Chen, J; He, XQ; Xing, XG; Xing, QG; Liu, ZL; Pan, DL (2020). An Inherent Optical Properties Data Processing System for Achieving Consistent Ocean Color Products From Different Ocean Color Satellites. JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 125(1), e2019JC015811.

We used field measurements and multimission satellite data to evaluate how well an inherent optical properties (IOPs) data processing system performed at correcting the residual error of the atmospheric correction in satellite remote sensing reflectance (R-rs) and how well the system simultaneously minimized intermission biases between different remote sensing systems. We developed the IOPs data processing system as a semianalytical algorithm called IDAS. Our results show that IDAS generates accurate and consistent IOPs products from two ocean color missions: Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer Aqua (MODISA). Specifically, with "high-quality" SeaWiFS and MODISA R-rs data, IDAS provided temporally consistent IOPs products for the oligotrophic open ocean resulting in an annual mean intermission difference of less than 3%, which is significantly lower than what a quasi-analytical algorithm (QAA) provided. We used IDAS to generate a long time series of b(b)(555) from the Northwest Atlantic Subtropical Gyre using SeaWiFS (1998 to 2002) and MODISA (2003 to 2017) images. Our results show that the IDAS-derived annual b(b)(555) decreased monotonically by 2.81% per decade from 1998 to 2017. Comparing the IDAS-generated annual trend for b(b)(555) to the same data processed with the QAA algorithm, we found that the QAA results differed because of impacts of the residual errors of the atmospheric correction and intermission biases. The differences in the annual trends existed despite the same temporal changing patterns of in situ particulate organic carbon existing in the Sargasso Sea and in the satellite chlorophyll-a concentration in the Northwest Atlantic Subtropical Gyre.