This year marks the end of the Shedding Light On Cloud Shadows project (SLOCS, 2019-2024). SLOCS aims to understand temporal, spatial, and spectral variability in surface solar irradiance driven by individual clouds from field observations and 3D cloud-resolving large-eddy simulations. In this contribution, we would like to present the highlights of the project and the most important conclusions.

The reason for initiating SLOCS is that clouds trigger large fluctuations in solar surface irradiance, and therefore in surface heat fluxes, but there is still much to be learned about these fluctuations. The incoming radiation in shadows is almost an order of magnitude less than under clear sky, while peaks near clouds shadows can sometimes reach a 50% increase with respect to clear sky, due to scattering of sunlight on clouds. Performing cloud-resolving simulations with realistic surface solar irradiance patterns under broken clouds remains therefore a challenge, and current cloud-resolving models do not capture the radiation-cloud interactions well. 

The Shedding Light On Cloud Shadows (SLOCS) project addresses this challenge by i) performing spatial observations in a spatial grid fine enough (~50 m, 10 Hz) to capture individual clouds using a newly designed instrument, and ii) developing 3D radiative transfer models for cloud-resolving models with optimal balance between detail level and performance. The FESSTVaL, LIAISE, and CloudRoots campaigns provided unique opportunities to measure surface solar irradiance around cloud shadows in different climates. In the campaigns, we performed grid measurements of radiation, while benefiting from complementary boundary-layer and cloud observations.

The most important lessons learned from the field observations are:
1. Scales as small as meters and seconds contribute significantly to fluctuations in surface solar irradiance
2. All broken cloud patterns generate strong peaks, but the underlying mechanisms vary greatly amoung cloud types
3. Spectral variations (in colors of light) are mostly significant under cumulus clouds.

We used those observations to set up a series of cloud-resolving simulations with MicroHH and to evaluate two newly-developed radiative transfer solvers: i) a ray tracer fast enough to be coupled to our cloud-resolving model and ii) a solver that post-processes the outcome of a 1D two-stream solver to emulate 3D effects. Also, we studied the impact of periodic and open lateral boundary conditions. The most important conclusions are:

1. Capturing 3D interactions between clouds and radiation accurately leads to larger clouds with more liquid water compared to those in simulations with conventional 1D methods
2. Post-processing conventional 1D radiation computations allows for simulating surface solar irradiance fields with realistic probability density functions, but inaccurate cloud shadow shape and location.
3. Open lateral boundaries in large-eddy simulations are at least as important as correct radiation-cloud interactions in producing realistic cloud shadows in the range from hectometers to kilometers.