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- Author or Editor: Jeffrey D. Mirocha x
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Abstract
Because accurate modeling of atmospheric flows in urban environments requires sophisticated representation of complex urban geometries, much work has been devoted to treatment of the urban surface. However, the importance of the larger-scale flow impinging upon the urban complex to the flow, transport, and dispersion within it and downwind has received less attention. Building-resolving computational fluid dynamics (CFD) models are commonly employed to investigate interactions between the flow and three-dimensional structures that make up the urban environment; however, such models are typically forced with simplified boundary conditions that fail to include important regional-scale phenomena that can strongly influence the flow within the urban complex and downwind. This paper investigates the interaction of an important and frequently occurring regional-scale phenomenon, the nocturnal low-level jet (LLJ), with urban-scale turbulence and dispersion in Oklahoma City, Oklahoma, using data from the Joint Urban 2003 (JU2003) field experiment. Two simulations of nocturnal tracer release experiments from JU2003 using Lawrence Livermore National Laboratory’s Finite-Element Model in 3 Dimensions and Massively Parallelized (FEM3MP) CFD model yield differing levels of agreement with the observations in wind speed, turbulence kinetic energy (TKE), and concentration profiles in the urban wake, approximately 750 m downwind of the central business district. Profiles of several observed turbulence parameters at this location indicate characteristics of both bottom-up and top-down boundary layers during each of the experiments. These data are consistent with turbulence production due to at least two sources, the complex flow structures of the urban area and the region of strong vertical wind shear occurring beneath the LLJs present each night. Strong LLJs occurred each night, but their structures varied considerably, resulting in significant differences in the magnitudes of the turbulence parameters observed during the two experiments. Because FEM3MP was forced only with an upwind velocity profile that did not adequately represent the LLJ, the downward propagation of TKE observed during the experiments was absent from the simulations. As such, the differing levels of agreement between the simulations and observations during the two experiments can, in part, be explained by their exclusion of this important larger-scale influence. The ability of the Weather Research and Forecast Model (WRF) to simulate accurate velocity fields during each night was demonstrated, and the use of regional-scale simulation data was identified as a promising approach for representing the effects of important regional-scale phenomena such as the LLJ on urban-scale simulations.
Abstract
Because accurate modeling of atmospheric flows in urban environments requires sophisticated representation of complex urban geometries, much work has been devoted to treatment of the urban surface. However, the importance of the larger-scale flow impinging upon the urban complex to the flow, transport, and dispersion within it and downwind has received less attention. Building-resolving computational fluid dynamics (CFD) models are commonly employed to investigate interactions between the flow and three-dimensional structures that make up the urban environment; however, such models are typically forced with simplified boundary conditions that fail to include important regional-scale phenomena that can strongly influence the flow within the urban complex and downwind. This paper investigates the interaction of an important and frequently occurring regional-scale phenomenon, the nocturnal low-level jet (LLJ), with urban-scale turbulence and dispersion in Oklahoma City, Oklahoma, using data from the Joint Urban 2003 (JU2003) field experiment. Two simulations of nocturnal tracer release experiments from JU2003 using Lawrence Livermore National Laboratory’s Finite-Element Model in 3 Dimensions and Massively Parallelized (FEM3MP) CFD model yield differing levels of agreement with the observations in wind speed, turbulence kinetic energy (TKE), and concentration profiles in the urban wake, approximately 750 m downwind of the central business district. Profiles of several observed turbulence parameters at this location indicate characteristics of both bottom-up and top-down boundary layers during each of the experiments. These data are consistent with turbulence production due to at least two sources, the complex flow structures of the urban area and the region of strong vertical wind shear occurring beneath the LLJs present each night. Strong LLJs occurred each night, but their structures varied considerably, resulting in significant differences in the magnitudes of the turbulence parameters observed during the two experiments. Because FEM3MP was forced only with an upwind velocity profile that did not adequately represent the LLJ, the downward propagation of TKE observed during the experiments was absent from the simulations. As such, the differing levels of agreement between the simulations and observations during the two experiments can, in part, be explained by their exclusion of this important larger-scale influence. The ability of the Weather Research and Forecast Model (WRF) to simulate accurate velocity fields during each night was demonstrated, and the use of regional-scale simulation data was identified as a promising approach for representing the effects of important regional-scale phenomena such as the LLJ on urban-scale simulations.
Abstract
To facilitate multiscale simulation using the Weather Research and Forecasting Model, vertical mesh refinement for one-way concurrent nested simulation was recently introduced. Grid refinement in the vertical dimension removes the requirement of different grid aspect ratios on the bounding versus the nested domain, such that results from refinement are in the horizontal directions only, and thereby can also reduce numerical errors on the bounding domain arising from large aspect ratios in the presence of complex terrain. Herein, the impacts of vertical grid refinement on the evolving downstream flow in nested large-eddy simulations are evaluated in relation to other model configuration choices, including turbulence subfilter-scale (SFS) stress models, mesh configuration, and alternative methods for calculating several near-surface flow parameters. Although vertical nesting requires coarsening of the vertical grid on the bounding domain, leading to a smaller range of resolved turbulence scales in the nest’s lateral boundary conditions, parameter values within the nested domains are generally only minimally impacted, relative to nesting using the same vertical grid on each domain. Two dynamic SFS models examined herein generally improved the simulated mean wind speed, turbulence kinetic energy, stresses and spectra, on both domains, and accelerated equilibration rates within nested domains, relative to two constant coefficient models. A new method of extrapolating horizontal velocity components to near-surface locations at nested domain lateral boundaries, and a correction to the calculation of deformation elements near the surface, are each shown to slightly alter the mean parameter values, yet only minimally impact equilibration rates within the nested domain.
Abstract
To facilitate multiscale simulation using the Weather Research and Forecasting Model, vertical mesh refinement for one-way concurrent nested simulation was recently introduced. Grid refinement in the vertical dimension removes the requirement of different grid aspect ratios on the bounding versus the nested domain, such that results from refinement are in the horizontal directions only, and thereby can also reduce numerical errors on the bounding domain arising from large aspect ratios in the presence of complex terrain. Herein, the impacts of vertical grid refinement on the evolving downstream flow in nested large-eddy simulations are evaluated in relation to other model configuration choices, including turbulence subfilter-scale (SFS) stress models, mesh configuration, and alternative methods for calculating several near-surface flow parameters. Although vertical nesting requires coarsening of the vertical grid on the bounding domain, leading to a smaller range of resolved turbulence scales in the nest’s lateral boundary conditions, parameter values within the nested domains are generally only minimally impacted, relative to nesting using the same vertical grid on each domain. Two dynamic SFS models examined herein generally improved the simulated mean wind speed, turbulence kinetic energy, stresses and spectra, on both domains, and accelerated equilibration rates within nested domains, relative to two constant coefficient models. A new method of extrapolating horizontal velocity components to near-surface locations at nested domain lateral boundaries, and a correction to the calculation of deformation elements near the surface, are each shown to slightly alter the mean parameter values, yet only minimally impact equilibration rates within the nested domain.
Abstract
Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.
Abstract
Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.
Abstract
While numerous modeling studies have focused on the interaction of ocean surface waves with the atmospheric boundary layer, most employ idealized waves that are either monochromatic or synthetically generated from a theoretical wave spectrum, and the atmospheric solvers are typically incompressible. To study wind–wave coupling in real-world scenarios, a model that can simulate both realistic meteorological and wave conditions is necessary. In this paper we describe the implementation of a moving bottom boundary condition into the Weather Research and Forecasting Model for large-eddy simulation applications. We first describe the moving bottom boundary conditions within WRF’s pressure-based vertical coordinate system. We then validate our code with idealized test cases that have analytical solutions, including flow over a monochromatic wave with and without viscosity. Finally, we present results from turbulent flows over a moving monochromatic wave with different wave ages, and demonstrate satisfactory agreement of the wave growth rate with results from the literature. We also compare atmospheric stress and wind parameters from two physically equivalent cases. The first specifies a wind moving in the same direction as a propagating wave, while the second involves a stationary wave with the wind adjusted such that the wind relative to the wave is the same as in the first case. Results indicate that the velocity and Reynolds stress profiles for the two cases match, further validating the moving bottom implementation.
Abstract
While numerous modeling studies have focused on the interaction of ocean surface waves with the atmospheric boundary layer, most employ idealized waves that are either monochromatic or synthetically generated from a theoretical wave spectrum, and the atmospheric solvers are typically incompressible. To study wind–wave coupling in real-world scenarios, a model that can simulate both realistic meteorological and wave conditions is necessary. In this paper we describe the implementation of a moving bottom boundary condition into the Weather Research and Forecasting Model for large-eddy simulation applications. We first describe the moving bottom boundary conditions within WRF’s pressure-based vertical coordinate system. We then validate our code with idealized test cases that have analytical solutions, including flow over a monochromatic wave with and without viscosity. Finally, we present results from turbulent flows over a moving monochromatic wave with different wave ages, and demonstrate satisfactory agreement of the wave growth rate with results from the literature. We also compare atmospheric stress and wind parameters from two physically equivalent cases. The first specifies a wind moving in the same direction as a propagating wave, while the second involves a stationary wave with the wind adjusted such that the wind relative to the wave is the same as in the first case. Results indicate that the velocity and Reynolds stress profiles for the two cases match, further validating the moving bottom implementation.
Abstract
As model grid resolutions move from the mesoscale to the microscale, turbulent structures represented in atmospheric boundary layer simulations change dramatically. At intermediate resolutions, the so-called gray zone, turbulent motions are not resolved accurately, posing a challenge to numerical simulations. The representation of turbulence is also highly sensitive to the choice of closure model. Here, we examine explicit filtering and reconstruction in the gray zone as a technique to better represent atmospheric turbulence. The convective boundary layer is simulated using the Weather Research and Forecasting (WRF) Model with horizontal resolutions ranging from 25 m to 1 km. Four large-eddy simulation (LES) turbulence models are considered: the Smagorinsky model, the TKE-1.5 model, and two versions of the dynamic reconstruction model (DRM). The models are evaluated by their ability to produce consistent mean potential temperature profiles, heat and momentum fluxes, velocity fields, and turbulent kinetic energy spectra as the grids become coarser. The DRM, a mixed model that uses an explicit filtering and reconstruction technique to account for resolvable subfilter-scale (RSFS) stresses, performs very well at resolutions of 500 m and 1 km without any special tuning, whereas the Smagorinsky and TKE-1.5 models produce heavily grid-dependent results.
Abstract
As model grid resolutions move from the mesoscale to the microscale, turbulent structures represented in atmospheric boundary layer simulations change dramatically. At intermediate resolutions, the so-called gray zone, turbulent motions are not resolved accurately, posing a challenge to numerical simulations. The representation of turbulence is also highly sensitive to the choice of closure model. Here, we examine explicit filtering and reconstruction in the gray zone as a technique to better represent atmospheric turbulence. The convective boundary layer is simulated using the Weather Research and Forecasting (WRF) Model with horizontal resolutions ranging from 25 m to 1 km. Four large-eddy simulation (LES) turbulence models are considered: the Smagorinsky model, the TKE-1.5 model, and two versions of the dynamic reconstruction model (DRM). The models are evaluated by their ability to produce consistent mean potential temperature profiles, heat and momentum fluxes, velocity fields, and turbulent kinetic energy spectra as the grids become coarser. The DRM, a mixed model that uses an explicit filtering and reconstruction technique to account for resolvable subfilter-scale (RSFS) stresses, performs very well at resolutions of 500 m and 1 km without any special tuning, whereas the Smagorinsky and TKE-1.5 models produce heavily grid-dependent results.
Abstract
A canopy model framework is implemented in the Weather Research and Forecasting Model to improve the accuracy of large-eddy simulations (LES) of the atmospheric boundary layer (ABL). The model includes two options that depend on the scale of surface roughness elements. A resolved canopy model, typically used to model flow through vegetation canopies, is employed when roughness elements are resolved by the vertical LES grid. In the case of unresolved roughness, a modified “pseudocanopy model” is developed to distribute drag over a shallow layer above the surface. Both canopy model options are validated against idealized test cases in neutral stability conditions and are shown to improve surface layer velocity profiles relative to simulations employing Monin–Obukhov similarity theory (MOST), which is commonly used as a surface boundary condition in ABL models. Use of the canopy model framework also leads to increased levels of resolved turbulence kinetic energy and turbulent stresses. Because LES of the ABL has a well-known difficulty recovering the expected logarithmic velocity profile (log law) in the surface layer, particular focus is placed on using the pseudocanopy model to alleviate this issue over a range of model configurations. Tests with varying surface roughness values, LES closures, and grid aspect ratios confirm that the pseudocanopy model generally improves log-law agreement relative to simulations that employ a standard MOST boundary condition. The canopy model framework thus represents a low-cost, easy-to-implement method for improving LES of the ABL.
Abstract
A canopy model framework is implemented in the Weather Research and Forecasting Model to improve the accuracy of large-eddy simulations (LES) of the atmospheric boundary layer (ABL). The model includes two options that depend on the scale of surface roughness elements. A resolved canopy model, typically used to model flow through vegetation canopies, is employed when roughness elements are resolved by the vertical LES grid. In the case of unresolved roughness, a modified “pseudocanopy model” is developed to distribute drag over a shallow layer above the surface. Both canopy model options are validated against idealized test cases in neutral stability conditions and are shown to improve surface layer velocity profiles relative to simulations employing Monin–Obukhov similarity theory (MOST), which is commonly used as a surface boundary condition in ABL models. Use of the canopy model framework also leads to increased levels of resolved turbulence kinetic energy and turbulent stresses. Because LES of the ABL has a well-known difficulty recovering the expected logarithmic velocity profile (log law) in the surface layer, particular focus is placed on using the pseudocanopy model to alleviate this issue over a range of model configurations. Tests with varying surface roughness values, LES closures, and grid aspect ratios confirm that the pseudocanopy model generally improves log-law agreement relative to simulations that employ a standard MOST boundary condition. The canopy model framework thus represents a low-cost, easy-to-implement method for improving LES of the ABL.
Abstract
Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Herein, a procedure permitting vertical nesting for one-way concurrent simulation is developed and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.
Abstract
Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Herein, a procedure permitting vertical nesting for one-way concurrent simulation is developed and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.
Abstract
This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment.
Significance Statement
Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.
Abstract
This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment.
Significance Statement
Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.
Abstract
Topographic effects on radiation, including both topographic shading and slope effects, are included in the Weather Research and Forecasting (WRF) Model, and here they are made compatible with the immersed boundary method (IBM). IBM is an alternative method for representing complex terrain that reduces numerical errors over sloped terrain, thus extending the range of slopes that can be represented in WRF simulations. The implementation of topographic effects on radiation is validated by comparing land surface fluxes, as well as temperature and velocity fields, between idealized WRF simulations both with and without IBM. Following validation, the topographic shading implementation is tested in a semirealistic simulation of flow over Granite Mountain, Utah, where topographic shading is known to affect downslope flow development in the evening. The horizontal grid spacing is 50 m and the vertical grid spacing is approximately 8–27 m near the surface. Such a case would fail to run in WRF with its native terrain-following coordinates because of large local slope values reaching up to 55°. Good agreement is found between modeled surface energy budget components and observations from the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program at a location on the east slope of Granite Mountain. In addition, the model captures large spatiotemporal inhomogeneities in the surface sensible heat flux that are important for the development of thermally driven flows over complex terrain.
Abstract
Topographic effects on radiation, including both topographic shading and slope effects, are included in the Weather Research and Forecasting (WRF) Model, and here they are made compatible with the immersed boundary method (IBM). IBM is an alternative method for representing complex terrain that reduces numerical errors over sloped terrain, thus extending the range of slopes that can be represented in WRF simulations. The implementation of topographic effects on radiation is validated by comparing land surface fluxes, as well as temperature and velocity fields, between idealized WRF simulations both with and without IBM. Following validation, the topographic shading implementation is tested in a semirealistic simulation of flow over Granite Mountain, Utah, where topographic shading is known to affect downslope flow development in the evening. The horizontal grid spacing is 50 m and the vertical grid spacing is approximately 8–27 m near the surface. Such a case would fail to run in WRF with its native terrain-following coordinates because of large local slope values reaching up to 55°. Good agreement is found between modeled surface energy budget components and observations from the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program at a location on the east slope of Granite Mountain. In addition, the model captures large spatiotemporal inhomogeneities in the surface sensible heat flux that are important for the development of thermally driven flows over complex terrain.
Abstract
Complete models of the hydrologic cycle have gained recent attention as research has shown interdependence between the coupled land and energy balance of the subsurface, land surface, and lower atmosphere. PF.WRF is a new model that is a combination of the Weather Research and Forecasting (WRF) atmospheric model and a parallel hydrology model (ParFlow) that fully integrates three-dimensional, variably saturated subsurface flow with overland flow. These models are coupled in an explicit, operator-splitting manner via the Noah land surface model (LSM). Here, the coupled model formulation and equations are presented and a balance of water between the subsurface, land surface, and atmosphere is verified. The improvement in important physical processes afforded by the coupled model using a number of semi-idealized simulations over the Little Washita watershed in the southern Great Plains is demonstrated. These simulations are initialized with a set of offline spinups to achieve a balanced state of initial conditions. To quantify the significance of subsurface physics, compared with other physical processes calculated in WRF, these simulations are carried out with two different surface spinups and three different microphysics parameterizations in WRF. These simulations illustrate enhancements to coupled model physics for two applications: water resources and wind-energy forecasting. For the water resources example, it is demonstrated how PF.WRF simulates explicit rainfall and water storage within the basin and runoff. Then the hydrographs predicted by different microphysics schemes within WRF are compared. Because soil moisture is expected to impact boundary layer winds, the applicability of the model to wind-energy applications is demonstrated by using PF.WRF and WRF simulations to provide estimates of wind and wind shear that are useful indicators of wind-power output.
Abstract
Complete models of the hydrologic cycle have gained recent attention as research has shown interdependence between the coupled land and energy balance of the subsurface, land surface, and lower atmosphere. PF.WRF is a new model that is a combination of the Weather Research and Forecasting (WRF) atmospheric model and a parallel hydrology model (ParFlow) that fully integrates three-dimensional, variably saturated subsurface flow with overland flow. These models are coupled in an explicit, operator-splitting manner via the Noah land surface model (LSM). Here, the coupled model formulation and equations are presented and a balance of water between the subsurface, land surface, and atmosphere is verified. The improvement in important physical processes afforded by the coupled model using a number of semi-idealized simulations over the Little Washita watershed in the southern Great Plains is demonstrated. These simulations are initialized with a set of offline spinups to achieve a balanced state of initial conditions. To quantify the significance of subsurface physics, compared with other physical processes calculated in WRF, these simulations are carried out with two different surface spinups and three different microphysics parameterizations in WRF. These simulations illustrate enhancements to coupled model physics for two applications: water resources and wind-energy forecasting. For the water resources example, it is demonstrated how PF.WRF simulates explicit rainfall and water storage within the basin and runoff. Then the hydrographs predicted by different microphysics schemes within WRF are compared. Because soil moisture is expected to impact boundary layer winds, the applicability of the model to wind-energy applications is demonstrated by using PF.WRF and WRF simulations to provide estimates of wind and wind shear that are useful indicators of wind-power output.
