Simulation of Atmospheric Boundary Layer Processes Using Local- and Nonlocal-Closure Schemes

Abstract

A soil-vegetation-atmospheric boundary layer model was developed to study the performance of two localclosure and two nonlocal-closure boundary layer mixing schemes for use in meteorological and air quality simulation models. Full interaction between the surface and atmosphere is achieved by representing surface characteristics and associated processes using a prognostic soil-vegetation scheme and atmospheric boundary layer schemes. There are 30 layers in the lowest 3 km of the model with a high resolution near the surface. The four boundary layer schemes are tested by simulating atmospheric boundary layer structures over densely and sparsely vegetated regions using the observational data from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) and from Wangara. Simulation results indicate that the near-surface turbulent fluxes predicted by the four boundary layer schemes differ from each other, even though the formulation used to represent the surface-layer processes is the same. These differences arise from the differing ways of representing subgrid-scale vertical mixing processes. Results also indicate that the vertical profiles of predicted parameters (i.e., temperature, mixing ratio, and horizontal winds) from the four mixed-layer schemes differ from each other, particularly during the daytime growth of the mixed layer. During the evening hours, after the mixed layer has reached its maximum depth, the differences among these respective predicted variables are found to be insignificant. There were some general features that were associated with each of the schemes in all of the simulations. Compared with observations, in all of the cases the simulated maximum depths of the boundary layer for each scheme were consistently either lower or higher, superadiabatic lapse rates were consistently either stronger or weaker, and the intensity of the vertical mixing was either stronger or weaker. Also, throughout the simulation period in all case studies, most of the differences in the predicted parameters are present in the surface layer and near the top of the mixed layer.

Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau

“…The respective parameters for both land surface types were estimated by a combination from the in-situ measurements and laboratory investigation of soil characteristics (Chen et al 2012). Surface emissivity, leaf area index and minimum stomatal resistance have been derived from various sources Hu et al 2009;Alapaty et al 1997) …”

An intercomparison study of two land surface models using a 1‐D model and fife measurements

“…We used a three-dimensional windowed model developed by Alapaty et al (1997b) to study the effects of different representations of soil-vegetation-atmosphere interactions on predicted boundary layer parameters using a turbulent kinetic energy (TKE) scheme. The windowed model has 35 vertical sigma layers and 3 × 3 grid cells in the horizontal layers.…”

“…In our study, we used a scheme based on TKE and its dissipation rate that is already implemented and well tested in the 1-D and a 3-D mesoscale model (MM5) by Alapaty et al (1997b) and Alapaty and Alapaty (1999). The prognostic equations used in this scheme to explicitly calculate the TKE (E) and its dissipation rate (ε) are those suggested by Yamada and Mellor (1975).…”

“…The FIFE site is located near Manhattan, KS, covering a 15 × 15 km area where grass prairie is the predominant vegetation. Various initial conditions used in the simulations are given in Alapaty et al (1997b). Measured surface fluxes (sensible and latent heat) are available for every 30-min time interval while vertical profiles of temperature, winds, and humidity obtained using slow ascent balloons are available for every ∼10 m vertical altitude intervals for various hours during each day of the observations.…”

High-Resolution Simulation of Surface and Turbulent Fluxes during HAPEX-MOBILHY

“…simpler (with much less prognostic and diagnostic equations) than higher-order schemes or more complicated nonlocal schemes such as the transilient turbulent method or bottom-up top-down diffusion, but it still includes most of the important processes occurring in the PBL, and it was shown to perform well even in convective conditions (Cuxart et al 1994;Alapaty et al 1997).…”