Comparison of sensible and latent heat fluxes from optical-microwave scintillometers and eddy covariance systems with respect to surface energy balance closure

Abstract

The eddy-covariance (EC) method has been widely used to measure sensible (H) and latent (LE) heat fluxes, however, it has limited spatial representativeness (hundreds of meters’ scale). Optical-microwave scintillometers (OMS) can directly measure kilometer-scale H and LE, which can be used to validate satellite remote sensing products and model simulations. Therefore, quantitative comparisons and analyses between H and LE measured by OMS and EC are important. In this study, the H and LE values measured by OMS and EC were compared and analyzed over two different surfaces: alpine meadow (homogeneous underlying surface) and irrigated cropland (heterogeneous underlying surface). Results showed that the H (LE) difference between OMS and EC measurements was approximately 17% (18%) and 27% (37%) over the homogeneous and heterogeneous underlying surfaces during the vegetation growing season, respectively. Furthermore, the difference in measured LE from OMS and EC (ΔLEOMS−EC) is caused by the combination of the difference in land surface hydrothermal conditions (LSHCs) and the different principles of OMS and EC measurements. On the one hand, ΔLEOMS−EC varied with the changing LSHCs within the instruments’ source areas over the heterogeneous surface, and the value could be decreased by irrigation and precipitation events. On the other hand, OMS averages large-scale measurements over both space and time and does not need to capture all-scale eddies (e.g., large-scale eddies), so the occurrence of advection increases ΔLEOMS−EC. Finally, compared with that of EC system, the energy balance closure ratio of OMS system was similar over the homogeneous underlying surface but significantly increased by 26% over the heterogeneous underlying surface. These results indicate that OMS has a potential advantage in measuring sensible and latent heat fluxes, particularly over heterogeneous underlying surfaces.