Impacts of land surface and sea surface temperatures on the onset date of the South China Sea summer monsoon

2009 ◽  
Vol 26 (3) ◽  
pp. 493-502 ◽  
Author(s):  
Peng Liu ◽  
Yongfu Qian ◽  
Anning Huang
2015 ◽  
Vol 28 (22) ◽  
pp. 9029-9035 ◽  
Author(s):  
Guanghua Chen

Abstract In a recent paper, Kajikawa and Wang detected the interdecadal shift of the South China Sea summer monsoon (SCSSM) onset with a late SCSSM onset in an earlier epoch (1979–93) and an early SCSSM onset in a later epoch (1994–2008) and attributed this change to enhanced tropical cyclone (TC) activity and intraseasonal variability (ISV) related to 30–80-day and 10–25-day anomalies in the second epoch. This comment assesses the individual impact of TCs and ISV on the interdecadal change of the SCSSM onset by means of the removal of anomalies associated with TCs and ISV. Results herein show that TCs have no significant impact on the SCSSM onset in all years, except 2006 in which a strong and long-lived TC occurred over the South China Sea. After removing the 30–80-day anomaly, the difference in the mean SCSSM onset date in the two epochs decreases to some extent, implying that the 30–80-day anomaly can, in part, play a role in the interdecadal shift of the SCSSM onset. In contrast, the 10–25-day anomaly has an insignificant contribution to the interdecadal shift of the SCSSM onset. The discrepancy of ISV contribution results from the SCSSM background state, the magnitude and spatiotemporal scale of ISV, and the phase relationship between ISV and SCSSM transition from easterly to westerly.


2021 ◽  
Vol 925 (1) ◽  
pp. 012009
Author(s):  
Y S Djamil ◽  
R K Lestari ◽  
X Wang

Abstract Community Climate System Model version 4 (CCSM4) simulated warmer sea surface temperatures (SSTs) in the South China Sea (SCS) for the mid-Holocene scenario compared to the pre-Industrial. Previous sensitivity experiments using the atmospheric component of the CCSM4, the Community Atmospheric Model version 4 (CAM4), showed that warmer SSTs in the SCS suppresses rainfall over Borneo, which is in-contrary to the effect of the stronger insolation over the island. In this study, we show that warmer SSTs in the SCS, as simulated in the CCSM4, is responding to a weaker low-level wind impacted by the stronger convectional rainfall over Borneo due to stronger insolation. These results suggest that warmer SSTs in the SCS might act as a negative feedback which damps the effect of the stronger insolation on rainfall changes over Borneo.


2006 ◽  
Author(s):  
Yanzhen Chi ◽  
Zhaoyong Guan ◽  
Jinhai He ◽  
Li Qi ◽  
Xuefen Zhang

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 65
Author(s):  
Chunxu Zhao ◽  
Chunyan Shen ◽  
Andrew Bakun ◽  
Yunrong Yan ◽  
Bin Kang

The purpleback flying squid (Ommastrephidae: Sthenoteuthis oualaniensis) is an important species at higher trophic levels of the regional marine ecosystem in the South China Sea (SCS), where it is considered to show the potential for fishery development. Accordingly, under increasing climatic and environmental changes, understanding the nature and importance of various factors that determine the spatial and temporal distribution and abundance of S. oualaniensis in the SCS is of great scientific and socio-economic interest. Using generalized additive model (GAM) methods, we analyzed the relationship between available environmental factors and catch per unit effort (CPUE) data of S. oualaniensis. The body size of S. oualaniensis in the SCS was relatively small (<19.4 cm), with a shorter lifespan than individuals in other seas. The biological characteristics indicate that S. oualaniensis in the SCS showed a positive allometric growth, and could be suitably described by the logistic growth equation. In our study, the sea areas with higher CPUE were mainly distributed at 10°–11° N, with a 27–28 °C sea surface temperature (SST) range, a sea surface height anomaly (SSHA) of −0.05–0.05 m, and chlorophyll-a concentration (Chl-a) higher than 0.18 μg/L. The SST was the most important factor in the GAM analysis and the best fitting GAM model explained 67.9% of the variance. Understanding the biological characteristics and habitat status of S. oualaniensis in the SCS will benefit the management of this resource.


Sign in / Sign up

Export Citation Format

Share Document