Assessment of surface exchange coefficients in the Noah-MP land surface model for different land-cover types in China

The parameterization of surface exchange coefficients (C-h) representing land-atmosphere coupling strength plays a key role in land surface modelling. Previous studies have found that land-atmosphere coupling in land surface models (LSMs) is largely overestimated, which affects the predictability of weather and climate evolution. To improve the representation of land-atmosphere interactions in LSMs, this study investigated the impact of dynamic canopy-height-dependent coupling strength in an offline Noah LSM with multi-parameterization options (Noah-MP) when applied to China. Comparison with the default Noah-MP LSM showed that the dynamic scheme significantly improved the C-h calculations and realistically reduced the biases of simulated surface energy and water components against observations. It is noteworthy that the improvements brought about by the dynamic scheme differed across land-cover types. The scheme was superior in reproducing the observed C-h as well as surface energy and water variables for short vegetation (grass, crops, and shrubs), whereas the improvement for tall canopy vegetation (forest) was not significant although the estimations were reasonable. The improved version benefits from the treatment of the roughness length for heat. Further, the scheme can better reproduce the observed surface thermal components, while the improvement in hydraulic variables (such as soil moisture) remains limited. Overall, the dynamic coupling scheme markedly affects the simulation of land-atmosphere interactions, and altering the dynamics of surface coupling has the potential to improve the representation of land-atmosphere interactions and, thus, the further development of LSM.

Automated summary

The study identifies an issue with the overestimation of land-atmosphere coupling in land surface models, proposing and verifying an improved dynamic scheme that effectively corrects biases in simulated surface energy and water components, with variations across different vegetation types.