Australia's Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change.

We examine the characteristics and causes of southeast Australia's Tinderbox Drought (2017 to 2019) that preceded the Black Summer fire disaster. The Tinderbox Drought was characterized by cool season rainfall deficits of around -50% in three consecutive years, which was exceptionally unlikely in the context of natural variability alone. The precipitation deficits were initiated and sustained by an anomalous atmospheric circulation that diverted oceanic moisture away from the region, despite traditional indicators of drought risk in southeast Australia generally being in neutral states. Moisture deficits were intensified by unusually high temperatures, high vapor pressure deficits, and sustained reductions in terrestrial water availability. Anthropogenic forcing intensified the rainfall deficits of the Tinderbox Drought by around 18% with an interquartile range of 34.9 to -13.3% highlighting the considerable uncertainty in attributing droughts of this kind to human activity. Skillful predictability of this drought was possible by incorporating multiple remote and local predictors through machine learning, providing prospects for improving forecasting of droughts.

Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events.

Although climate models have been used to assess compound events, the combination of multiple hazards or drivers poses uncertainties because of the systemic biases present. Here, we investigate multivariate bias correction for correcting systemic bias in the boundaries that form the inputs of regional climate models (RCMs). This improves the representation of physical relationships among variables, essential for accurate characterization of compound events. We address four types of compound events that result from eight different hazards. The results show that while the RCM simulations presented here exhibit similar performance for some event types, the multivariate bias correction broadly improves the RCM representation of compound events compared to no correction or univariate correction, particularly for coincident high temperature and high precipitation. The RCM with uncorrected boundaries tends to produce a negative bias in the return period of these events, suggesting a tendency to over-simulate compound events with respect to observed events.

Assessing Australia's future solar power ramps with climate projections.

Increasing levels of photovoltaic (PV) penetration to the electricity grid brings challenges to both design and operation of the grid due to its vulnerability to climate change. A crucial aspect of PV operation is power ramps leading to variability and instability in the grid. With notable large-scale PV deployment planned, including the world's largest planned solar energy infrastructure in Powell Creek Australia, characterising future ramps is crucial for ensuring stable power generation to support large-scale economic development. Using CORDEX-Australasia projections under RCP8.5 and RCP4.5 emission scenarios, future solar ramps across Australia have been characterised up to 2100. Results predict a reduction in ramp magnitude across Australia, with changes in frequency and period length varying with the location. This work highlights the importance of considering future changes in climate when designing large-scale solar farms to ensure the incorporation of frequency control devices and storage plans for a reliable power supply.

Intensification of subhourly heavy rainfall.

Short-duration rainfall extremes can cause flash flooding with associated impacts. Previous studies of climate impacts on extreme precipitation have focused mainly on daily rain totals. Subdaily extremes are often generated in small areas that can be missed by gauge networks or satellites and are not resolved by climate models. Here, we show a robust positive trend of at least 20% per decade in subhourly extreme rainfall near Sydney, Australia, over 20 years, despite no evidence of trends at hourly or daily scales. This trend is seen consistently in storms tracked using multiple independent ground radars, is consistent with rain-gauge data, and does not appear to be associated with known natural variations. This finding suggests that subhourly rainfall extremes may be increasing substantially faster than those on more widely reported time scales.

Towards advancing scientific knowledge of climate change impacts on short-duration rainfall extremes.

A large number of recent studies have aimed at understanding short-duration rainfall extremes, due to their impacts on flash floods, landslides and debris flows and potential for these to worsen with global warming. This has been led in a concerted international effort by the INTENSE Crosscutting Project of the GEWEX (Global Energy and Water Exchanges) Hydroclimatology Panel. Here, we summarize the main findings so far and suggest future directions for research, including: the benefits of convection-permitting climate modelling; towards understanding mechanisms of change; the usefulness of temperature-scaling relations; towards detecting and attributing extreme rainfall change; and the need for international coordination and collaboration. Evidence suggests that the intensity of long-duration (1 day+) heavy precipitation increases with climate warming close to the Clausius-Clapeyron (CC) rate (6-7% K-1), although large-scale circulation changes affect this response regionally. However, rare events can scale at higher rates, and localized heavy short-duration (hourly and sub-hourly) intensities can respond more strongly (e.g. 2 × CC instead of CC). Day-to-day scaling of short-duration intensities supports a higher scaling, with mechanisms proposed for this related to local-scale dynamics of convective storms, but its relevance to climate change is not clear. Uncertainty in changes to precipitation extremes remains and is influenced by many factors, including large-scale circulation, convective storm dynamics andstratification. Despite this, recent research has increased confidence in both the detectability and understanding of changes in various aspects of intense short-duration rainfall. To make further progress, the international coordination of datasets, model experiments and evaluations will be required, with consistent and standardized comparison methods and metrics, and recommendations are made for these frameworks. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Global hotspots for the occurrence of compound events.

Compound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980-2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs.

Future changes in extreme weather and pyroconvection risk factors for Australian wildfires.

Extreme wildfires have recently caused disastrous impacts in Australia and other regions of the world, including events with strong convective processes in their plumes (i.e., strong pyroconvection). Dangerous wildfire events such as these could potentially be influenced by anthropogenic climate change, however, there are large knowledge gaps on how these events might change in the future. The McArthur Forest Fire Danger Index (FFDI) is used to represent near-surface weather conditions and the Continuous Haines index (CH) is used here to represent lower to mid-tropospheric vertical atmospheric stability and humidity measures relevant to dangerous wildfires and pyroconvective processes. Projected changes in extreme measures of CH and FFDI are examined using a multi-method approach, including an ensemble of global climate models together with two ensembles of regional climate models. The projections show a clear trend towards more dangerous near-surface fire weather conditions for Australia based on the FFDI, as well as increased pyroconvection risk factors for some regions of southern Australia based on the CH. These results have implications for fields such as disaster risk reduction, climate adaptation, ecology, policy and planning, noting that improved knowledge on how climate change can influence extreme wildfires can help reduce future impacts of these events.

Accounting for skill in trend, variability, and autocorrelation facilitates better multi-model projections: Application to the AMOC and temperature time series.

We present a novel quasi-Bayesian method to weight multiple dynamical models by their skill at capturing both potentially non-linear trends and first-order autocorrelated variability of the underlying process, and to make weighted probabilistic projections. We validate the method using a suite of one-at-a-time cross-validation experiments involving Atlantic meridional overturning circulation (AMOC), its temperature-based index, as well as Korean summer mean maximum temperature. In these experiments the method tends to exhibit superior skill over a trend-only Bayesian model averaging weighting method in terms of weight assignment and probabilistic forecasts. Specifically, mean credible interval width, and mean absolute error of the projections tend to improve. We apply the method to a problem of projecting summer mean maximum temperature change over Korea by the end of the 21st century using a multi-model ensemble. Compared to the trend-only method, the new method appreciably sharpens the probability distribution function (pdf) and increases future most likely, median, and mean warming in Korea. The method is flexible, with a potential to improve forecasts in geosciences and other fields.

Hydroclimatic Variability and Predictability: A Survey of Recent Research.

Recent research in large-scale hydroclimatic variability is surveyed, focusing on five topics: (i) variability in general, (ii) droughts, (iii) floods, (iv) land-atmosphere coupling, and (v) hydroclimatic prediction. Each surveyed topic is supplemented by illustrative examples of recent research, as presented at a 2016 symposium honoring the career of Professor Eric Wood. Taken together, the recent literature and the illustrative examples clearly show that current research into hydroclimatic variability is strong, vibrant, and multifaceted.

Effects of city expansion on heat stress under climate change conditions.

We examine the joint contribution of urban expansion and climate change on heat stress over the Sydney region. A Regional Climate Model was used to downscale present (1990-2009) and future (2040-2059) simulations from a Global Climate Model. The effects of urban surfaces on local temperature and vapor pressure were included. The role of urban expansion in modulating the climate change signal at local scales was investigated using a human heat-stress index combining temperature and vapor pressure. Urban expansion and climate change leads to increased risk of heat-stress conditions in the Sydney region, with substantially more frequent adverse conditions in urban areas. Impacts are particularly obvious in extreme values; daytime heat-stress impacts are more noticeable in the higher percentiles than in the mean values and the impact at night is more obvious in the lower percentiles than in the mean. Urban expansion enhances heat-stress increases due to climate change at night, but partly compensates its effects during the day. These differences are due to a stronger contribution from vapor pressure deficit during the day and from temperature increases during the night induced by urban surfaces. Our results highlight the inappropriateness of assessing human comfort determined using temperature changes alone and point to the likelihood that impacts of climate change assessed using models that lack urban surfaces probably underestimate future changes in terms of human comfort.

Changing climate and overgrazing are decimating Mongolian steppes.

Satellite observations identify the Mongolian steppes as a hotspot of global biomass reduction, the extent of which is comparable with tropical rainforest deforestation. To conserve or restore these grasslands, the relative contributions of climate and human activities to degradation need to be understood. Here we use a recently developed 21-year (1988-2008) record of satellite based vegetation optical depth (VOD, a proxy for vegetation water content and aboveground biomass), to show that nearly all steppe grasslands in Mongolia experienced significant decreases in VOD. Approximately 60% of the VOD declines can be directly explained by variations in rainfall and surface temperature. After removing these climate induced influences, a significant decreasing trend still persists in the VOD residuals across regions of Mongolia. Correlations in spatial patterns and temporal trends suggest that a marked increase in goat density with associated grazing pressures and wild fires are the most likely non-climatic factors behind grassland degradation.

Rapid, long-distance dispersal by pumice rafting.

Pumice is an extremely effective rafting agent that can dramatically increase the dispersal range of a variety of marine organisms and connect isolated shallow marine and coastal ecosystems. Here we report on a significant recent pumice rafting and long-distance dispersal event that occurred across the southwest Pacific following the 2006 explosive eruption of Home Reef Volcano in Tonga. We have constrained the trajectory, and rate, biomass and biodiversity of transfer, discovering more than 80 species and a substantial biomass underwent a >5000 km journey in 7-8 months. Differing microenvironmental conditions on the pumice, caused by relative stability of clasts at the sea surface, promoted diversity in biotic recruitment. Our findings emphasise pumice rafting as an important process facilitating the distribution of marine life, which have implications for colonisation processes and success, the management of sensitive marine environments, and invasive pest species.