An optimal ensemble of the Noah-MP land surface model for simulating surface heat fluxes over a typical subtropical forest in South China

Accurate estimation of land surface heat fluxes is critical to climate and air quality forecasting, which needs an appropriate parameterization in land surface models. The benchmarking method was applied to search for the optimal combination of the physical parameterization based on Noah land surface model with multi-physics options (Noah-MP). The effect of integrated physical mechanisms on the simulation of land surface energy fluxes in a typical subtropical forest (Dinghushan Forest Ecosystem Research Station) over South China is further investigated. The most sensitive process is the soil moisture threshold for evaporation while there are six processes have little or no effect on heat simulation. The optimal combination options are referred as follow: prescribed table leaf area index (LAI) and vegetation fraction, Jarvis scheme for canopy stomatal resistance, Noah soil moisture scheme, SIMGM model for runoff and groundwater, original Noah consistent scheme for surface layer drag coefficient and two-stream applied to grid-cell scheme for radiation transfer.