Spatial Scale Consideration for Estimating All-Sky Surface Shortwave Radiation With a Modified 1-D Radiative Transfer Model

The spatial scale variability of surface shortwave radiation (SSR) budget is dominated by clouds. Therefore, a prerequisite step for accurate estimation of the instantaneous SSR components under all-sky conditions, especially partly cloudy conditions, is to determine a proper spatial scale. In this study, a modified one-dimensional (1-D) radiative transfer (RT) model is developed to study the effect of cloud cover on SSR field, in which cloud fraction (CF) is introduced to improve the classic 1-D plane-parallel RT equations and a global sensitivity analysis (GSA) is performed to quantitatively understand the effect of CF on SSR under both optically thick and optically thin cloudy conditions. An artificial neural network approach is then employed to generate multiple SSR components based on extensive RT simulations using the modified 1-D RT model and the GSA results. The optimal spatial scale is quantitatively determined through eight cloudy scenarios over the Tibetan Plateau, with different amounts and spatial distribution patterns of clouds. The GSA results show that the top three vital parameters for the modified 1-D RT model are solar zenith angle, CF, and land surface albedo. The optimal spatial scale for applying the modified 1-D RT model is about 20 km, which is surprisingly consistent with some theoretically and technically complicated simulation studies. The finding of the current study adds new evidence to the growing body of knowledge about the spatial scale consideration for estimating all-sky instantaneous SSR with 1-D RT theory.

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