Remote sensing algorithm for retrieving global-scale sea surface solar irradiance

This paper presents a new remote sensing (RS) algorithm for retrieving instantaneous sea surface solar irradiance (SR) by using the XGBoost (XGB) package in RStudio and available remote sensing data along with ground-truth solar irradiance data. By means of XGB, the new RS algorithm, called LSU model, was structurally built with nine key RS parameters, including photosynthetically available radiation (PAR); instantaneous PAR (iPAR); water leaving reflectance Rrs at wavelengths 412, 443, 469, and 488 nm; angstrom; aerosol optical thickness (aot_869); and latitude that represent major sources and sinks of solar irradiance, as model input variables. Among the nine parameters, the most important four parameters are PAR, iPAR, latitude, and aot_869. It was found that the sea surface SR is highly affected by conditions in both the atmosphere and the seawater. The aot_869 is by far the most important factor describing the effects of the atmospheric absorption and scattering of SR before reaching the sea surface. The most important factors describing the effects of seawater characteristics on solar irradiance are PAR, iPAR, and latitude. Comparisons with existing SR models indicate that LSU model is scientifically sound due to the use of major source and sink factors of SR as model input variables. LSU model is also technically accurate due to its fine resolution (1×1 km) and overall best performance in predicting instantaneous SR. More importantly, LSU model is globally applicable as it can be utilized to obtain global-scale SR data for any day, any time, and anywhere in the world.