What Will the Weather Do? Forecasting Flood Losses Based on Oscillation Indices
| Autor: | Jeroen C. J. H. Aerts, Gabriela Guimarães Nobre, Konstantinos Bischiniotis, Philip J. Ward, Matteo Giuliani, Hans de Moel |
|---|---|
| Přispěvatelé: | Water and Climate Risk |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
atmospheric oscillation
disaster risk reduction ENSO flood forecasting impact-based forecasting NAO 010504 meteorology & atmospheric sciences Disaster risk reduction Flood forecasting 0207 environmental engineering 02 engineering and technology 01 natural sciences impact‐based forecasting Earth and Planetary Sciences (miscellaneous) GE1-350 Hydrometeorology 020701 environmental engineering Resilience (network) QH540-549.5 0105 earth and related environmental sciences General Environmental Science Ecology Flood myth Oscillation SDG 11 - Sustainable Cities and Communities Environmental sciences El Niño Southern Oscillation 13. Climate action Climatology Environmental science Teleconnection |
| Zdroj: | Guimarães Nobre, G, de Moel, H, Giuliani, M, Bischiniotis, K, Aerts, J C J H & Ward, P J 2020, ' What Will the Weather Do? Forecasting Flood Losses Based on Oscillation Indices ', Earth's Future, vol. 8, no. 3, e2019EF001450, pp. 1-16 . https://doi.org/10.1029/2019EF001450 Earth's Future, 8(3):e2019EF001450, 1-16. AGU Earth's Future, Vol 8, Iss 3, Pp n/a-n/a (2020) |
| ISSN: | 2328-4277 |
| DOI: | 10.1029/2019EF001450 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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