Implementation of a Single-Column Model for Fog and Low Cloud Forecasting at Central-Spanish Airports

2007 ◽  
Vol 164 (6-7) ◽  
pp. 1327-1345 ◽  
Author(s):  
Enric Terradellas ◽  
Darío Cano
Keyword(s):  
Column Model ◽  
Single Column ◽  
Single Column Model ◽  
Low Cloud

scholarly journals Large-Eddy Simulation and Single-Column Modeling of Thermally Stratified Wind Turbine Arrays for Fully Developed, Stationary Atmospheric Conditions

2015 ◽  
Vol 32 (6) ◽  
pp. 1144-1162 ◽  
Author(s):  
Adrian Sescu ◽  
Charles Meneveau
Keyword(s):  
Thermal Stratification ◽  
Layer Structure ◽  
Potential Temperature ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Shear Stresses ◽  
Column Model ◽  
Large Eddy ◽  
Single Column ◽  
Single Column Model

AbstractEffects of atmospheric thermal stratification on the asymptotic behavior of very large wind farms are studied using large-eddy simulations (LES) and a single-column model for vertical distributions of horizontally averaged field variables. To facilitate comparisons between LES and column modeling based on Monin–Obukhov similarity theory, the LES are performed under idealized conditions of statistical stationarity in time and fully developed conditions in space. A suite of simulations are performed for different thermal stratification levels and the results are used to evaluate horizontally averaged vertical profiles of velocity, potential temperature, vertical turbulent momentum, and heat flux. Both LES and the model show that the stratification significantly affects the atmospheric boundary layer structure, its height, and the surface fluxes. However, the effects of the wind farm on surface heat fluxes are found to be relatively small in both LES and the single-column model. The surface fluxes are the result of two opposing trends: an increase of mixing in wakes and a decrease in mixing in the region below the turbines due to reduced momentum fluxes there for neutral and unstable cases, or relatively unchanged shear stresses below the turbines in the stable cases. For the considered cases, the balance of these trends yields a slight increase in surface flux magnitude for the stable and near-neutral unstable cases, and a very small decrease in flux magnitude for the strongly unstable cases. Moreover, thermal stratification is found to have a negligible effect on the roughness scale as deduced from the single-column model, consistent with the expectations of separation of scale.

scholarly journals Continuous Single-Column Model Evaluation at a Permanent Meteorological Supersite

2012 ◽  
Vol 93 (9) ◽  
pp. 1389-1400 ◽  
Author(s):  
R. A. J. Neggers ◽  
A. P. Siebesma ◽  
T. Heus
Keyword(s):  
Case Studies ◽  
General Circulation ◽  
Column Model ◽  
Parameterization Schemes ◽  
Numerical Predictions ◽  
Single Column ◽  
Weather And Climate ◽  
Single Column Model ◽  
Process Level

Uncertainties in numerical predictions of weather and climate are often linked to the representation of unresolved processes that act relatively quickly compared to the resolved general circulation. These processes include turbulence, convection, clouds, and radiation. Single-column model (SCM) simulation of idealized cases and the subsequent evaluation against large-eddy simulation (LES) results has become an often used and relied on method to obtain insight at process level into the behavior of such parameterization schemes; benefits of SCM simulation are the enhanced model transparency and the high computational efficiency. Although this approach has achieved demonstrable success, some shortcomings have been identified; among these, i) the statistical significance and relevance of single idealized case studies might be questioned and ii) the use of observational datasets has been relatively limited. A recently initiated project named the Royal Netherlands Meteorological Institute (KNMI) Parameterization Testbed (KPT) is part of a general move toward a more statistically significant process-level evaluation, with the purpose of optimizing the identification of problems in general circulation models that are related to parameterization schemes. The main strategy of KPT is to apply continuous long-term SCM simulation and LES at various permanent meteorological sites, in combination with comprehensive evaluation against observations at multiple time scales. We argue that this strategy enables the reproduction of typical long-term mean behavior of fast physics in large-scale models, but it still preserves the benefits of single-case studies (such as model transparency). This facilitates the tracing and understanding of errors in parameterization schemes, which should eventually lead to a reduction of related uncertainties in numerical predictions of weather and climate.

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