| description abstract | By coupling a multimode land surface scheme with a regional climate model, three scientific issues are addressed in this paper: (i) the regional model's sensitivity to the different levels of complexity presented by the land surface parameterization, (ii) relative model sensitivity to the land surface parameterization as compared with that to other model physical representations, and, (iii) following offline calibration, whether different complexity in the land surface representation leads to different model performance in the coupled experiments. In this study, a version of a regional model [Division of Atmospheric Research Limited Area Model (DARLAM)] is coupled with the Chameleon Surface Model (CHASM). Three sets of experiments are analyzed in this paper, employing six different complexity modes of CHASM. Model results from these coupled experiments show that the regional model is sensitive overall to different complexities represented in the CHASM modes. Moreover, these model sensitivities are larger than the model's intrinsic sensitivity to the perturbation of its initial conditions. The sensitivity is retained in a series of model configurations employing different vertical resolutions and convection schemes. Different complexities in the land surface representation lead to 10?30 W m?2 changes in surface evaporation and 0.5?2.5-K changes in surface temperature. In comparing different sets of coupled experiments, it is noted that, because of the complex feedbacks involved in air?land interactions, land surface parameterizations can induce quantitatively similar model sensitivity to that from changing other model aspects such as vertical resolution and convection parameterization. Although different CHASM modes can be calibrated to show similar offline results, when coupled with DARLAM these similarities between different complexity modes are significantly reduced. The sensitivity revealed in the coupled model simulations underlines the importance of understanding the feedbacks between model land surface parameterization and other physical components. More important, these results show that complexity in land surface representation cannot be substituted by tuning of parameters such as the surface or stomatal resistance, because offline agreement is not maintained in coupled simulations. | |
