No 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.

Two formulations of a nonlinear turbulence subfilter-scale (SFS) stress model were implemented into the Advanced Research Weather Research and Forecasting model (ARW-WRF) version 3.0 for improved largeeddy simulation performance. The new models were evaluated against the WRF model's standard Smagorinsky and 1.5-order turbulence kinetic energy (TKE) linear eddy-viscosity SFS stress models in simulations of geostrophically forced, neutral boundary layer flow over both flat terrain and a shallow, symmetric transverse ridge. Comparisons of simulation results with similarity profiles indicate that the nonlinear models significantly improve agreement with the expected profiles near the surface, reducing the overprediction of near-surface stress characteristic of linear eddy-viscosity models with no near-wall damping. Comparisons of simulations conducted using different mesh sizes indicate that the nonlinear model simulations at coarser resolutions agree more closely with the higher-resolution results than corresponding lower-resolution simulations using the standard WRF SFS stress models. The nonlinear models produced flows featuring a broader range of eddy sizes, with less spectral power at lower frequencies and more spectral power at higher frequencies. In simulated flow over the transverse ridge, distributions of flow separation and reversal near the surface simulated at higher resolution were likewise better depicted in coarser-resolution simulations using the nonlinear models.

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011), the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems, one vertically profiling and another operated over a variety of scanning modes, were utilized to obtain forcing for the simulations, and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20 W m−2 and 100 W m−2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011, whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. Validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

One-way concurrent nesting within the Weather Research and Forecasting Model (WRF) is examined for conducting large-eddy simulations (LES) nested within mesoscale simulations. Wind speed, spectra, and resolved turbulent stresses and turbulence kinetic energy from the nested LES are compared with data from nonnested simulations using periodic lateral boundary conditions. Six different subfilter-scale (SFS) stress models are evaluated using two different nesting strategies under geostrophically forced flow over both flat and hilly terrain. Neutral and weakly convective conditions are examined. For neutral flow over flat terrain, turbulence appears on the nested LES domains only when using the two dynamic SFS stress models. The addition of small hills and valleys (wavelengths of 2.4 km and maximum slopes of ± 10°) yields small improvements, with all six models producing some turbulence on nested domains. Weak convection (surface heat fluxes of 10 W m−2) further accelerates the development of turbulence on all nested domains. However, considerable differences in key parameters are observed between the nested LES domains and their nonnested counterparts. Nesting of a finer LES within a coarser LES provides superior results to using only one nested LES domain. Adding temperature and velocity perturbations near the inlet planes of nested domains shows promise as an easy-to-implement method to accelerate turbulence generation and improve its accuracy on nested domains.