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.

Limited-area convection-permitting climate models (CPMs) with horizontal grid-spacing less than $4$\,km are being used more and more frequently. CPMs represent small-scale features such as deep convection more realistically than coarser regional climate models (RCMs), and thus do not apply deep convection parameterisations (CPs). Because of computational costs CPMs tend to use smaller horizontal domains than RCMs. As all limited-area models (LAMs), CPMs suffer issues with lateral boundary conditions (LBCs) and nesting. We investigated these issues using idealised so-called Big-Brother (BB) experiments with the LAM COSMO-CLM

Limited‐area convection‐permitting climate models (CPMs) with horizontal grid‐spacing less than 4 km and not relying on deep convection parameterisations (CPs) are being used more and more frequently. CPMs represent small‐scale features such as deep convection more realistically than coarser regional climate models (RCMs) with deep CPs. Because of computational costs, CPMs tend to use smaller horizontal domains than RCMs. As all limited‐area models (LAMs), CPMs suffer issues with lateral boundary conditions (LBCs) and nesting. We investigated these issues using idealized Big‐Brother (BB) experiments with the LAM COSMO‐CLM. Grid‐spacing of the reference BB simulation was 2.4 km. Deep convection was triggered by idealized hills with driving data from simulations with different spatial resolutions, with/without deep CP, and with different nesting frequencies and LBC formulations. All our nested idealized 2.4‐km Little‐Brother (LB) experiments performed worse than a coarser CPM simulation (4.9 km) which used a four times larger computational domain and yet spent only half the computational cost. A boundary zone of >100 $ > 100$ grid‐points of the LBs could not be interpreted meteorologically because of spin‐up of convection and boundary inconsistencies. Hosts with grid‐spacing in the so‐called gray zone of convection (ca. 4–20 km) were not advantageous to the LB performance. The LB's performance was insensitive to the applied LBC formulation and updating (if ≤3 $\le 3$‐hourly). Therefore, our idealized experiments suggested to opt for a larger domain instead of a higher resolution even if coarser than usual (∼5 $\sim 5$ km) as a compromise between the harmful boundary problems, computational cost and improved representation of processes by CPMs.

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