A Scale-aware Parameterization For Estimating Subgrid Variability of Downward Solar Radiation Using HIGH-RESOLUTION Digital Elevation Model Data

Abstract

Subgrid variability of solar downward radiation at the surface can be important in estimating subgrid variability of other radiation-driven variables, such as snowmelt and soil temperature. However, this information is ignored in current hydrological and weather prediction models as only the mean downward solar radiation of model grid is used. In this study, a parameterization for estimating subgrid variability of downward solar radiation from the model grid mean using high-resolution digital elevation model (DEM) data is proposed. This scheme considers aspect and slope effects on the subgrid variability. The advantage of this scheme is that computations are performed at the same resolution as the considered hydrological or weather prediction model, and subgrid topographic properties derived from high-resolution DEM data are used as static inputs. This proposed scheme has been verified in mountainous and flat areas, respectively. It is found that the scheme can well estimate the subgrid variability of downward solar radiation. Also, effects of the DEM resolution on the calculated subgrid variability and the spatial correlation of downward solar radiation are studied. Results show that modeled subgrid variability highly depends on the resolution of the DEM, while the spatial correlation is negligibly time dependent. The proposed scheme can be used in any hydrological and weather prediction model to estimate subgrid variability of downward solar radiation. For example, it is planned to be tested in future NOAA regional and global weather models to account for the effects of the subgrid variability of downward solar radiation on the snow model of the land-surface component.