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Attribution of Amazon floods to modes of climate variability: a review

Towner, J., Cloke, H. L., Lavado, W., Santini, W., Bazo, J., Coughlan de Perez, E. and Stephens, E. M. (2020) Attribution of Amazon floods to modes of climate variability: a review. Meteorological Applications. ISSN 1469-8080 (In Press)

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Abstract/Summary

Anomalous conditions in the oceans and atmosphere have the potential to be used to enhance the predictability of flood events, enabling earlier warnings to reduce risk. In the Amazon basin, extreme flooding is consistently attributed to warmer or cooler conditions in the tropical Pacific and Atlantic Oceans, with some evidence linking floods to other hydroclimatic drivers such as the Madden-Julian Oscillation (MJO). This review evaluates the impact of several hydroclimatic drivers on rainfall and river discharge regimes independently, aggregating all of the information of previous studies to provide an up to date depiction of what we currently know and do not know about how variations in climate impact flooding in the Amazon. Additionally, 34 major flood events that have occurred since 1950 in the Amazon and their attribution to climate anomalies are documented and evaluated. This review finds that despite common agreement within the literature describing the relationship between phases of climate indices and hydrometeorological variables, results linking climate anomalies and flood hazard is often limited to correlation rather than causation, while the understanding on their usefulness for flood forecasting is weak. There is a need to better understand the ocean-atmosphere response mechanisms that led to previous flood events. In particular, examining the oceanic and atmospheric conditions preceding individual hydrological extremes as opposed to composite analysis, could provide insightful information into the magnitude and spatial distribution of anomalous SSTs required to produce extreme floods. Importantly, such analysis could provide meaningful thresholds on which to base seasonal flood forecasts.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:92510
Publisher:Royal Meteorological Society

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