australia and globally.
Understanding, quantifying and visualising projected ranges of future regional climate change is important for informing robust climate change impact assessments. Here, we examine projections of Australian sub-continental regionally averaged surface air temperature and precipitation in the Sixth Coupled Model Intercomparison Project (CMIP6) global and Coordinated Regional climate Downscaling Experiment (CORDEX)-Australasia regional model ensembles and illustrate the relative sources of uncertainty from emissions scenarios, models and internal climate variability. As expected, the uncertainty in temperature change for all regions by the end of the century is predominantly determined by the emissions scenario. Here, we examine a low and high emissions scenario, bookending a range of plausible cases. In contrast, the uncertainty in precipitation changes towards the end of the 21st Century is largely related to model-to-model differences, in particular owing to the differences between global models, with regional models contributing a smaller, but still significant, source of uncertainty. Regional models can significantly alter precipitation projections; however, we find few cases of consistency across the regional models. Decadal variability is an important contributing factor for precipitation uncertainty for the entire 21st Century. Large changes in interannual precipitation variability are projected by some climate models by the end of the 21st Century, and these changes tend to be well correlated to mean precipitation changes. Robust responses to climate change must account for all of these dimensions in a structured way.
