Understanding the Existence of Quasi-Universal Scaling Characteristics of the Lower Atmospheric Boundary Layer Wind Speeds in the Mesoscale Regime

In lieu of any rigorous benchmarks, historically, the planetary boundary layer (PBL) schemes have always been tested against a handful of observational or large-eddy simulation (LES)-generated datasets. However, owing to a variety of unavoidable errors (e.g., errors in initial conditions, boundary conditions), the simulated fields are always displaced in space and/or time from their observational counterparts and the standard verification matrices (e.g., correlation coefficient, root mean square error, bias, etc.) often lead to wrong conclusions. Therefore, we believe that the modeling communities need rigorous benchmarks which are not only capable of capturing the essential multiscale structure of the observed and the modeled atmospheric fields but also provide constructive feedback to the model developers. Moreover, the accurate knowledge of the scaling characteristics of the atmospheric mesoscale wind fields is important for the validation of the numerical models those focus on wind forecasting, dispersion, diffusion, horizontal transport, and optical turbulence.

In this presentation, the extended self-similarity (ESS) framework will be used to explain the lower PBL wind speed quasi-universal scaling characteristics in the mesoscale regime based on observations over the homogeneous and the complex terrains. In addition, we will present an evaluation on the performance of diverse PBL parameterization schemes used in the state-of-the-art Weather Research and Forecasting (WRF) model in simulating the ESS-based scaling behavior of the observed wind fields.