Faster climate simulations possible with synthetic turbulence shortcuts
Researchers found that artificially generated turbulence can cut computation time for atmospheric modeling by enabling quicker convergence in simulations. The discovery matters for energy companies, climate forecasters, and wind farm operators who rely on expensive supercomputer time to predict weather patterns and optimize renewable energy output.
Originaltitel: Assessment of synthetic turbulence of stably stratified atmospheric boundary layers for LES
<p>This work studies the evolution of turbulence in a Stable Boundary Layer (SBL) in Large-Eddy Simulations (LES) when a synthetic turbulence field of velocity and temperature is used as initial condition and as well as precursor. Following common approaches found in the literature, initial fields of different characteristics are created and their evolution in the LES is evaluated in order to assess the ability of the synthetically generated turbulence to represent a snapshot of SBL turbulence. The study is carried out with two modelling cases, a forested site as well as the GABLS benchmark [4]. In both cases, the usage of a turbulent SBL as an initial condition proved advantageous to reach a faster convergence presenting an opportunity for computational savings. Yet, the very different turbulence conditions of the modelling setups produce varying results with regard to the type of velocity and temperature fluctuations. Likewise, the usage of a precursor was shown able to represent the flow in a successor LES although with varying reliability, dependent on the background turbulence and the stratification level, that suppresses velocity fluctuations and could lead to the misrepresentation of turbulence level.</p>