Multi-objective calibration of the Community Land Model Version 5.0 using in-situ observations of water and energy fluxes and variables

Abstract. This study evaluate water and energy fluxes and variables in combination with parameter optimization of the state-of-the-art land surface model Community Land Model version 5 (CLM5), using six years of hourly observations of latent heat flux, sensible heat flux, groundwater recharge and soil moisture.

The results show that multi-objective calibration in combination with truncated singular value decomposition and Tikhonov regularization is a powerful method to improve the current practice of using look-up tables to define parameter values in land surface models. Furthermore, reliability of the optimized model parameters can be estimated by statistical measures such as identifiability and relative error variance reduction. As in most other eddy covariance studies, closure of the land surface energy balance is not achieved on observation data. However, using direct measurement of turbulent fluxes as target variable, the parameter optimization is capable of matching simulations and observations of latent heat, especially during the summer period, while simulated sensible heat is clearly biased. The fact that CLM5 is not capable of matching sensible heat, not even with advanced parameter optimization of model parameter values, suggests that the lack of energy closure is due to biases in the sensible heat flux. The results from this study contribute to improvements in model characterization of water and energy fluxes. It is underlined that parameter calibration using available observations of hydrologic and energy fluxes and variables is necessary to obtain the optimal parameter set of a land surface model.