Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters
Chen, Chen-Tung Arthur
- 海洋环境－已发表论文 
Total suspended particulate matter (TSM) in coastal waters is often characterized by high concentration and significant diurnal dynamics. Insufficient spatial and temporal resolution limits both cruise sampling and polar-orbiting satellite remote sensing in the mapping of TSM diurnal dynamics in coastal regions. However, the in-orbit operation of the world's first geostationary satellite ocean color sensor, GOCI, provides hourly observations of the covered area. In this study, we proposed a practical atmospheric correction algorithm for GOCI data in turbid waters. The validation results showed that the GOCI-retrieved normalized water-leaving radiances matched the in situ values well in both quantity and spectral shapes. We also developed a regional empirical TSM algorithm for GOCI data that is applicable in extremely turbid waters. Based on these atmospheric correction and regional TSM algorithms, we generated hourly TSM maps from GOCI Level-1B data. The diurnal variations derived by GOCI were a good match to the buoy data. The hourly GOCI observations revealed that various regions and tidal phases had different diurnal variation magnitudes, with a maximum of up to 5000 mg/l in central Hangzhou Bay. Strong wind events, such as typhoons, can significantly increase TSM in the bay; however, both the GOCI observations and buoy measurements indicated that this increase was episodic, had a short duration, and returned to normal within a day after the passage of a typhoon. Our results suggest that GOCI can successfully map the diurnal dynamics of TSM in turbid coastal waters. Moreover, the significant diurnal dynamics revealed in the hourly GOCI observations implied that caution should be taken in mapping TSM in coastal waters using cruise sampling and conventional polar-orbiting satellite data, as the temporal resolution is insufficient for catching diurnal variations. (c) 2013 Elsevier Inc. All rights reserved.