On the Feasibility of Using Large-Eddy Simulations for Real-Time Turbulent-Flow Forecasting in the Atmospheric Boundary Layer

We investigate the feasibility of using large-eddy simulation (LES) for real-time forecasting of instantaneous turbulent velocity fluctuations in the atmospheric boundary layer. Although LES is generally considered computationally too expensive for real-time use, wall-clock time can be significantly reduced by using very coarse meshes. Here, we focus on forecasting errors arising on such coarse grids, and investigate the trade-off between computational speed and accuracy. We omit any aspects related to state estimation or model bias, but rather look at the size and evolution of restriction errors, subgrid-scale errors, and chaotic divergence, to obtain a first idea of the feasibility of LES as a forecasting tool. To this end, we set-up an idealized test scenario in which the forecasting error in a neutral atmospheric boundary layer is investigated based on a fine reference simulation, and a series of coarser LES grids. We find that errors only slowly increase with grid coarsening, related to restriction errors that increase. Unexpectedly, modelling errors slightly decrease with grid coarsening, as both chaotic divergence and subgrid-scale error sources decrease. A practical example, inspired by wind-energy applications, reveals that there is a range of forecasting horizons for which the variance of the forecasting error is significantly reduced compared to the turbulent background variance, while at the same time, associated LES wall times are up to 300 times smaller than simulated time.