Remote Sensing of Sea Surface Salinity Variability in the South China Sea. Issue 12 (2nd December 2020)
- Record Type:
- Journal Article
- Title:
- Remote Sensing of Sea Surface Salinity Variability in the South China Sea. Issue 12 (2nd December 2020)
- Main Title:
- Remote Sensing of Sea Surface Salinity Variability in the South China Sea
- Authors:
- Yi, Daling Li
Melnichenko, Oleg
Hacker, Peter
Potemra, James - Abstract:
- Abstract: Using newly available satellite observations of sea surface salinity (SSS), we provide, for the first time, a detailed and synoptic view of the spatiotemporal variability of SSS in the South China Sea (SCS). The results depict the SCS as a very dynamic region exhibiting variability over a broad range of time scales, from intraseasonal to interannual, with the seasonal cycle dominating (∼47% of the total SSS variance). The seasonal distribution of SSS has considerable latitudinal variations: the strongest variance across the southern SCS (∼5–12°N), weaker in the northern part of the sea (north of ∼18°N), with the weakest seasonal SSS variability in between. The factors controlling patterns of seasonal SSS distribution are closely related to both the external freshwater forcing and ocean processes over the entire SCS monsoon system. The most active interannual SSS variability is found in the northeastern and eastern parts of the SCS, as well as the adjacent western Pacific. A significant basin‐wide salinification began in summer of 2015, peaked in spring of 2016 with the averaged amplitude of up to 0.5 PSU, and maintained until the fall of 2016. Such persistent salinification during 2015–2016 following a strong El Nino event can be largely modulated by El Nino‐related atmospheric and oceanic dynamics. The intraseasonal variability was found to be surprisingly weak throughout the SCS (the standard deviation <0.2 PSU), except for a few regions near the coast where itAbstract: Using newly available satellite observations of sea surface salinity (SSS), we provide, for the first time, a detailed and synoptic view of the spatiotemporal variability of SSS in the South China Sea (SCS). The results depict the SCS as a very dynamic region exhibiting variability over a broad range of time scales, from intraseasonal to interannual, with the seasonal cycle dominating (∼47% of the total SSS variance). The seasonal distribution of SSS has considerable latitudinal variations: the strongest variance across the southern SCS (∼5–12°N), weaker in the northern part of the sea (north of ∼18°N), with the weakest seasonal SSS variability in between. The factors controlling patterns of seasonal SSS distribution are closely related to both the external freshwater forcing and ocean processes over the entire SCS monsoon system. The most active interannual SSS variability is found in the northeastern and eastern parts of the SCS, as well as the adjacent western Pacific. A significant basin‐wide salinification began in summer of 2015, peaked in spring of 2016 with the averaged amplitude of up to 0.5 PSU, and maintained until the fall of 2016. Such persistent salinification during 2015–2016 following a strong El Nino event can be largely modulated by El Nino‐related atmospheric and oceanic dynamics. The intraseasonal variability was found to be surprisingly weak throughout the SCS (the standard deviation <0.2 PSU), except for a few regions near the coast where it is likely related to the intraseasonal variability in the monsoon rainfall and subsequent variations in river runoff. Plain Language Summary: Monitoring and studying sea surface salinity (SSS) variability in the South China Sea (SCS) is important to understanding the interocean circulation and its role in the hydrological cycle. In the past decade, the technological innovation in satellite remote sensing provided an unprecedented opportunity for ocean observations. Using these new satellite products, we investigate the spatial and temporal variability of SSS in the SCS and examine the dominant processes responsible for the observed variability. We examine multiple time scales, from a few months to a few years, and find that the seasonal cycle is the strongest signal. The seasonal distribution of SSS has considerable latitudinal variations, closely controlled by both the external freshwater forcing and ocean processes over the entire SCS monsoon system. We also find that the surface layer displays a significant basin‐wide salinification during 2015–2016 because of a strong El Nino event and its related atmospheric and oceanic dynamics. We observe the maximum intraseasonal variability in a few near‐coastal areas where it is likely related to the intraseasonal variability in rainfall and subsequent variations in river runoff. Key Points: The seasonal cycle of salinity exhibits the strongest signal and is controlled by different processes over the South China Sea monsoon system A persistent basin‐wide salinification occurred during 2015–2016 because of the El Nino‐related atmospheric and oceanic dynamics An active intraseasonal variability of salinity near the coast is likely related to the intraseasonal variation in rainfall and river runoff … (more)
- Is Part Of:
- Journal of geophysical research. Volume 125:Issue 12(2020)
- Journal:
- Journal of geophysical research
- Issue:
- Volume 125:Issue 12(2020)
- Issue Display:
- Volume 125, Issue 12 (2020)
- Year:
- 2020
- Volume:
- 125
- Issue:
- 12
- Issue Sort Value:
- 2020-0125-0012-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-12-02
- Subjects:
- El Nino event -- hydrological cycle -- multi‐time scales -- satellite sea surface salinity -- South China Sea -- spatiotemporal variability
Oceanography -- Periodicals
551.4605 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2169-9291 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2020JC016827 ↗
- Languages:
- English
- ISSNs:
- 2169-9275
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4995.005000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23111.xml