Predictability of the rainy season onset date in Central Highlands of Vietnam. (31st October 2019)

• Record Type: Journal Article
• Authors: Pham‐Thanh, Ha; van der Linden, Roderick; Ngo‐Duc, Thanh; Nguyen‐Dang, Quang; Fink, Andreas H.; Phan‐Van, Tan
• Is Part Of: International journal of climatology. Volume 40:Number 6(2020)
• Page Start: 3072
• Page End: 3086
• Publication Date: 2019-10-31
• Subjects: Central Highlands -- predictability -- rainy season onset -- seasonal prediction -- Vietnam; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.6383
• Languages: English
• ISSNs: 0899-8418

Abstract

Abstract: In this study, different criteria to determine the rainy season onset date (RSOD) and its predictability in the Central Highlands (CH) of Vietnam are investigated. Using daily rainfall amounts from 10 meteorological stations for the period 1981–2015, four criteria to determine the RSOD were tested in order to select the one that most reasonably depicts the climatology of the RSOD over the CH. Results show that the RSOD varies strongly from year to year. In the long‐term mean, the onset starts first in southern parts of the CH and then progresses to the northern parts. The earliest onset date is around the beginning of April, and the latest in the second half of May. The average RSOD is on 28 April with a standard deviation of 14 days. Thus, the RSOD is distinct from the summer monsoon onset, namely, leading the mean summer monsoon onset by about 3 weeks in some years. In terms of remote influences, the RSOD in the CH has a high correlation with the El Niño–Southern Oscillation phenomenon, with most RSODs being later during El Niño years, while being earlier during La Niña years. The RSOD in the CH also shows high correlations with sea surface temperatures (SSTs), 850‐hPa zonal winds (U850) and mean sea level pressures (PMSL) over certain regions of the Pacific and Indian Oceans. Building on these relationships, the RSOD can be successfully predicted using large‐scale fields of SST, U850 and PMSL as predictors in two different approaches, namely the field mean and principal component analysis. This suggests that the overall approach can also be applied in predicting the RSOD in the CH on sub‐seasonal to seasonal timescales. Abstract : Annual and monthly mean rainfall for the period 1981–2015 at 13 stations in the CH.