Document Type : Original Research Article
Iranian National Institute of Oceanography and Atmospheric Science (INIOAS)
Center for International Scientific Studies & Collaboration (CISSC), ministry of Science Research and Technology, Tehran, Iran
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 2002-2020 period over the Persian Gulf. Statistical correlation between Chl-a time series and anomalies from selected satellite sensors were significantly correlated for 84% 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 70% 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.