Time-series variation of size-fractionated plankton using GOCI data around the area of Northwest Pacific Ocean

Abstract

The phytoplankton size class (PSC) is one of key factor for the ecological andbiogeochemical processes in the ocean environment. In recent years, remote sensed data hasbeen used to determine the global distribution of PSC and phytoplankton functional type (PFT).The area of Northwest Pacific Ocean has various characteristics from clear water (e.g. EastSea) to extremely turbid water (e.g. estuary of the Yangtze River). Therefore, the ecologicaland biogeochemical processes in this area were also very intricate. In this study, we determinedthe PSC distribution in the sea area of Northwest Pacific Ocean using the Geostationary OceanColor Imager (GOCI) data. GOCI is the world’s first geostationary ocean color sensor and nowconsistently observing the seas around Korea, Japan and China. For the retrieval of PSC, wedeveloped abundance-based PSC algorithm for GOCI. Totally 1,922 pigment samples of HPLC(High Performance Liquid chromatography) data used for algorithm development, these datawas acquired from 32 different cruises performed by different institutes. To get the consistencyof pigment dataset, we carried out the quality control (QC) analysis. A quality control filter wasapplied to all pigment data using relationship of accessory pigments and total chlorophyll-aconcentration. Consequently, 88 samples and 5 entire cruises were eliminated as a result ofQC. The performance of developed algoriton functional type (PFT).The area of Northwest Pacific Ocean has various characteristics from clear water (e.g. EastSea) to extremely turbid water (e.g. estuary of the Yangtze River). Therefore, the ecologicaland biogeochemical processes in this area were also very intricate. In this study, we determinedthe PSC distribution in the sea area of Northwest Pacific Ocean using the Geostationary OceanColor Imager (GOCI) data. GOCI is the world’s first geostationary ocean color sensor and nowconsistently observing the seas around Korea, Japan and China. For the retrieval of PSC, wedeveloped abundance-based PSC algorithm for GOCI. Totally 1,922 pigment samples of HPLC(High Performance Liquid chromatography) data used for algorithm development, these datawas acquired from 32 different cruises performed by different institutes. To get the consistencyof pigment dataset, we carried out the quality control (QC) analysis. A quality control filter wasapplied to all pigment data using relationship of accessory pigments and total chlorophyll-aconcentration. Consequently, 88 samples and 5 entire cruises were eliminated as a result ofQC. The performance of developed algori