Boundary-layer turbulent processes and mesoscale variability represented by Numerical Weather Prediction models during the BLLAST campaign

This study evaluates the ability of three operational models, AROME, ARPEGE and ECMWF, to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence (BLLAST) field campaign. AROME is a 2.5 km limited area non-hydrostatic model operated over France, ARPEGE a global model with a 10 km grid-size over France and ECMWF a global model with a 16 km grid-size. We analyze the representation of the vertical profiles of temperature and humidity and the time evolution of near surface atmospheric variables as well as the radiative and turbulent fluxes for a total of 12 24h-long Intensive Observing Periods. Special attention is paid to the evolution of the turbulent kinetic energy that was sampled by a combination of independent instruments. For the first time, this variable, which is a central variable in the turbulence scheme used in AROME and ARPEGE, is evaluated with observations. In general, the 24h-forecasts succeed in reproducing the variability from one day to the other in term of cloud cover, temperature, boundary-layer depth. However, they exhibit some systematic biases, in particular a cold bias within the daytime boundary layer for all models. An overestimation of the sensible heat flux is noted for two points in ARPEGE, partly related to an inaccurate simplification of surface characteristics and over-predominance of forests. AROME shows a moist bias within the daytime boundary layer, consistently with overestimated latent heat fluxes. ECMWF presents a dry bias at 2 m above surface and also overestimates the sensible heat flux. The high-resolution model AROME better resolves the vertical structures, in particular the strong daytime inversion and the evening thin stable boundary layer. This model is also capable to capture the peculiar observed features, such as the orographically-driven subsidence and a well-defined maximum in water vapor mixing ratio in the upper part of the residual layer that arises during the evening due to mesoscale advection. The mesoscale variability is analyzed and the order of magnitude is also well reproduced in AROME. AROME provides a good simulation of the diurnal variability of the turbulent kinetic energy while ARPEGE shows a right order of magnitude.