Frequency of compound hot–dry weather extremes has significantly increased in Australia since 1889

Abstract

There is high confidence that climate change has increased the probability of concurrent temperatureprecipitation extremes, changed their spatial-temporal variations, and affected the relationships between drivers of such natural hazards. However, the extent of such changes has been less investigated in Australia. Daily weather data (131 years, 1889-2019) at 700 grid cells (1• × 1•) across Australia was obtained to calculate annual and seasonal mean daily maximum temperature (MMT) and total precipitation (TPR). A nonparametric multivariate copula framework was adopted to estimate the return period of compound hotdry (CHD) events based on an 'And' hazard scenario (hotter than a threshold 'And' drier than a threshold). CHD extremes were defined as years with joint return periods of larger than 25 years. Mann-Kendall nonparametric tests was used to analyse trends in MMT and TPR as well as in the frequency of univariate and CHD extremes. A general cooling-wetting trend was observed over 1889-1989. Significant increasing trends were detected over 1990-2019 in the frequency and severity of hot extremes across the country while trends in dry extremes were mostly insignificant (and decreasing). Results showed a significant increase in the association between temperature and precipitation at various temporal scales. The frequency of CHD extremes was mostly stable over 1889-1989, but significantly increased between 1990 and 2019 at 44% of studied grid cells, mostly located in the north, south-east and south-west. Spatial homogeneity (i.e. connectedness) and propagation of extreme events from one grid cell to its neighbouring cells was investigated across Australia. It can be concluded that this connectedness has not significantly changed since 1889.

Climate stressors modulate interannual olive yield at province level in Italy: A composite index approach to support crop management

“…We suggest the composite risk index is a potentially useful tool for developing climate service predictions of risk, albeit acknowledging some local inconsistency, that could be integrated with other well‐established methodologies such as Decision Support Systems currently used for assessing crop yield trajectories. Several types of compound indexes are available in literature to investigate weather extremes (see, for example Collins, 2021), but they rarely correlate them with the effects on crops; the temporal aggregation of weather variables on a bimonthly basis, their standardization using Z ‐score, and aggregation into a composite risk index linked to exceptional yields enables an interpretable seasonal forecasting use of C. The forecasting capabilities could also be enhanced by coupling the proposed method with physiologically based models (Gutierrez et al, 2005; Ponti et al, 2015) of olive growth and development that predict the phenology and relative estimates of yield potential, and the dynamics of the olive fly (Gutierrez et al, 2009; Ponti et al, 2014), and the disease X. fastidiosa (see Gilioli et al, 2023; Strona & Castellano, 2018). The system model by Gilioli et al (2023) determined that the abundance of the vector also influenced by weather was the key factor determining the spread rate of the pathogen.…”

Compound drought and hot events assessment in Australia using copula functions

“…A relationship between drought conditions and hot events has been identified in several regions of the world [26,27], such as China [28,29], the Mediterranean basin [30,31], Brazil [32], the U.S.A. [33], and Australia [34][35][36][37]. Moreover, an increase in the frequency of these compound events has also been identified [31-33, 38, 39], driven mainly by the increase in hot events [29,31,33,40]. The frequency of these compound events is expected to continue increasing in the future, as pointed out by future projections for either low or highemission scenarios [41,42].…”

“…Although copulas have proved to be a very efficient and flexible tool to disclose important features of the dependence structure between two types of extreme events (e.g., non-linear relationships and tail dependence), other methods have been applied to explain the relationship between heatwaves and droughts. Namely, the study of the relationship between drought conditions and hot events in Australia has been made using a correlation analysis [26,[34][35][36][37], although copula functions have also been applied [39,40]. Hot events occurring during the summer months were shown to be related to drought conditions occurring concurrently [34-37, 39, 48], but also in the previous months [26,34,37,48].…”

“…Recently, [37] showed that the correlation between drought conditions and hot events varies during the months of December to February, either for concurrent or for previous drought conditions, but no work has considered a monthly temporal resolution when using copula functions. Moreover, [40] identified an increased frequency of occurrence of compound drought and hot events in the period 1990-2019, when compared to previous years, but annual or seasonal events were considered, and not events in the individual summer months.…”

Record-breaking and unprecedented compound hot and dry summers in Europe under different emission scenarios

“…Compound hot and dry (CHD) events are becoming more frequent at both global (Seneviratne et al 2021) and regional scales, such as in China (Yang et al 2023, Zhang et al 2023, Brazil (Geirinhas et al 2021), USA (Alizadeh et al 2020), Australia (Collins 2022) Europe and the Mediterranean (De Luca et al 2020, Ionita et al 2021, Markonis et al 2021, Hao et al 2022.…”