UC Berkeley

Microscale atmospheric simulations of the planetary boundary layer are frequently used for wind energy forecasting, emergency response, mountain meteorology, air pollution modeling, and numerous other applications involving atmospheric flows over complex terrain. These models are typically configured using local observations and are limited to resolving only microscale flow features. Mesoscale meteorology, regional influences, and large-scale turbulence are not resolved with the traditional microscale modeling techniques. This dissertation details a series of developments to the Weather Research and Forecasting (WRF) model that enable mesoscale to microscale (i.e. multiscale) simulations. These multiscale simulations dynamically downscale meteorological conditions through a series of nested domains with increasingly high resolution, which allows mesoscale meteorology, regional influence, and large-scale flow features to influence microscale simulations.

Over steep terrain, the WRF model develops numerical errors that are due to grid deformation of the terrain-following coordinates. An alternative gridding technique, the immersed boundary method (IBM), has been implemented into the WRF model (Lundquist et al. 2012; Bao et al. 2018). Use of an IBM allows for microscale simulations over highly complex terrain (i.e. urban or mountainous). Here, an IBM and the WRF model’s grid-nesting framework have been modified to seamlessly work together, which allows for a microscale large-eddy simulation over complex terrain with an IBM to be nested within a traditional mesoscale WRF simulation (Wiersema et al. 2020). Additionally, grid configurations are controlled using the vertical grid nesting method of Daniels et al. (2016) and turbulence development at intermediate resolutions is improved using the cell perturbation method of Munoz-Esparza et al. (2015). Multiscale simulations are extremely challenging to configure due to the sensitivity of each nested domain to its configuration and to the configuration of its parent domain(s). This dissertation also begins to investigate the model sensitivity to grid resolution and surface boundary condition, which is integral information for modelers configuring the nested domains of future multiscale simulations.

Multiscale simulations are demonstrated for the prediction of transport and mixing of a tracer gas (SF6) released in the central business district of Oklahoma City during the Joint Urban 2003 field campaign. The simulations use either 5 or 6 nested domains with horizontal resolutions that range from several kilometers for the outermost domain to 2~m for the innermost domain. The multiscale simulations are compared with microscale-only simulations and with observations of wind speed, wind direction, and SF6 concentrations. The microscale-only simulations use idealized lateral boundary conditions and are configured using local meteorological observations from the field campaign. The multiscale simulation, which is configured independent of local observations, shows similar model skill predicting wind speed and wind direction, and improved skill predicting SF6 concentrations and turbulence kinetic energy when compared with the microscale-only simulations. Additionally, the multiscale simulation includes the effects of large-scale flow features and turbulence that the microscale-only simulations are incapable of resolving, which is shown to have a dramatic effect on predictions of transport and mixing. The analysis of simulations in this dissertation demonstrates the potential for multiscale simulations to improve predictions of transport and mixing over highly complex terrain and enable microscale simulations where local observations are not available.