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

Abstract

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 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 are often limited to correlation rather than to causation, while the understanding of their usefulness for flood forecasting is weak. There is a need to understand better 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 sea surface temperatures required to produce extreme floods. Importantly, such an analysis could provide meaningful thresholds on which to base seasonal flood forecasts.

Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin

“…A global daily reanalysis of river discharge is provided at a resolution of 0.1 • (∼ 32 km) for the 36-year analysis period . The data are derived from the operational Global Flood Awareness System, version 2.1 (GloFAS; Alfieri et al, 2013;Harrigan et al, 2020), where runoff output from the H-TESSEL module of the European Centre for Medium-Range Weather Forecasts (ECMWF), integrated forecast system (IFS; cycle 41r2), is coupled to the calibrated LISFLOOD routing model (van Der Knijff et al (2010); see Hirpa et al (2018) for details on calibration) to produce deterministic estimates of historic river flows. All of the 58 stations were used within the calibration of Lisflood.…”

“…The impact of different climatic phases tends to cause a similar response for both rainfall and river discharge (Towner et al, 2020), though the relationship between flooding and rainfall can be non-linear (Stephens et al, 2015;Coughlan de Perez et al, 2017) with significant differences identified between the mean state of the two variables in response to the same climate phase (Dettinger and Diaz, 2000). An example of this for the Amazon is detailed by Marengo et al (2012) in a comparison study of the 1989, 1999 and 2009 floods, whereby the worst flood event did not correspond with the largest rainfall anomaly (mm −1 d −1 ).…”

Leveraging multi-model season-ahead streamflow forecasts to trigger advanced flood preparedness

“…In the Amazon basin, while the literature has described relationships between climate patterns and hydrometeorological variables, the way in which climate variables influence flood risk remains understudied (Towner et al, 2020) as a result of the nonlinear relationship between precipitation and streamflow (Stephens, Day, Pappenberger, & Cloke, 2015).…”

Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin

“…Numerous hydroclimatic drivers have been identified to cause anomalous rainfall and river discharge conditions in the Amazon basin (Towner et al, 2020), with ENSO and tropical Atlantic SST variability considered to be the most influential (Marengo et al, 1992;Ronchail et al, 2005b;Yoon and Zeng, 2010;Espinoza et al, 2019). Several indices of ENSO are available, differing on spatial location, variable type and on the number of variables used.…”

“…The impact of different climatic phases tends to cause a similar response for both rainfall and river discharge (Towner et al, 2020), though the relationship between flooding and rainfall can be non-linear (Stephens et al, 2015;Coughlan de Perez et al, 2017), with significant differences identified between the mean state of the two variables in response to the same climate phase (Dettinger and Diaz, 2000). An example of this for the Amazon is detailed by Marengo et al (2012) in a comparison study of the 1989, 1999 and 2009 floods, whereby the worst flood event did not correspond with the largest rainfall anomaly.…”