28 years (1980–2007) of station and gridded reanalysis data were used to investigate the effects of El Niño/Southern Oscillation (ENSO) on autumn rainfall in the Extended Central Vietnam (ECV) region. Results show that, under El Niño conditions, autumn rainfall in Central Vietnam is reduced by about 10 to 30%. This reduction seems to be caused by a weakening of the North East monsoon circulation, which appears to be linked to an anomalous anticyclonic vortex and a positive sea level pressure anomaly over the East Sea. In addition, the disappearance of a secondary moisture source over the southern region of the East Sea also favors the reduction in rainfall over this region. Conversely, during La Niña, the total autumn rainfall in the ECV region increases by about 9 to 19%. The strengthening of the North East monsoon, with a cyclonic wind anomaly over the East Sea, helps to increase the moisture supply to the area by about 10 to 20%, resulting in enhanced rainfall in the ECV. It is also found that the La Niña conditions do not only cause an increase in rainfall, but also change the temporal distribution of the monthly rainfall over the region, with more rainfall in the latter months of the year.
In October 2020, Central Vietnam was struck by heavy rain resulting from a sequence of 5 tropical depressions and typhoons. The immense amount of water led to extensive flooding and landslides that killed more than 200 people, injured more than 500 people, and caused direct damages valued at approximately 1.2 billion USD. Here, we quantify how the intensity of the precipitation leading to such exceptional impacts is attributable to anthropogenic climate change. First, we define the event as the regional maximum of annual maximum 15-day average rainfall (Rx15day). We then analyse the trend in Rx15day over Central Vietnam from the observations and simulations in the PRIMAVERA and CORDEX-CORE ensembles, which pass our evaluation tests, by applying the generalised extreme value (GEV) distribution in which location and scale parameters exponentially covary with increasing global temperatures. Combining these observations and model results, we find that the 2020 event, occurring about once every 80 years (at least 17 years), has not changed in either probability of occurrence (a factor 1.0, ranging from 0.4 to 2.4) or intensity (0%, ranging from −8 to +8%) in the present climate in comparison with early-industrial climate. This implies that the effect of human-induced climate change contributing to this persistent extreme rainfall event is small compared to natural variability. However, given the scale of damage of this hazard, our results underline that more investment in disaster risk reduction for this type of rainfall-induced flood hazard is of importance, even independent of the effect of anthropogenic climate change. Moreover, as both observations and model simulations will be extended with the passage of time, we encourage more climate change impact investigations on the extreme in the future that help adaptation and mitigation plans and raise awareness in the country.
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