Analysis of Retrieval Accuracy and Spatial–Temporal Variation of Chlorophyll-A Concentration in Bohai Sea Based on GOCI

Bohai Sea is China's inland sea, its complex marine and atmospheric optical properties pose a challenge to the application of satellite data to retrieve chlorophyll-a (CHLA) concentration with high accuracy. The high accuracy retrieval results of CHLA require simultaneous consideration of the adaptability of atmospheric correction algorithms and CHLA retrieval models. In this study, four atmospheric correction methods [the standard atmospheric correction algorithms of GDPS1.4.1 and GDPS2.0, the standard near-infrared atmospheric correction algorithm of NASA (Seadas_Default), and management unit of the North Sea mathematical models (Seadas_MUMM)] and four CHLA retrieval models (OC2, YOC, OC3G, and OC2M-HI) were selected in the process of applying geostationary ocean color imager (GOCI) data to retrieve CHLA in Bohai Sea. Based on the in situ data, the adaptability of their pairwise combinations in retrieval of CHLA in Bohai Sea was evaluated. The results indicate that the OC2 and OC3G models significantly overestimated the CHLA. The combination of the Seadas_Default atmospheric correction algorithm with the YOC CHLA retrieval model, or the combination of the Seadas_MUMM atmospheric correction algorithm with the YOC CHLA retrieval model, is more suitable for the retrieval of CHLA using GOCI data in Bohai Sea. In addition, this study shows that the CHLA obtained based on the data from eight-scene GOCI data were different to the data obtained based on single-scene GOCI data (approximating traditional polar-orbiting satellite sensor data) in daily, monthly, and yearly average results. The monthly mean difference between the two is the most significant, ranging from -0.66 to 1.49 μg/l.