Applying a remotely sensed land-atmosphere coupling diagnostic to improve land surface evapotranspiration estimation

Model structural error is an important source of modeled land-atmosphere interaction uncertainty. In a previous study, a global map of soil moisture (SM) and evapotranspiration (ET) coupling strength was estimated by leveraging multi-source SM and ET estimates. This study investigates the value of this reference SM-ET coupling strength map for optimizing land surface model (LSM) estimates of ET. Specifically, we ran the Noah-MP LSM with 18 different evaporation resistance schemes over North America. The optimal scheme was then defined by minimizing the difference between LSM-modeled and reference SM-ET coupling strength on grid-by-grid basis. Ground-based evaluation demonstrates that such optimization significantly (at p = 0.05 confidence) reduces both the bias and root-mean-square-error in Noah-MP ET estimates. Similar improvements are also shown in surface SM estimates. These results demonstrate the remote sensing-based SM-ET coupling metrics can be used to select optimal Noah-MP evaporation resistance scheme. In addition, results illustrate that all potential Noah-MP evaporation resistance schemes overestimate SM-ET coupling strength within the central United States. Addressing this bias should be a key priority for future LSM development in dry-wet transitional zones.