Forecasting solar radiation is critical for balancing the electricity grid due to increasing production from solar energy. To this end, we need precise simulation of clouds, which is traditionally done by numerical weather prediction. However, these large-scale (LS) models struggle especially with forecasting stratocumulus clouds because their coarse vertical resolution cannot capture the sharp inversion present at stratocumulus cloud top. To address this issue, we employ large eddy simulation (LES), which operates at high resolution and has demonstrated superior accuracy in simulating stratocumulus clouds. However, LES relies on input data from a LS model, which is imperfect. To reduce the uncertainty caused by the LS data, we integrate a single ensemble Kalman filter step at the start of simulation in the LES model, utilizing local observations. Our results show that this approach is computationally feasible, robust, and reduces prediction error at assimilation by 50\%. The improvement diminishes after approximately one hour of simulation due to the influence of large-scale forcing. Future work will focus on enhancing the LS inflow through nested simulations with realistic lateral boundary conditions to sustain the improvements in forecasting accuracy.

This study investigates how wind shear and momentum fluxes in the surface- and boundary layer vary across wind and cloud regimes. We use a nine-year-long data set from the Cabauw tower of the Ruisdael Observatory (NL) complemented by (8.2 x 8.2 km^2) daily LES hindcasts. An automated algorithm classifies observed and simulated days into different cloud regimes: 1) clear-sky days, 2) days with convective clouds (cumulus) rooted in the surface layer, with three ranges of cloud cover, and 3) days with clouds not rooted near the surface. Categorized days in observations and LES do not fully match, with a tendency of the LES to develop convective clouds on clear-sky days and less frequently produce non-rooted clouds, whose scales are far larger than the LES domain. Even so, the climatology and diurnal cycle of winds are for each regime very similar in LES and observations, strengthening our confidence in LES’ skill to reproduce certain clouds for an atmospheric state. Wind shear is smallest in clear-sky and cumulus regimes with limited cloud cover (CLCC), which also have the weakest 200 m wind speed and largest surface buoyancy flux. They have notably larger cross-wind fluxes, although along-wind momentum flux profiles are similar across all regimes. Cloudy days have larger momentum fluxes distributed over deeper layers, sustaining up to 20% of the surface flux value at cloud base. Compared to clear-sky, the CLCC regimes have stronger updrafts and deeper mixed-layers. At similar atmospheric stability, surface friction is larger and underestimated by Monin-Obukhov Similarity Theory.