Limited-area model sensitivity to the complexity of representation of the land surface energy balance

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 surfa ce parameterization as compared with that to other model physical represent ations, and, (iii) following offline calibration, whether different complex ity 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 wi th the Chameleon Surface Model (CHASM). Three sets of experiments are analy zed in this paper, employing six different complexity modes of CHASM. Model results from these coupled experiments show that the regional model is sen sitive overall to different complexities represented in the CHASM modes. Mo reover, these model sensitivities are larger than the model's intrinsic sen sitivity to the perturbation of its initial conditions. The sensitivity is retained in a series of model configurations employing different vertical r esolutions and convection schemes. Different complexities in the land surfa ce 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 co upled experiments, it is noted that, because of the complex feedbacks invol ved in air-land interactions, land surface parameterizations can induce qua ntitatively similar model sensitivity to that from changing other model asp ects such as vertical resolution and convection parameterization. Although different CHASM modes can be calibrated to show similar offline results, wh en coupled with DARLAM these similarities between different complexity mode s are significantly reduced. The sensitivity revealed in the coupled model simulations underlines the importance of understanding the feedbacks betwee n model land surface parameterization and other physical components. More i mportant, these results show that complexity in land surface representation cannot be substituted by tuning of parameters such as the surface or stoma tal resistance, because offline agreement is not maintained in coupled simu lations.