A Combined Local and Nonlocal Closure Model for the Atmospheric Boundary Layer. Part I: Model Description and Testing

Abstract

The modeling of the atmospheric boundary layer during convective conditions has long been a major source of uncertainty in the numerical modeling of meteorological conditions and air quality. Much of the difficulty stems from the large range of turbulent scales that are effective in the convective boundary layer (CBL). Both small-scale turbulence that is subgrid in most mesoscale grid models and large-scale turbulence extending to the depth of the CBL are important for the vertical transport of atmospheric properties and chemical species. Eddy diffusion schemes assume that all of the turbulence is subgrid and therefore cannot realistically simulate convective conditions. Simple nonlocal closure PBL models, such as the Blackadar convective model that has been a mainstay PBL option in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) for many years and the original asymmetric convective model (ACM), also an option in MM5, represent large-scale transport driven by convective plumes but neglect small-scale, subgrid turbulent mixing. A new version of the ACM (ACM2) has been developed that includes the nonlocal scheme of the original ACM combined with an eddy diffusion scheme. Thus, the ACM2 is able to represent both the supergrid- and subgrid-scale components of turbulent transport in the convective boundary layer. Testing the ACM2 in one-dimensional form and comparing it with large-eddy simulations and field data from the 1999 Cooperative Atmosphere–Surface Exchange Study demonstrates that the new scheme accurately simulates PBL heights, profiles of fluxes and mean quantities, and surface-level values. The ACM2 performs equally well for both meteorological parameters (e.g., potential temperature, moisture variables, and winds) and trace chemical concentrations, which is an advantage over eddy diffusion models that include a nonlocal term in the form of a gradient adjustment.

Joint atmospheric-terrestrial water balances for East Africa: a WRF-Hydro case study for the upper Tana River basin

“…At the land-atmosphere interface, the loss or Boutput^of water from the earth's surface through evaporation and evapotranspiration is the input for the atmospheric branch, whereas for precipitation, the atmospheric output is considered an input or the gain of the terrestrial branch as in Peixoto and Oort (1992). Details of the water balance computation are available in many textbooks as in Peixoto and Oort (1992). In this section, a brief account of the relationship of terrestrial and atmospheric water balance components is provided.…”

Performance Evaluation of the Boundary-Layer Height from Lidar and the Weather Research and Forecasting Model at an Urban Coastal Site in the North-East Iberian Peninsula

“…The fifth scheme is the Asymmetrical Convective Model version 2 (ACM2) scheme (Pleim 2007), which is a first-order, non-local closure scheme and features non-local upward mixing and local downward mixing. It is a modified version of the ACM1 scheme from the MM5 model, which was a derivative of the Blackadar scheme (Blackadar 1978).…”

Tropical cyclone predictions over the Bay of Bengal using the high‐resolution Advanced Research Weather Research and Forecasting (ARW) model

“…The modelling incorporated the following: for convection, the KF (Kain, 2004), BMJ (Betts and Miller, 1986;Janjić, 2000), GDE (Grell and Dévényi, 2002) and Grell-2 (NG: New Grell) schemes; for PBL the Yonsei University (YSU; Hong et al, 2006), MYJ (Mellor and Yamada, 1982;Janjić, 2002) and Asymmetrical Convective Model version 2 (ACM; Pleim, 2007) schemes; for cloud microphysics the LIN (Lin et al, 1983), WRF single moment 3-class (WSM3; Hong et al, 2004) and WRF Single moment 6-class (WSM6; Dudhia et al, 2008) schemes; and for surface processes the five-layer soil thermal diffusion model (SOIL; Dudhia, 1996), the NOAH land surface model (Chen and Dudhia, 2001) and rapid update cycle model (RUC; Smirnova et al, 2000). As mentioned earlier, a total of 13 simulations were conducted for each of the five TCs, with a sequential order of (i) cumulus convection, (ii) microphysics, (iii) PBL turbulence and (iv) land-surface physics, such that the best CC scheme is identified first, followed by CMP sensitivity experiments with only the best CC in order to identify the best CMP scheme; the selected CC and CMP schemes are then used for three PBL sensitivity experiments, followed by surface processes sensitivity experiments with the selected CC, CMP and PBL schemes.…”

“…(e.g. Mohanty et al, 2004;Bhaskar Rao et al, 2006, 2007Prasad and Rama Rao, 2003;Trivedi et al, 2006;Srinivas et al, 2007Srinivas et al, , 2010Deshpande et al, 2010;Krishna et al, 2010;Mukhopadhyay et al, 2011;Singh et al, 2008Singh et al, , 2011Singh et al, , 2012Pattanik andMohanty, 2008, 2010;Raju et al, 2011a). Very few studies have reported the performance of numerical models statistically for the cyclones over the NIO.…”