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Accurate estimation of the near-surface chlorophyll-a (Chl-a) concentration in turbid estuaries via remote sensing is an ongoing challenge. Recently, with the successful launch of the third satellite of the China Ocean Colour Satellite Series, HY-1 C, equipped with the Coastal Zone Imager (CZI) with a 3-day revisit period and 50-m resolution in four bands, this study constructed a Chl-a inversion model via symbolic regression (SR) in the Pearl River Estuary (PRE) considering 60 in situ samples to explore the current ocean colour monitoring potential of the CZI. Compared to five state-of-the-art algorithms, the SR model attained a lower mean absolute percentage error (MAPE, 35.51%), mean absolute error (MAE, 1.56) and root-mean-square error (RMSE, 0.24). Additionally, the Chl-a spatial distributions determined with the SR model also better coincided with those determined with synchronous satellite products. The above results indicate that the SR model performed better than the five state-of-the-art models and could be effectively applied to turbid PRE waters. This research may provide a reference regarding the practicality and feasibility of the CZI in water environment monitoring in coastal and estuarial waters at a high temporal-spatial resolution. [ABSTRACT FROM AUTHOR]

The Bermuda Testbed Mooring (BTM) and Bay of Bengal Ocean Acidification (BOBOA) mooring measurements were used to identify changes in the partial pressure of CO2 at the sea surface (pCO2sea) and air-sea CO2 fluxes (FCO2) associated with passage of two tropical cyclones (TCs), Florence and Hudhud. TC Florence passed about 165 km off the BTM mooring site with strong wind speeds of 24.8 m s–1 and translation speed of 7.23 m s–1. TC Hudhud passed about 178 km off the BOBOA mooring site with wind speeds of 14.0 m s–1 and translation speed of 2.58 m s–1. The present study examined the effect of temperature, salinity, dissolved inorganic carbon (DIC), total alkalinity (TA), air-sea CO2 flux, and phytoplankton chlorophyll a change on pCO2sea as a response to TCs. Enhanced mixed layer depths were observed due to TCs-induced vertical mixing at both mooring sites. Decreased pCO2sea (–15.16±5.60 μatm) at the BTM mooring site and enhanced pCO2sea (14.81±7.03 μatm) at the BOBOA mooring site were observed after the passage of Florence and Hudhud, respectively. Both DIC and TA are strongly correlated with salinity in the upper layer of the isothermal layer depth (ILD). Strong (weak) vertical gradient in salinity is accompanied by strong (weak) vertical gradients in DIC and TA. Strong vertical salinity gradient in the upper layer of the ILD (0.031 psu m–1), that supply much salinity, dissolved inorganic carbon and total alkalinity from the thermocline was the cause of the increased pCO2sea in the BOBOA mooring water. Weak vertical salinity gradient in the upper layer of the ILD (0.003 psu m–1) was responsible for decreasing pCO2sea in the BTM mooring water. The results of this study showed that the vertical salinity gradient in the upper layer of the ILD is a good indicator of the pCO2sea variation after the passages of TCs. [ABSTRACT FROM AUTHOR]

Water transparency, measured with Secchi disk depth (SDD), is an important parameter for describing the optical properties of a water body. This study evaluates variations of SDD and related impact factors in the Bohai and Yellow Seas (BYS). Based on a new mechanistic model proposed by Lee et al. (2015) applied to MODIS remote sensing reflectance data, climatological SDD variation from 2003 to 2019 was estimated. The annual mean images showed an increasing trend from the coastal zone to the deep ocean. Lower values were found in the Bohai Sea (BHS), while higher values observed in the center of the southern Yellow Sea (SYS). Additionally, the entire sea has shown a decreasing temporal tend, with the variation rate lowest in the BHS at 0.003 m y−1, and highest in the SYS at 0.015 m y−1. However, the weak increasing trend that appeared since 2017 suggests that water quality seems to have improved. Further, it displayed seasonal patterns of low in winter and spring and high in summer and autumn. The empirical orthogonal function (EOF) analysis of SDD variations over the BYS, shows that the first SDD EOF mode is the highest, strongly correlated with total suspended matter. With the high correlation coefficients of chromophoric dissolved organic matter, it illustrates that the SDD variation is mainly dominated by the optical components in the seawater, although correlation with chlorophyll-a is the weakest. The second and third EOF modes show that photosynthetically available radiation, sea surface temperature, sea surface salinity, and wind speed are the main covariates that cause SDD changes. Water transparency evaluation on a long-term scale is essential for water quality monitoring and marine ecosystem protection. [ABSTRACT FROM AUTHOR]

A support vector machine (SVM) regression algorithm was developed for estimating the chlorophyll-a concentration (C chla) in the turbid estuarine waters of the Pearl River estuary (PRE) based on visible infrared imaging radiometer suite (VIIRS) ocean color data. The proposed SVM algorithm outperformed the OC3 algorithm in the turbid waters. The temporal variation and spatial distribution of SVM-based monthly C chla products were determined during 2012 and 2018. By analyzing the monthly average C chla products and ancillary data, the underlying mechanisms of the C chla coastal summer plume jet and winter bloom were revealed. The C chla coastal plume jet was often observed in June, when the zonal wind direction changed from westward to eastward and the river runoff reached its maximum value of the year. The winter bloom in the ocean area was attributed to strong mixing in the upper layer, which resulted from cooling-induced buoyancy changes. • A SVM model was developed for the estimation of chlorophyll-a concentration. • Spatial distribution and temporal variation of chlorophyll-a concentration was reveal. • The underlying mechanisms of the summer plume jet and winter bloom were discussed. [ABSTRACT FROM AUTHOR]