Assessment of long-term consistency of ocean-color satellite-derived chlorophyll-a products in the Persian Gulf

Over the past two decades, several ocean color satellites have operated in parallel. The combination of different ocean color satellite sensor products is a vital task for studying the biogeochemistry of seas. In this study, we evaluated the temporal consistency of the monthly time-series and monthly interannual variations of satellite-derived chlorophyll-a concentrations (Chl-a) from four satellite sensors during ۲۰۰۲-۲۰۲۰ period over the Persian Gulf. Statistical correlation between Chl-a time series and anomalies from selected satellite sensors were significantly correlated for ۸۴% area of the Persian Gulf. Correlations were reasonably sensitive to the choice of Chl-a retrieval and atmospheric correction algorithms. The standard algorithms for Chl-a retrieval showed the lowest value of correlations, and it was indicated that these algorithms were not suitable for Chl-a estimations from satellite sensors over the Persian Gulf. The OCI algorithm for Chl-a retrieval showed more consistency among different satellite sensors and it was shown that it is more suitable than previous ones for estimation of Chl-a from selected satellite sensors. Also, it was shown that the SeaDAS and POLYMER atmospheric correction algorithms have a great influence on the Chl-a estimations from selected satellite sensors. It was shown that more than ۷۰% of the study area indicated imperfect consistency between selected atmospheric correction algorithms applied on different satellite sensors. Choosing the best atmospheric correction and Chl-a retrieval algorithms is the most important task in the estimation and utilization of Chl-a in the Persian Gulf.

Keywords:

Remote Sensing , Ocean color , Atmospheric Correction , coastal waters , Correlation analysis