The role of climate variability in extreme floods in Europe

Nobre, Gabriela Guimarães; Jongman, Brenden; Aerts, Jeroen C. J. H.; Ward, Philip J.

doi:10.1088/1748-9326/aa7c22

Cited by 67 publications

(73 citation statements)

References 71 publications

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“…Further, Steirou et al () note the importance of the winter NAO state for the amplitude and timing of spring snowmelt as well as the varying importance of other modes of climate variability such as the Scandinavia (SCA) and the East Atlantic/West Russian (EA/WR) patterns. These findings resonate with those of Nobre, Jongman, Aerts, and Ward () in relation to the influence of the NAO and EA patterns on extreme rainfall, flood occurrence, and flood damage across Europe. For the eastern United States, stream flow demonstrates strong seasonal and NAO strength dependency (Coleman & Budikova, ; Sheldon & Burd, ).…”

Section: Modes Of Climate Variability and River Flowsupporting

confidence: 89%

Climate and rivers

McGregor

2019

River Research & Apps

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Over the last few decades as hydrologists have slowly raised their line of sight above the watershed boundary, it has become increasingly recognised that what happens in the atmosphere, as a major source of moisture for the terrestrial branch of the hydrological cycle, can strongly influence river dynamics at a range of spatial and temporal scales. Notwithstanding this, there is still a tendency for some in the river research community to restrict their gaze to the river channel or floodplain. However, Geoff Petts, the person to which this special issue is dedicated, understood well and widely encouraged a holistic view of river catchment processes. This included an acknowledgment of the role of climate, in its broadest sense, in shaping what happens within and without the river channel. The purpose of this paper therefore is to offer a broad overview of the role of some aspects of climate science in advancing knowledge in river research. Topics to be addressed include the role of climate in influencing river flow regimes, a consideration of the large‐scale climate mechanisms that drive hydrological variability within river basins at interannual to decadal timescales and atmospheric rivers and their link to surface hydrology. In reviewing these topics, a number of key knowledge gaps have emerged including attributing the causes of river flow regime changes to any one particular cause, the nonstationary and asymmetric forcing of river regimes by modes of climate variability and establishing links between atmospheric rivers, and terrestrial river channel processes, fluvial habitats, and ecological change.

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Section: Modes Of Climate Variability and River Flowsupporting

confidence: 89%

Climate and rivers

McGregor

2019

River Research & Apps

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“…Flooding at individual stations is known to exhibit serial correlation (Douglas et al, 2000;Mallakpour et al, 2017), with flood-rich and flood-poor periods; our results show that at a larger scale, years with widespread flooding are also clustered in time. However, although flood risks in Europe are known to be affected by the El Niño-Southern Oscillation and the North Atlantic Oscillation (Emerton et al, 2017;Nobre et al, 2017;Ward et al, 2014), neither has a measurable correlation with the average European flood synchrony scale ( Figure S5). However, although flood risks in Europe are known to be affected by the El Niño-Southern Oscillation and the North Atlantic Oscillation (Emerton et al, 2017;Nobre et al, 2017;Ward et al, 2014), neither has a measurable correlation with the average European flood synchrony scale ( Figure S5).…”

Section: Resultsmentioning

confidence: 99%

“…This serial correlation in flood synchrony suggests a possible link to drivers that vary over multiannual time scales, such as long-term climatic oscillations. However, although flood risks in Europe are known to be affected by the El Niño-Southern Oscillation and the North Atlantic Oscillation (Emerton et al, 2017;Nobre et al, 2017;Ward et al, 2014), neither has a measurable correlation with the average European flood synchrony scale ( Figure S5). This disconnect may arise from regional differences on how El Niño-Southern Oscillation and the North Atlantic Oscillation affect flood risks in Europe (Emerton et al, 2017;Nobre et al, 2017;Ward et al, 2014).…”

Section: 1029/2018gl081883mentioning

confidence: 99%

Growing Spatial Scales of Synchronous River Flooding in Europe

Berghuijs

Allen

Harrigan

et al. 2019

Geophysical Research Letters

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River flooding is a common hazard, causing billions of dollars in annual losses. Flood impacts are shaped by the spatial scale over which different rivers flood simultaneously, but this dimension of flood risk remains largely unknown. Using annual flood data from several thousand European rivers, we demonstrate that the flood synchrony scale—the distance over which multiple rivers flood near synchronously—far exceeds the size of individual drainage basins and varies regionally by more than an order of magnitude. These data also show that flood synchrony scales have grown by about 50% over the period 1960–2010. Detrended flood synchrony values are serially correlated, implying that years with spatially extensive floods tend to follow one another. These findings reveal that flood risks are correlated well beyond the individual drainage basins for which flood hazards are typically assessed and managed.

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“…Furthermore, positive NAO (in winter) and negative phases of NAO (in summer) and EAWR (in fall) are related to an increase in the probability of Low and Medium Damaging flood events. In northern Europe, during winter months rainfall variability is strongly modulated by the NAO and the EA, in which their positive phases are linked to higher than average and more intense extreme rainfall in the United Kingdom, Ireland, and in the Scandinavian countries (Casanueva et al, 2014;Guimarães Nobre et al, 2017). In addition, the combination of positive SOI and negative NAO has previously been linked with increased precipitation and high peak discharges in northern European regions in summer (Shaman, 2014;Zanardo et al, 2019), whereas negative EAWR is related to wetter autumns in the latter regions (Casanueva et al, 2014).…”

Section: 1029/2019ef001450mentioning

confidence: 99%

“…We use the NatCatSERVICE dataset of Munich Re (2016) to derive time-series of direct tangible flood losses. This dataset registers flood events in Europe, and their respective period, timing, location, and damages (in US$) since 1980, and has been widely used in previous studies (e.g., Bischiniotis et al, 2018;Guimarães Nobre et al, 2017;Hoeppe, 2016). We adjust the nominal flood losses value into 2016 US$ values according to the inflation rate obtained from the World Development indicators produced by the World Bank (available at https://data.worldbank.org/indicator/ny.gdp.defl.zs).…”

Section: Step 1: Extracting Indicators 211 Extracting Flood Lossesmentioning

confidence: 99%

What Will the Weather Do? Forecasting Flood Losses Based on Oscillation Indices

et al. 2020

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Atmospheric oscillations are known to drive the large‐scale variability of hydrometeorological extremes in Europe, which can trigger flood events and losses. However, to date there are no studies that have assessed the combined influence of different large‐scale atmospheric oscillations on the probabilities of flood losses occurring. Therefore, in this study we examine the relationship between five indices of atmospheric oscillation and four classes of flood losses probabilities at subregional European scales. In doing so, we examine different combinations of atmospheric oscillations, both synchronous and seasonally lagged. By applying logistic regressions, we aim to identify regions and seasons where probabilities of flood losses occurring can be estimated by indices of atmospheric oscillation with higher skill than historical probabilities. We show that classes of flood losses can be predicted by synchronous indices of atmospheric oscillation and that in some seasons and regions lagged relationships may exist between the indices of atmospheric oscillation and the probability of flood losses. Furthermore, we find that some models generate increased (or decreased) probability of flood losses occurring when the indices are at their extreme positive or negative phases. A better understanding of the effects of atmospheric oscillations on the likelihood of flood losses occurring represents a step forward in achieving flood resilience in Europe. For instance, improved early predictions of the indices that represent such atmospheric oscillations, or the evidence of a lagged relationship between their teleconnections and floods, can significantly contribute to mitigating the socioeconomic burden of floods.

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The role of climate variability in extreme floods in Europe

Cited by 67 publications

References 71 publications

Climate and rivers

Climate and rivers

Growing Spatial Scales of Synchronous River Flooding in Europe

What Will the Weather Do? Forecasting Flood Losses Based on Oscillation Indices

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