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Robust extension of the simple sea-surface irradiance model to handle cloudy conditions for the global ocean using satellite remote sensing data
Institution:1. Ocean Optics and Imaging Laboratory, Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai 600036, India;2. Ocean Satellite Group, National Remote Sensing Center (NRSC), ISRO, Hyderabad 500037, India
Abstract:Sea-surface solar radiation (abbreviated as photosynthetically available radiation, PAR) in the visible wavelength (400–700 nm) is an essential parameter to estimate marine primary productivity and understanding phytoplankton dynamics, upper ocean physics and biogeochemical processes. Although many remote-sensing models were developed to estimate daily PAR (DPAR) from ocean colour data, these models often produce biases in the DPAR products under cloudy-sky and complex atmospheric conditions due to the lack of parameterization to deal with the cloud cover conditions and insufficient in-situ DPAR data. This study presents an Extended Sea-surface Solar Irradiance Model (ESSIM) for estimating DPAR over the global ocean. The ESSIM uses the direct and diffuse components from the Simple sea-surface Solar Irradiance Model (SSIM) along with a new parameter to handle cloudy conditions. The ESSIM produced DPAR products with greater accuracy under both clear and cloudy conditions. Its performance was tested on the time-series MODIS-Aqua images and compared with the concurrent in-situ data and the results from two global models. Results showed that the DPAR values produced by ESSIM agree with in-situ data better than the global models for all-sky conditions (with a mean relative error of 11.267 %; a root mean square error of 5.563 Em?2day?1; and a mean net bias of 2.917 Em?2day?1). The ESSIM performed slightly better than the SSIM for clear conditions and the Frouin's Operational Algorithm (FOA) for all-sky conditions. As the new parameterization accounts for cloudy conditions, the ESSIM produced more accurate results for cloud cover conditions across latitudes (up to 60°). The time-series Level-3 binned MODIS-Aqua data (global gridded) also demonstrated that the ESSIM improved the accuracy of DPAR products and produced spatially and temporally consistent DPAR products over the global ocean regardless of the seasons and sky conditions.
Keywords:DPAR  ESSIM  MODIS-Aqua  Global Ocean  Satellite observation  Cloudy condition
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