Diurnal Variation of Land Surface Wind Speed Probability Distribution with an Idealized Single-Column Climate Modeling

Knowledge of land surface wind speed (SWS) probability distribution is essential for wind power estimation, surface fluxes estimation, and wind risk assessment. Ten years Cabauw wind tower observation demonstrates a large diurnal cycle of wind power within the bottom 140m; while the observed diurnal variations of SWS are characterized by the Weibull like daytime PDF and the above-Weibull nighttime PDF from 21 years weather station observations over global land. However, most current state of art regional climate models and general circulation models are incapable of simulate the observed diurnal varying SWS PDF, particularly at night.

In this study, the single column version of the CCCma third generation AGCM is coupled with a stochastic wind model to simulate diurnal variations of surface wind speed distribution over land surface. A semi-empirical 1st-order TKE scheme is developed and applied in the stability based vertical diffusion scheme, in which the shear and buoyancy generation terms are balanced by the TKE dissipation term. The Prandl number becomes very large in a very stable PBL. There is a cut-off level above which, turbulence will vanish unless forced (e.g., by the presence of a TKE source associated with breaking gravity wave). This forced TKE source is represented by a bursty-type stochastic noise in this idealized SCM study.

Diurnal cycle of wind power and the leading three momentum of boundary layer wind speed are well simulated over moderate rough land surface. Sensitivity test results suggest that the forced TKE source between the cut-off Richardson number level and the top of boundary layer and high vertical resolution are necessary to simulate the observed fine structure of boundary layer wind speed PDF near the wind turbine level between 10m to 140m. Results also suggested that the Non-Weibull behavior of nighttime SWS PDF becomes more significant under smaller background geostrophic winds.