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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Influence of the South China Sea Biweekly Sea Surface Temperature on the South China Sea Summer Monsoon Especially during the Indian Ocean Dipole

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Author(s):
Vaid, B. H. [1] ; Polito, P. S. [2]
Total Authors: 2
Affiliation:
[1] Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing, Jiangsu - Peoples R China
[2] Univ Sao Paulo, Inst Oceanog, Sao Paulo, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: ATMOSPHERE-OCEAN; v. 54, n. 1, p. 48-59, FEB 2016.
Web of Science Citations: 2
Abstract

The influence of the biweekly sea surface temperature (SST) in the South China Sea (SCS) on the SCS summer monsoon, especially during the Indian Ocean Dipole (IOD) is presented using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) SST and rainfall data for April to June from 1999 to 2013. During positive IOD (PIOD) years the biweekly SST anomalies over the SCS lead the rain anomalies by three days, with a significant correlation (r = 0.8, at the 99% confidence level), whereas during negative IOD (NIOD) years, the correlation is only 0.2. The biweekly SST is observed to influence the westward and northward propagating rainfall anomalies over the SCS and, hence, affect the SCS summer monsoon, especially during PIOD years. No such propagation was seen during NIOD years. The biweekly intraseasonal oscillation of SST in the SCS results in enhanced sea level pressure and surface shortwave radiation, especially during PIOD years. The potential findings here indicate that the biweekly SST in the SCS is strongly (weakly) influenced during PIOD (NIOD) years. Further, it is observed that SST in the SCS has a strong (weak) effect on the SCS summer monsoon by westward and northward propagation of rainfall, especially during PIOD (NIOD) years. When a PIOD or NIOD exists over the tropical Indian Ocean, the SCS SST will be strongly (r = 0.6, at the 99% confidence level) or weakly correlated with the residual index, respectively. (AU)