Satellite views of the Bohai Sea, Yellow Sea, and East China Sea
Highlights
► Study of Bohai Sea (BS), Yellow Sea (YS), and East China Sea (ECS). ► BS, YS, and ECS are characterized and quantified with long-term satellite observations. ► Features of ocean properties in these three seas show considerable seasonal variability. ► Multiple driving mechanisms for the ecosystem of the BS, YS, and ECS are identified.
Introduction
The Bohai Sea (BS), Yellow Sea (YS), and East China Sea (ECS) are the three major marginal seas in the western Pacific Ocean bounded by China, Korea, and Japan (Fig. 1). The Bohai Sea, Yellow Sea, and East China Sea cover ∼7.8 × 104, ∼3.8 × 105, and ∼1.25 × 106 km2, respectively, for a total coverage of ∼1.71 × 106 km2. The mean depths of the BS, YS, and ECS are about 20, 44, and 188 m, respectively. All three of these oceans are characterized with high loadings of sediment concentrations (Guo and Yanagi, 1998, Shi and Wang, 2010b, Wang et al., 2007) in the continental shelf regions. The Yellow River, which is China’s second largest river, transports ∼1.64 × 109 tons of sediment into the Bohai Sea yearly (Milliman and Meade, 1983). The sediment discharge into the ECS from the Yangtze River is approximately 5.0 × 108 tons annually (Milliman and Meade, 1983). Other major rivers, such as the Liaohe, Yalu, and Haihe, also transport significant amounts of sediment into these three seas.
Seasonal monsoons, the Kuroshio Current, and semidiurnal and diurnal tides (Fang, 1994) are primary processes that dominate the ocean hydrography, ocean circulations, sea surface temperature (SST), ocean stratification, and ocean fronts in these three oceans. Due to the sediment deposited in these three oceans via rivers, the BS, YS, and ECS are among the most turbid ocean regions in the world (Shi and Wang, 2010a, Shi and Wang, 2010b). In the BS, huge sediment transportations and depositions from the Liaohe River and the Yellow River form two major delta wetlands: the Liaohe River estuary and the Yellow River estuary. In the YS, sediment depositions from the ancient Yellow River help form the Subei Shoal off China’s Jiangsu province. The outer shelf mud in the south of Cheju Island has been found to contain calcites in its clay fraction derived from the erosion of the old Yellow River submarine delta (Milliman et al., 1985).
Satellite remote sensing has long been used to study physical, optical, biological, and biogeochemical processes in these ocean regions. SST images from the Advanced Very High Resolution Radiometer (AVHRR) were used to characterize sea surface features in the ECS (Tseng et al., 2000). Major ocean fronts in the three oceans have also been distinguished with satellite SST observations (Hickox et al., 2000). With satellite remote sensing, clear ocean-to-atmospheric feedback in the Yellow and East China Seas, triggered by the submerged ocean bottom topography (Xie et al., 2002), is also revealed. In recent years, satellite ocean color remote sensing has been increasingly used to study ocean optical, biological, and biogeochemical processes as well as to monitor the natural hazards in these regions. Monthly variation of pigment concentrations has been studied with satellite Coastal Zone Color Scanner (CZCS) observations (Tang et al., 1998). Images of chlorophyll-a concentration (Chl-a) of the Moderate Resolution Imaging Spectroradiometer (MODIS) show significant cross-shelf penetrating fronts off the southeast coast of China (Yuan et al., 2005). The occurrences of green algae blooms in the YS are also investigated with satellite ocean color observations (Hu et al., 2010, Shi and Wang, 2009b). Most recently, ocean sand ridge signatures in the BS (Shi et al., 2011a), sea ice effects in the BS (Shi and Wang, 2012a, Shi and Wang, 2012b), ocean optical and biological properties in the Korean dump site of the YS (Son et al., 2011), and the seasonal sediment plume in central ECS (Shi and Wang, 2010b), as well as the spring-neap tidal effects on satellite ocean color remote sensing in the BS, YS, and ECS (Shi et al., 2011b) have been studied using MODIS-Aqua measurements.
For the BS, YS, and ECS regions, significant ocean radiance contributions at the near-infrared (NIR) wavelengths can be found along the coast of the YS and ECS (Shi and Wang, 2009a, Wang et al., 2007). For example, the normalized water-leaving radiance (nLw(λ)) at the NIR band can reach ∼2–3 mW cm−2 μm−1 sr−1 in the Hangzhou Bay (Wang et al., 2007). The bio-optical complexities in the BS, YS, and ECS regions suggest that the standard (NIR) atmospheric correction algorithm (Gordon and Wang, 1994, IOCCG, 2010) for MODIS ocean color data processing is unable to produce valid ocean color products in order to quantify ocean optical, biological, and biogeochemical properties in these three seas. Indeed, limited ocean color products from the NASA standard (NIR) data processing, such as nLw(λ) spectra (Gordon, 2005, Gordon and Wang, 1994, Morel and Gentili, 1991, Wang, 2006b), chlorophyll-a concentration (O’Reilly et al., 1998), diffuse attention coefficient at the wavelength of 490 nm (Kd(490)) (Lee et al., 2005, Morel et al., 2007, Mueller, 2000, Wang et al., 2009a), and total suspended matter (TSM) concentration (Miller and McKee, 2004, Tassan, 1993, Zhang et al., 2010), can be used to quantitatively evaluate and characterize the short-term and long-term variability in these three seas, and consequently study the ocean and atmospheric processes contributing to these changes. Recently, a shortwave infrared (SWIR) atmospheric correction algorithm (Wang, 2007, Wang and Shi, 2005) for satellite ocean color data processing has been proposed and demonstrated to significantly improve the ocean color products in the coastal and inland turbid waters (Wang et al., 2007, Wang et al., 2009b, Wang et al., 2011, Zhang et al., 2010). In addition, a tuned (NIR-corrected) atmospheric correction algorithm using NIR bands for MODIS-Aqua ocean color data processing is also proposed for these regions (Wang et al., 2012). Indeed, Shi and Wang (2009a) showed that the black pixel assumption, on which the atmospheric correction for satellite ocean color data processing is based, is generally valid for the SWIR bands for the turbid coastal regions such as in the BS, YS, and ECS regions.
In this study, the combined NIR-SWIR atmospheric correction algorithm (Wang, 2007, Wang and Shi, 2005, Wang and Shi, 2007, Wang et al., 2009b) is used to derive ocean optical property data for both the open ocean and coastal region waters. Seasonal and interannual changes of physical, optical, biological, and biogeochemical properties in these three seas are characterized and quantified with SST (Minnett et al., 2004), nLw(λ) (Gordon and Wang, 1994, IOCCG, 2010), Chl-a (O’Reilly et al., 1998), Kd(490) (Wang et al., 2009a), and TSM concentration (Zhang et al., 2010) from the measurements of MODIS-Aqua. Annual and seasonal climatologies of nLw(λ), Chl-a, Kd(490), TSM, and SST in the BS, YS, and ECS regions are derived and quantified. The evaluations of seasonal and interannual variations of all these physical, optical, biological, and biogeochemical parameters are also provided and correlated to the ocean and atmospheric processes.
Section snippets
MODIS ocean color and SST data processing in the BS, YS, and ECS Regions
MODIS is a key instrument aboard the NASA Terra (1999 to present) and Aqua (2002 to present) satellites. MODIS provides radiometric measurements in 36 spectral bands ranging in wavelengths from 412 nm to 14.2 μm. It can provide a wide range of land, atmosphere, and ocean products (Salomonson et al., 1989). Specifically for the ocean, it can provides SST retrievals from the measurements of the thermal infrared bands at 11–12 μm wavelengths and ocean color products in the visible and NIR bands
Annual climatology
Fig. 2 shows MODIS-Aqua-derived climatology maps from measurements of 2002–2009 for nLw(λ) spectra at wavelengths of 443 nm (nLw(443)) (Fig. 2a), 555 nm (nLw(555)) (Fig. 2b), 645 nm (nLw(645)) (Fig. 2c), and 859 nm (nLw(859)) (Fig. 2d), as well as for Chl-a (Fig. 2e), Kd(490) (Fig. 2f), TSM (Fig. 2g), and SST (Fig. 2h) in the BS, YS, and ECS regions. Fig. 2a-d show the annual mean fields of nLw(443), nLw(555), nLw(645), and nLw(859) in the region, respectively. The enhancements of nLw(λ) at blue
Mechanism driving the satellite observations of the BS, YS, and ECS
This study shows that BS, YS, and ECS regions experience significant variability between 2002 and 2009. In the continental shelf of the BS, YS, and ECS, ocean bottom is covered with silty clay south of the Yangtze River due to accumulation of Yangtze River sediments and silty, clay-like sands from the ancient Yellow River to the north (Demaster et al., 1985, Milliman et al., 1985). The spatial patterns of the annual and seasonal climatology (Fig. 2, Fig. 3, Fig. 4, Fig. 5, Fig. 6) and their
Summary
In this study, 8-year MODIS-Aqua observations are used to quantify and characterize the physical, optical, biological, and biogeochemical properties in the BS, YS, and ECS regions. As described in Shi and Wang (2010a), these regions are among the world’s most turbid ocean regions. Even though it has been long known that the BS, YS, and ECS are featured with highly turbid waters in coastal regions and ocean optical, biological, and biogeochemical property features in these three seas show
Acknowledgements
This research was supported by NASA and NOAA funding and grants. MODIS L1B data and SST data were obtained from the NASA/GSFC MODAPS Services website and ocean color website, respectively. We thank three anonymous reviewers for their constructive comments. The views, opinions, and findings contained in this paper are those of the authors and should not be construed as an official NOAA or U.S. Government position, policy, or decision.
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