Search Results
the atmospheric levels are vertically decoupled from each other arises naturally in Reynolds-averaged Navier–Stokes (RANS) models of the SBL, regardless of the domain size and number of vertical levels considered, and these results have been later confirmed by McNider et al. (2012) using a complete single-column model. Both Derbyshire (1999) and Ansorge and Mellado (2014) have raised the important question whether such decoupling in the models is only a feature of the system of equations or
the atmospheric levels are vertically decoupled from each other arises naturally in Reynolds-averaged Navier–Stokes (RANS) models of the SBL, regardless of the domain size and number of vertical levels considered, and these results have been later confirmed by McNider et al. (2012) using a complete single-column model. Both Derbyshire (1999) and Ansorge and Mellado (2014) have raised the important question whether such decoupling in the models is only a feature of the system of equations or
; Poulos et al. 2002 ) and modeling experiments (e.g., flux–gradient relationship analysis, 1D and 3D atmospheric models). Within the surface layer (SL), Monin–Obukhov similarity theory (MOST) is an accurate method for relating turbulent fluxes to properties of the mean flow ( Monin and Obukhov 1954 ). Above the SL in the SBL (where MOST does not apply), single-column models (SCMs) are often used to formulate or evaluate a turbulence parameterization scheme. These models are advantageous because of
; Poulos et al. 2002 ) and modeling experiments (e.g., flux–gradient relationship analysis, 1D and 3D atmospheric models). Within the surface layer (SL), Monin–Obukhov similarity theory (MOST) is an accurate method for relating turbulent fluxes to properties of the mean flow ( Monin and Obukhov 1954 ). Above the SL in the SBL (where MOST does not apply), single-column models (SCMs) are often used to formulate or evaluate a turbulence parameterization scheme. These models are advantageous because of
assume that to reasonably simulate future climate, these models should be able to accurately reproduce the current climatology of all clouds at a given location. Due to the complexities of GCMs, the Single Column Model (SCM) approach was developed to evaluate parameterizations ( Randall et al. 1996 ) and has been implemented by the Atmospheric Radiation Measurement (ARM) program ( Ackerman and Stokes 2003 ) to improve the representation of clouds and radiation in GCMs using long-term surface
assume that to reasonably simulate future climate, these models should be able to accurately reproduce the current climatology of all clouds at a given location. Due to the complexities of GCMs, the Single Column Model (SCM) approach was developed to evaluate parameterizations ( Randall et al. 1996 ) and has been implemented by the Atmospheric Radiation Measurement (ARM) program ( Ackerman and Stokes 2003 ) to improve the representation of clouds and radiation in GCMs using long-term surface
encompasses the possible effects of heterogeneity in soil moisture, land cover, and soil types together, but excludes topographic forcing. We attempt to answer the question: Under what conditions does the atmosphere exhibit a heightened sensitivity to surface variations and, therefore, surface heterogeneity? The simplicity of a single-column model is exploited to survey a range of surface conditions with the same large-scale atmospheric forcing to isolate the effect of the surface variability
encompasses the possible effects of heterogeneity in soil moisture, land cover, and soil types together, but excludes topographic forcing. We attempt to answer the question: Under what conditions does the atmosphere exhibit a heightened sensitivity to surface variations and, therefore, surface heterogeneity? The simplicity of a single-column model is exploited to survey a range of surface conditions with the same large-scale atmospheric forcing to isolate the effect of the surface variability
mean flow direction at the hub height, as required by the actuator disk model, is imposed using the algorithm presented in Sescu and Meneveau (2014) . We use LES and theoretical considerations to derive model equations for the effective roughness length—as an extension of the single-column analysis of Calaf et al. (2010 , 2011) to thermally stratified conditions—and to study the influence that a very large wind turbine array can have on the vertical turbulent momentum and heat fluxes. Both
mean flow direction at the hub height, as required by the actuator disk model, is imposed using the algorithm presented in Sescu and Meneveau (2014) . We use LES and theoretical considerations to derive model equations for the effective roughness length—as an extension of the single-column analysis of Calaf et al. (2010 , 2011) to thermally stratified conditions—and to study the influence that a very large wind turbine array can have on the vertical turbulent momentum and heat fluxes. Both
6°S, 8°E PIRATA mooring. With the single-column model (SCM) we can investigate processes active on very short time scales. This is impractical, if not impossible, with the three-dimensional model. With the coupled SCM, as opposed to the standalone version of the atmosphere and the ocean, we can investigate coupled air–sea processes, and the effect of the model bias in one component on the other component. In this work we first test the impact of the atmosphere on the ocean, and then focus on
6°S, 8°E PIRATA mooring. With the single-column model (SCM) we can investigate processes active on very short time scales. This is impractical, if not impossible, with the three-dimensional model. With the coupled SCM, as opposed to the standalone version of the atmosphere and the ocean, we can investigate coupled air–sea processes, and the effect of the model bias in one component on the other component. In this work we first test the impact of the atmosphere on the ocean, and then focus on
offshore wind energy production. The purpose of this study is to examine the impact on hub-height offshore wind 1-h forecasts that result from the estimation of a key parameter in the marine ABL using ensemble DA and a single-column model (SCM). Secondarily, we want to find out if estimation of this key parameter also improves the prediction of the momentum fluxes, which play an important role in ABL development. These findings will provide some indication of how much model error in the marine ABL is
offshore wind energy production. The purpose of this study is to examine the impact on hub-height offshore wind 1-h forecasts that result from the estimation of a key parameter in the marine ABL using ensemble DA and a single-column model (SCM). Secondarily, we want to find out if estimation of this key parameter also improves the prediction of the momentum fluxes, which play an important role in ABL development. These findings will provide some indication of how much model error in the marine ABL is
simulation. A single-column model with a typical environmental condition of low-level mixed-phase clouds over the Southern Ocean was used for the comparison. Utility of single-column models to capture low-level mixed-phase clouds was found in Klein et al. (2009) . We demonstrate how to improve the biases through sensitivity experiments, step by step. In section 2 , the single-column model and its settings are described. In section 3 , budget analysis and a series of sensitivity experiments are shown
simulation. A single-column model with a typical environmental condition of low-level mixed-phase clouds over the Southern Ocean was used for the comparison. Utility of single-column models to capture low-level mixed-phase clouds was found in Klein et al. (2009) . We demonstrate how to improve the biases through sensitivity experiments, step by step. In section 2 , the single-column model and its settings are described. In section 3 , budget analysis and a series of sensitivity experiments are shown
to understand the sensitivity of the result and its impact on a particular problem. This can be done by running a full forecast, through single-column model (SCM) experiments, with LES, or a combination thereof. Following this line of reasoning, we aim to focus our efforts on the scale-aware TKE eddy-diffusivity mass-flux (sa-TKE-EDMF) PBL ( Han and Bretherton 2019 ) scheme that is slated to replace the operational GFS PBL scheme ( Han et al. 2016 ) in version 16 (v16) of the Finite Volume
to understand the sensitivity of the result and its impact on a particular problem. This can be done by running a full forecast, through single-column model (SCM) experiments, with LES, or a combination thereof. Following this line of reasoning, we aim to focus our efforts on the scale-aware TKE eddy-diffusivity mass-flux (sa-TKE-EDMF) PBL ( Han and Bretherton 2019 ) scheme that is slated to replace the operational GFS PBL scheme ( Han et al. 2016 ) in version 16 (v16) of the Finite Volume
1. Introduction In recent decades, single-column atmospheric models, including cloud-resolving models and single-column versions of global climate models, have come into widespread use as a means to develop and test new parameterizations for use in global climate models. To compare with observations, these limited-domain models are often forced with an observed profile of large-scale ascent (equivalently, a profile of large-scale convergence). This approach, however, has its drawbacks. For
1. Introduction In recent decades, single-column atmospheric models, including cloud-resolving models and single-column versions of global climate models, have come into widespread use as a means to develop and test new parameterizations for use in global climate models. To compare with observations, these limited-domain models are often forced with an observed profile of large-scale ascent (equivalently, a profile of large-scale convergence). This approach, however, has its drawbacks. For
