Relationship between sea surface salinity from L-band radiometer and optical features in the East China Sea

2014 ◽  
Author(s):  
Bumjun Kil ◽  
Derek Burrage ◽  
Joel Wesson ◽  
Stephan Howden
Keyword(s):  
East China Sea ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
East China ◽  
The East China Sea ◽  
Surface Salinity ◽  
China Sea ◽  
L Band ◽  
Band Radiometer

scholarly journals Estimation of Hourly Sea Surface Salinity in the East China Sea Using Geostationary Ocean Color Imager Measurements

2020 ◽  
Vol 12 (5) ◽  
pp. 755
Author(s):  
Dae-Won Kim ◽  
Young-Je Park ◽  
Jin-Yong Jeong ◽  
Young-Heon Jo
Keyword(s):  
Real Time ◽  
East China Sea ◽  
Ocean Color ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
East China ◽  
The East China Sea ◽  
Surface Salinity ◽  
China Sea ◽  
Mean Square Errors

Sea surface salinity (SSS) is an important tracer for monitoring the Changjiang Diluted Water (CDW) extension into Korean coastal regions; however, observing the SSS distribution in near real time is a difficult task. In this study, SSS detection algorithm was developed based on the ocean color measurements by Geostationary Ocean Color Imager (GOCI) in high spatial and temporal resolution using multilayer perceptron neural network (MPNN). Among the various combinations of input parameters, combinations with three to six bands of GOCI remote sensing reflectance (Rrs), sea surface temperature (SST), longitude, and latitude were most appropriate for estimating the SSS. According to model validations with the Soil Moisture Active Passive (SMAP) and Ieodo Ocean Research Station (I-ORS) SSS measurements, the coefficient of determination (R2) were 0.81 and 0.92 and the root mean square errors (RMSEs) were 1.30 psu and 0.30 psu, respectively. In addition, a sensitivity analysis revealed the importance of SST and the red-wavelength spectral signal for estimating the SSS. Finally, hourly estimated SSS images were used to illustrate the hourly CDW distribution. With the model developed in this study, the near real-time SSS distribution in the East China Sea (ECS) can be monitored using GOCI and SST data.

scholarly journals The Applicability of the Geostationary Ocean Color Imager to the Mapping of Sea Surface Salinity in the East China Sea

2021 ◽  
Vol 13 (14) ◽  
pp. 2676
Author(s):  
Jong-Kuk Choi ◽  
Young-Baek Son ◽  
Myung-Sook Park ◽  
Deuk-Jae Hwang ◽  
Jae-Hyun Ahn ◽  
...  
Keyword(s):  
East China Sea ◽  
Ocean Color ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
East China ◽  
Red Tides ◽  
The East China Sea ◽  
Surface Salinity ◽  
China Sea

During the summer season, low-salinity water (LSW) inputs from the Changjiang River are observed as filamentous or lens-like features in the East China Sea. Sea surface salinity (SSS) is an important factor in ocean science, and is used to estimate oceanic carbon fluxes, trace red tides, and calculate other physical processes at the surface. In this study, a proxy was developed using remote sensing reflectance (Rrs) from the Geostationary Ocean Color Imager (GOCI) centered at 490 nm (band 3), 555 nm (band 4), 660 nm (band 5), and 680 nm (band 6), and salinity (data from summer cruises during the period of 2011–2016). It was then validated to map LSW plumes in the East China Sea. The GOCI-derived surface salinity was determined by the empirical relationships between Rrs at the four bands and in situ wave glider SSS data (August 2016), and was validated with synchronous in situ hydrographic SSS data (August 2011, 2012, 2013, and 2016). The GOCI-derived SSS was considered reliable in terms of the validation with the in situ measurement with a high coefficient of determination along with a low RMSE (R2 = 0.803, RMSE = 0.914, N = 21), and in comparisons with two previous models that were used to derive SSS in the East China Sea. The GOCI-derived SSS was successfully used to examine time-series variations on diurnal and daily scales, and the effects of a typhoon in terms of marine physical and biological properties in combination with the chlorophyll-a concentration and sea surface temperature.

scholarly journals Sea surface salinity variability in the East China Sea observed by the Aquarius instrument

2014 ◽  
Vol 119 (10) ◽  
pp. 7016-7028 ◽  
Author(s):  
Seung-bum Kim ◽  
Jae Hak Lee ◽  
Paolo de Matthaeis ◽  
Simon Yueh ◽  
Chang-Su Hong ◽  
...  
Keyword(s):  
East China Sea ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
East China ◽  
The East China Sea ◽  
Surface Salinity ◽  
China Sea ◽  
Salinity Variability

A diatom-based reconstruction of summer sea-surface salinity in the Southern Okinawa Trough, East China Sea, over the last millennium

2012 ◽  
Vol 27 (8) ◽  
pp. 771-779 ◽  
Author(s):  
Dongling Li ◽  
Mads Faurschou Knudsen ◽  
Hui Jiang ◽  
Jesper Olsen ◽  
Meixun Zhao ◽  
...  
Keyword(s):  
East China Sea ◽  
Okinawa Trough ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
East China ◽  
Last Millennium ◽  
Surface Salinity ◽  
China Sea ◽  
Southern Okinawa Trough

scholarly journals The influence of episodic flooding on a pelagic ecosystem in the East China Sea

2017 ◽  
Vol 14 (10) ◽  
pp. 2597-2609 ◽  
Author(s):  
Chung-Chi Chen ◽  
Gwo-Ching Gong ◽  
Wen-Chen Chou ◽  
Chih-Ching Chung ◽  
Chih-Hao Hsieh ◽  
...  
Keyword(s):  
East China Sea ◽  
Extreme Rainfall ◽  
Sea Surface Salinity ◽  
East China ◽  
Community Respiration ◽  
The East China Sea ◽  
Pelagic Ecosystem ◽  
Surface Salinity ◽  
China Sea ◽  
Flooding Period

Abstract. This study was designed to determine the effects of flooding on a pelagic ecosystem in the East China Sea (ECS) with a focus on plankton activity and plankton community respiration (CR). In July 2010, a flood occurred in the Changjiang River. As a comparison, a variety of abiotic and biotic parameters were monitored during this flooding event and during a non-flooding period (July 2009). During the flood, the Changjiang diluted water (CDW) zone covered almost two-thirds of the ECS, which was approximately 6 times the area covered during the non-flooding period. The mean nitrate concentration was 3-fold higher during the 2010 flood (6.2 vs. 2.0 µM in 2009). CR was also higher in the 2010 flood: 105.6 mg C m−3 d−1 vs. only 73.2 mg C m−3 d−1 in 2009. The higher CR in 2010 could be attributed to phytoplankton respiration, especially at stations in the CDW zone that were not previously characterized by low sea surface salinity in 2009. In addition, zooplankton (> 330 µm) were another important component contributing to the high CR rate observed during the 2010 flood; this was a period also associated with a significant degree of fCO2 drawdown. These results collectively suggest that the 2010 flood had a significant effect on the carbon balance in the ECS. This effect might become more pronounced in the future, as extreme rainfall and flooding events are predicted to increase in both frequency and magnitude due to climate change.

scholarly journals Effects of flooding on organic carbon consumption in the East China Sea

2015 ◽  
Vol 12 (7) ◽  
pp. 5609-5639 ◽  
Author(s):  
C.-C. Chen ◽  
G.-C. Gong ◽  
W.-C. Chou ◽  
C.-C. Chung ◽  
F.-K. Shiah ◽  
...  
Keyword(s):  
East China Sea ◽  
Sea Surface Salinity ◽  
East China ◽  
Community Respiration ◽  
The East China Sea ◽  
Surface Salinity ◽  
Mean Values ◽  
China Sea ◽  
Flood Period ◽  
The Mean

Abstract. This study was designed to determine the effects of flooding on plankton community respiration (CR) in the East China Sea (ECS). In July 2010, a devastating flood occurred in the Changjiang River; the mean monthly discharge was 60 527 m3 s−1. To compare, the variables were also examined in the low riverine flow of July 2009 (33 955 m3 s−1). During the flooding, the Changjiang diluted water (CDW) zone, the sea surface salinity (SSS) was ≤ 31 psu, covering almost two thirds of the ECS, which was approximately six times that in the non-flooding period. The mean nitrate concentration was higher in 2010 (6.2 μM) than in 2009 (2.0 μM). However, in the 2010 flood, the mean values of Chl a and the bacterial biomass were only slightly higher or even lower than in 2009. Surprisingly, however, the CR was still higher in the flood period than in the non-flood period, with mean values of 105.6 and 73.2 mg C m−3 d−1, respectively. The higher CR in 2010 could be attributed to vigorous plankton activities, especially phytoplankton, at stations in the CDW zone, which were not mostly covered by low SSS in 2009. There was a huge amount of fCO2 drawdown in the 2010 flood. These results suggested that the devastating flood in 2010 had a significant effect on the carbon balance in the ECS. This effect might become more pronounced as extreme rainfall events and flooding magnitudes increase dramatically throughout the world.

scholarly journals Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea

2021 ◽  
Vol 9 (3) ◽  
pp. 279
Author(s):  
Zhehao Yang ◽  
Weizeng Shao ◽  
Yuyi Hu ◽  
Qiyan Ji ◽  
Huan Li ◽  
...  
Keyword(s):  
East China Sea ◽  
Oil Spill ◽  
Oil Spills ◽  
Ocean Model ◽  
Sea Surface ◽  
East China ◽  
The East China Sea ◽  
Sar Images ◽  
China Sea ◽  
Spatial Coverage

Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China Sea was hindcast simulated using the oil particle-tracing method. Sea-surface winds from the European Centre for Medium-Range Weather Forecasts (ECMWF), currents simulated from the Finite-Volume Community Ocean Model (FVCOM), and waves simulated from the Simulating WAves Nearshore (SWAN) were employed as background marine dynamics fields. In particular, the oil spill simulation was compared with the detection from Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) images. The validation of the SWAN-simulated significant wave height (SWH) against measurements from the Jason-2 altimeter showed a 0.58 m root mean square error (RMSE) with a 0.93 correlation (COR). Further, the sea-surface current was compared with that from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2), yielding a 0.08 m/s RMSE and a 0.71 COR. Under these circumstances, we think the model-simulated sea-surface currents and waves are reliable for this work. A hindcast simulation of the tracks of oil slicks spilled from the Sanchi shipwreck was conducted during the period of 14–17 January 2018. It was found that the general track of the simulated oil slicks was consistent with the observations from the collected GF-3 SAR images. However, the details from the GF-3 SAR images were more obvious. The spatial coverage of oil slicks between the SAR-detected and simulated results was about 1 km2. In summary, we conclude that combining numerical simulation and SAR remote sensing is a promising technique for real-time oil spill monitoring and the prediction of oil spreading.

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