Remote sensing of global daily evapotranspiration based on a surface energy balance method and reanalysis data

Currently available evapotranspiration (ET) products have not provided us with an accurate estimation for global irrigated land area. Thermal energy balance (EB) model has the potential to solve this problem. The accurate estimation of aerodynamic resistances is a major complication in most remote sensing ET models. An EB model using a column canopy-air turbulent heat diffusion method was developed to more realistically depict dynamic changes in aerodynamic resistance. In order to estimate global ET and land surface fluxes for all weather conditions, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra land surface temperature fields were combined and a nearest-evaporative-fraction gap-filling method was merged into the EB model. A global ET product covering the period 2003–2017 was produced using the EB model. By combining thermal and optional information from MODIS satellites and surface meteorological forcing data from ERA-Interim reanalysis data, the EB model provides a 5 × 5 km resolution estimate of daily ET without spatio-temporal gaps at the global scale. Assessment of the daily EB ET at 238 flux sites showed a mean bias of 0.05 mm/day and an RMSE of 1.56 mm/day. Analysis of global precipitation minus ET demonstrated that EB ET has a relatively higher potential for agriculture water resource management than currently available global ET products, such as Landflux, GLEAM, MOD16, GLDAS, and ERA-Interim ET. In addition, the EB model developed in this study can be applied to both polar and geostationary satellite thermal sensors.