No abstract

No abstract

Abstract. Based upon 14 field surveys conducted between 2003 and 2008, we showed that the seasonal pattern of sea surface partial pressure of CO 2 (pCO 2 ) and sea-air CO 2 fluxes differed among four different physicalbiogeochemical domains in the South China Sea (SCS) proper. The four domains were located between 7 and 23 • N and 110 and 121 • E, covering a surface area of 1344 × 10 3 km 2 and accounting for ∼ 54 % of the SCS proper. In the area off the Pearl River estuary, relatively low pCO 2 values of 320 to 390 µatm were observed in all four seasons and both the biological productivity and CO 2 uptake were enhanced in summer in the Pearl River plume waters. In the northern SCS slope/basin area, a typical seasonal cycle of relatively high pCO 2 in the warm seasons and relatively low pCO 2 in the cold seasons was revealed. In the central/southern SCS area, moderately high sea surface pCO 2 values of 360 to 425 µatm were observed throughout the year. In the area west of the Luzon Strait, a major exchange pathway between the SCS and the Pacific Ocean, pCO 2 was particularly dynamic in winter, when northeast monsoon induced upwelling events and strong outgassing of CO 2 . These episodic events might have dominated the annual sea-air CO 2 flux in this particular area. The estimate of annual sea-air CO 2 fluxes showed that most areas of the SCS proper served as weak to moderate sources of the atmospheric CO 2 , with sea-air CO 2 flux values of 0.46 ± 0.43 mol m −2 yr −1 in the northern SCS slope/basin, 1.37 ± 0.55 mol m −2 yr −1 in the central/southern SCS, and 1.21 ± 1.48 mol m −2 yr −1 in the area west of the Luzon Strait. However, the annual sea-air CO 2 exchange was nearly in equilibrium (−0.44 ± 0.65 mol m −2 yr −1 ) in the area off the Pearl River estuary. Overall the four domains contributed (18 ± 10) × 10 12 g C yr −1 to the atmospheric CO 2 .

No abstract

Spectral remote‐sensing reflectance (Rrs, sr−1) is the key for ocean color retrieval of water bio‐optical properties. Since Rrs from in situ and satellite systems are subject to errors or artifacts, assessment of the quality of Rrs data is critical. From a large collection of high quality in situ hyperspectral Rrs data sets, we developed a novel quality assurance (QA) system that can be used to objectively evaluate the quality of an individual Rrs spectrum. This QA scheme consists of a unique Rrs spectral reference and a score metric. The reference system includes Rrs spectra of 23 optical water types ranging from purple blue to yellow waters, with an upper and a lower bound defined for each water type. The scoring system is to compare any target Rrs spectrum with the reference and a score between 0 and 1 will be assigned to the target spectrum, with 1 for perfect Rrs spectrum and 0 for unusable Rrs spectrum. The effectiveness of this QA system is evaluated with both synthetic and in situ Rrs spectra and it is found to be robust. Further testing is performed with the NOMAD data set as well as with satellite Rrs over coastal and oceanic waters, where questionable or likely erroneous Rrs spectra are shown to be well identifiable with this QA system. Our results suggest that applications of this QA system to in situ data sets can improve the development and validation of bio‐optical algorithms and its application to ocean color satellite data can improve the short‐term and long‐term products by objectively excluding questionable Rrs data.