Parameter estimation for boundary-layer turbulence parameterizations over heterogeneous terrain

The accurate representation of turbulent exchange in the mountain boundary layer is particularly challenging for numerical weather prediction models. However, the use of common planetary boundary layer (PBL) parameterization schemes, which invariably assume flat and homogeneous terrain, results in significant model errors over mountains. We seek to improve the accuracy of PBL parameterization schemes over complex terrain using ensemble-based parameter estimation (PE). PE within the data assimilation framework offers a way to reduce model errors by constraining model parameters with atmospheric observations. For this purpose, we use an idealized modelling environment adopting Observing System Simulation Experiments (OSSEs) that consist of a large-eddy simulation (LES) providing a virtual truth and a single column model (SCM) ensemble, where the only model error source is the PBL parameterization. We attempt to estimate parameters in PBL schemes of varying complexity affecting vertical turbulent mixing by assimilating appropriate synthetic surface observations and vertical profiles from the LES run. We demonstrate that, with proper configuration of the data assimilation system, PE makes the estimated parameters converge towards optimal values, and at the same time reduces systematic errors in simulations of the atmospheric state.