Upscaling Sensible Heat Fluxes With Area-to-Area Regression Kriging

Surface sensible heat flux (SHF) is a critical indicator for understanding heat exchange at the land-atmosphere interface. A common method for estimating regional SHF is to use ground observations with approaches such as eddy correlation (EC) or the use of a large aperture scintillometer (LAS). However, data observed by these different methods might have an issue with different spatial supports for cross-validation and comparison. This letter utilizes a geostatistical method called area-to-area regression kriging (ATARK) to solve this problem. The approach is illustrated by upscaling SHF from EC to LAS supports in the Heihe River basin, China. To construct a point support variogram, a likelihood function of four parameters (nugget, sill, range, and shape parameters) conditioned by EC observations is used. The results testify to the applicability of ATARK as a solution for upscaling SHF from EC support to LAS support.