Heavy rainfall patterns in Vietnam and their relation with ENSO cycles

Abstract

Heavy rainfall months of more than 450 mm occur in all 56 meteorological stations in eight climatic zones of Vietnam during the rainy season from April to September in the north (>20 ∘ N), from August to December in the centre and from May to November in the south (<12 ∘ N). The severity of an El Niño Southern Oscillation (ENSO) episode, expressed as the integral of sea surface temperature anomaly (SSTA) in the central tropical Pacific over the duration, shows a 4.6-fold (2.3-fold) increase in number of heavy rainfall months during La Niña (El Niño) per unit change in severity during the 1960-2009 period, suggesting a twin peak occurrence with both ENSO extremes. A heavy rainfall index (HRI) links heavy rainfall months to the rainy season duration, and allows evaluation of the rainfall severity per station, climatic zone and ENSO cycle. For the deltas and central climatic zones, seasonal rainfall and number of heavy rainfall months are significantly higher at the p < 0.05 level during La Niña than during El Niño episodes. Interpolated seasonal rainfall shows distinct differences between regions, with location having a larger effect than ENSO cycles on monthly rainfall amounts. Twenty-year return monthly rainfall derived from generalized Pareto distributions for peak over thresholds range from 475 mm in the central highlands to 2185 mm in the central coast. The spatial and temporal patterns of heavy monthly rainfall help explain flooding and paddy inundation which occur at least twice as frequent during La Niña as compared to El Niño conditions, particularly in Central Vietnam. The relation of HRI with both 20-year return levels and ENSO cycles offers opportunities for fast screening of impacts in a wider region of Southeast Asia. Because ENSO cycles have an impact on flooding and paddy inundation, it provides prospects for early warning, differentiated for different zones and rainfall regimes.

Analysing the relationship between ocean indices and rainfall in the Chao Phraya River Basin

“…Similarly, Ueangsawat et al . () and several studies in Southeast Asia, such as in Vietnam, found that rainfall variability in this region is related with the variability of SOI index and sea surface temperature in the NINO3 and NINO3.4 regions (Chen et al ., ; Gobin et al ., ). In our study, the correlation between rainfall and SOI index is stronger than the correlation between rainfall and DMI index.…”

Spatiotemporal Trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017

“…Therefore, basin-wide or provincial-scale studies are essential to enhance the understanding on the variation of local precipitation extremes and to help local governments gain scientific information for disaster risk management. In addition, climate variability in Vietnam is modulated by El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) (Nguyen et al 2014;D'Arrigo and Ummenhofer 2015;Gobin et al 2016). The two phenomena are linked to significant anomalies in precipitation across Vietnam (Binh et al 2019).…”

Spatial distribution of the level of return of extreme precipitation events in Northeast Brazil

“…Therefore, it is necessary to develop research that helps to understand how these events behave over time, in addition to predicting the probability of occurrence of a specific event at regular intervals of time. In this respect, extreme value theory (EVT) has often been used to model extreme weather events for both global studies (Serinaldi and Kilsby, 2014) and regional studies, such as in Canada (Thiombiano et al, 2018), Finland (Pedretti and Irannezhad, 2018), China (Tu et al, 2017;Mo et al, 2018), Portugal (Santos et al, 2017a), Jakarta (Siswanto et al, 2016), Vietnam (Gobin et al, 2016), Korea (Chen et al, 2016), and United States (Heaton et al, 2011). In Brazil, EVT has been used to characterize the distribution of rainfall extremes in the city of São Paulo (Sugahara et al, 2008), the Amazon Basin (Santos et al, 2015(Santos et al, , 2016 and the city of Curitiba (Pedron et al, 2016).…”