Search

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc_PDSI_pm) covering the period 1950–2014, at 2.5° horizontal resolution. We find that the land areas affected by extreme wet, dry and wet-dry events (i.e. geographically remote, yet temporally co-occurring wet or dry extremes) all display increasing trends with time, of which changes in dry and wet-dry episodes are significant (p-value << 0.01). The most geographically widespread wet-dry event covered a combined land area of 21 million km2, with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid-point scale, we introduce two new metrics: the wet-dry (WD) ratio and the extreme transition (ET) time interval. The WD-ratio measures the relative occurrence of extreme wet or dry events, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD-ratio shows that the incidence of extreme wet episodes dominates over dry episodes in the USA, northern and southern south America, northern Europe, north Africa, western China and most of Australia. Conversely, extreme dry events are more prominent in most of the remaining regions. The median ET for wet to dry is ~ 27 months, while the dry to wet median ET is 21 months. We also evaluate correlations between wet-dry hydrological extremes and leading modes of large-scale variability, namely the: El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and American Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p-value < 0.05) a larger area compared to the latter, whereas the AMO shows an almost inverse pattern, and significantly impacts a larger overall area. Our analysis brings new insights on hydrological multi-hazards and are of direct relevance to governments and organisations with globally distributed interests, such as (re)insurance companies. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes. [ABSTRACT FROM AUTHOR]