Sensitivity of Limited Area Atmospheric Simulations to Lateral Boundary Conditions in Idealized Experiments

Abstract

Abstract The goal of limited area models (LAMs) is to downscale coarse‐gridded general circulation model output to represent small‐scale features of weather and climate. The LAM needs information from the driving coarse‐gridded model passing through its lateral boundaries. The treatment of this information transfer causes inconsistencies between driving and nested models and, subsequently, issues in regional weather and climate simulations. This work examines errors arising from choices taken by the modeler (temporal update frequency of boundary data, spatial resolution jump, and numerical lateral boundary formulation) systematically in an idealized simulation environment. So‐called Big‐Brother Experiments were performed with the LAM COSMO‐CLM (0.11° grid spacing). A baroclinic wave in a zonal channel was simulated over flat terrain with and without a Gaussian hill. The results reveal that the quality of the driving data, here represented by simulations only differing from the LAM simulations by reduced spatial resolution, dominates the performance of the nested model. Consequently, at the simulated mesoscale, the performance of the nested small‐scale model simulations is weakly sensitive to the numerical lateral boundary formulation (Davies relaxation or the newly implemented, computationally less demanding Mesinger Eta‐model formulation). The performance sensitivity to boundary update frequency and resolution jump is small when at least 6‐hourly updates and a resolution jump factor of maximally six is used. Gaussian hill LAM simulations illustrated the strength of downscaling; they can represent small‐scale features missing in the coarse‐scale driving simulations. In the idealized simulation experiments, spectral nudging is not advisable as it imprints the driving models deficits on the nested simulation.

Keywords

• lateral boundary conditions
• COSMO‐CLM
• idealized big brother experiments