Jan Kleissl

Large‐eddy simulation of a diurnal cycle of the atmospheric boundary layer: Atmospheric stability and scaling issues

A simulation of a diurnal cycle of atmospheric boundary layer (ABL) flow over a homogeneous terrain is performed using large-eddy simulation (LES) with the Lagrangian scale-dependent dynamic subgrid-scale model. The surface boundary condition is derived from the field observations of surface heat flux from the HATS experiment (Horst et al., 2004; Kleissl et al., 2004). The simulation results display good general agreement with previous modeling and experimental studies with regard to characteristic features such as growth of the convective boundary layer by entrainment, nocturnal jet, and multilayered flow structure of the nocturnal regime. To gain a better understanding of the physical parameters affecting the statistics of the flow, we study the dependence of a subgrid parameter (dynamic Smagorinsky coefficient), resolved turbulent kinetic energy, and resolved vertical velocity variance upon atmospheric stability. The profiles of these turbulent variables plotted as a function of Obukhov length show “hysteretic” behavior that implies nonunique dependence. The subsequent use of local Richardson number as the scaling parameter shows a decrease in this “hysteresis,” but there is an increased scatter in the profiles with increasing height. Conversely, profiles plotted as a function of local Obukhov length (based on the fluxes at the local vertical level) show almost no hysteresis, confirming the validity of Nieuwstadts local scaling hypothesis. Although the local scaling hypothesis was formulated for the stable boundary layer, we find that it applies to the entire stability range of the diurnal cycle.

Numerical study of dynamic Smagorinsky models in large‐eddy simulation of the atmospheric boundary layer: Validation in stable and unstable conditions

Large-eddy simulation (LES) of atmospheric boundary layer (ABL) flow is performed over a homogeneous surface with different heat flux forcings. The goal is to test the performance of dynamic subgrid-scale models in a numerical framework and to compare the results with those obtained in a recent field experimental study (HATS (Kleissl et al., 2004)). In the dynamic model the Smagorinsky coefficient c s is obtained from test filtering and analysis of the resolved large scales during the simulation. In the scale-invariant dynamic model the coefficient is independent of filter scale, and the scale-dependent model does not require this assumption. Both approaches provide realistic results of mean vertical profiles in an unstable boundary layer. The advantages of the scale-dependent model become evident in the simulation of a stable boundary layer and in the velocity and temperature spectra of both stable and unstable cases. To compare numerical results with HATS data, a simulation of the evolution of the ABL during a diurnal cycle is performed. The numerical prediction of c s from the scale-invariant model is too small, whereas the coefficients obtained from the scale-dependent version of the model are consistent with results from HATS. LES of the ABL using the scale-dependent dynamic model give reliable results for mean profiles and spectra at stable, neutral, and unstable atmospheric stabilities. However, simulations under strongly stable conditions (horizontal filter size divided by Obukhov length >3.8) display instabilities due to basic flaws in the eddy viscosity closure, no matter how accurately the coefficient is determined.

Characteristics of PM2.5 Episodes Revealed by Semi-Continuous Measurements at the Baltimore Supersite at Ponca St

Highly time-resolved measurements of PM2.5, its major constituents, particle size distributions (9 nm to 20 μ m), CO, NO/NO2, and O3, and meteorological parameters were made from February through November 2002, at the Baltimore Supersite at Ponca St. using commercial and prototype semi-continuous instruments. The average PM2.5 mass concentration during the study period was 16.9 μ g/m3 and a total of 29 PM2.5 pollution episodes, each in which 24-h averaged PM2.5 mass concentrations exceeded 30.0 μ g/m3 for one or more days, were observed. Herein, 6 of the worst episodes are discussed. During these events, PM2.5 excursions were often largely due to elevations in the concentration of one or two of the major species. In addition, numerous short-term excursions were observed and were generally attributable to local sources. Those in OC, EC, nitrate, CO, and NOx levels were often observed in the morning traffic hours, particularly before breakdown of nocturnal inversions. Moreover, fresh accumulation aerosols from local stationary combustion sources were observed on several occasions, as evidenced by elevations in elemental markers when winds were aligned with sources resulting in PM2.5 increments of ∼ 17 μ g/m3. Overall, the results described herein show that concentrations of PM2.5 and its major constituents vary enormously on time scales ranging from < 1 hr to several days, thus imposing a more highly complex pattern of pollutant exposure than can be captured by 24-hr integrated methods, alone. The data suggest that control of a limited number of local sources might achieve compliance with daily and annual PM2.5 standards.