Spatial variability of the diurnal cycle of heat fluxes in the atmospheric boundary layer over agricultural land and forest of the GLAFO site in Stuttgart (Germany) on a clear sky day

Spatial heterogeneity of land use impacts land-atmosphere feedback and therefore the spatial and temporal variability of latent and sensible heat fluxes within the atmospheric boundary layer. This is especially visible during clear sky days without notable advection. 
In spring and summer 2025 at the GEWEX Land Atmosphere Feedback Observatory (GLAFO) site of the University of Hohenheim (Stuttgart, Germany) an extensive field campaign was performed by the research group Land Atmosphere Feedback Initiative (LAFI) funded by the German Research Foundation. During five intensive observation periods (IOPs) the GLAFO equipment, which includes two Eddy-Covariance stations, was extended by Lidar measurements of wind, humidity and temperature.
To study the three-dimensional pattern of the heat fluxes over a heterogeneous surface during the day we applied the Weather Research and Forecasting model (WRF). We used WRF in a nested configuration with resolutions of 1250 m, 250 m and 50 m, forced with ECMWF operational data for a clear sky case study on 24 June 2025. In the two inner domains, WRF was applied in Large-Eddy simulation (LES) mode with switched-off turbulence scheme. The simulated evolution of the planetary boundary layer and the influence of the land surface on its development was compared with the temporal and vertical evolution in data from the lidar systems and eddy-covariance stations. 
In addition, we focused on the vertical representation of latent and sensible heat fluxes at the different model resolutions and their dependence on the underlying land surface. This will reveal the so-called blending height, namely the height at which the horizontal distributions of the fluxes are no longer dependent on the underlying surface. The derivation of this important variable paves the way to a more physical coupling of the land surface and the atmosphere in the model.