Global reanalyses like ERA5 accurately capture atmospheric processes at spatial scales of O(10) km or larger. By downscaling ERA5 with large-eddy simulation (LES), LES can provide details about processes at spatio-temporal scales down to meters and seconds. Here, we present an open-source Python package named the “Large-eddy simulation and Single-column model - Large-Scale Dynamics”, or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly-periodic LES. A validation with observations, for several sensitivity experiments consisting of month-long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day-to-day variability in the weather is well captured by (LS)2D and LES, but the setup under-performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land-surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES-ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions.