UC Berkeley

Traditional weather models struggle to resolve the details of complex terrain and the strongly stable stratification often observed in near surface temperature inversions. Conversely, traditional engineering computational fluid dynamics codes often use high resolution grid meshes, but do not include forcing from synoptic scale weather. As computational power grows, a new class of models is emerging. These are nested large-eddy simulations (LES), which are both highly resolved and include large scale weather forcing. In this case, high resolution implies grid meshes that are fine enough to resolve the most energetic eddies in the atmospheric boundary layer. These high resolution domains are nested, i.e. forced at the lateral boundaries, by coarser mesoscale models. The role of nested large-eddy simulation in the study of atmospheric boundary layer is twofold. First, trusted LES data allow the study of important dynamics with all the relevant forcing of real flow, but without dense observation networks. Though observations are still critical to the validation of these models, in some cases, as in fire weather, sufficiently detailed observations are very difficult to carry out due to practical concerns. In other cases, simulation is simply a less expensive means to achieve higher resolution data than even the densest sensor network can provide. In this sense, LES is a valuable tool for the research community. For the forecasting community, however, LES cannot be used in place of coarser models given current computational power. As prediction is an ultimate goal of weather modeling, we turn to the second role of LES, the generation of subgrid parameterizations for use in coarse models that can be run for real-time forecasting. The dual purpose of LES, the direct study of atmospheric boundary layer dynamics and the development of parameterizations for mesoscale models, motivate three investigations into the dynamics of the atmospheric boundary layer presented here. Each study conducts LES with the Weather Research and Forecasting (WRF) model, an advanced numerical weather prediction (NWP) code. Unlike traditional NWP or engineering codes, these simulations include both complex terrain as well as realistic weather forcing to advance our understanding of atmospheric boundary layer dynamics and the LES technique itself. The first project is conducted as part of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program. During the field campaign of the MATERHORN, large temperature fluctuations were observed on the slope of Granite Peak, Utah, which partially encloses a cold-air pool in the east basin. These flow features are able to be resolved using LES within the WRF model with ∆x = 100 m, allowing accurate representation of lee vortices with horizontal length scale of O(1 km). At this resolution, terrain slopes become quite steep, and some model warm biases remain in the east basin due to limits on terrain-following coordinates that prevent the model from fully resolving drainage flows with this steep terrain. A new timestep limit for the WRF model related to these steep slopes is proposed. In addition, the initialization of soil moisture is adjusted by drying the shallowest layer to assist the formation of a cold pool in the LES. These real case simulations compare well to observations and also to previously published simulations using idealized configurations to study similar phenomena. For instance, the values of non-dimensional mountain height, which characterize flow regimes in idealized studies, are similar in the real case. With their predictive capabilities established, these non-dimensional numbers are likely to provide the future basis for parameterization of the lee vortices which cannot be resolved by NWP models. The second study addresses a challenge to simulating turbulent flow in multiscale atmospheric applications, the efficient generation of resolved turbulence motions over an area of interest. One approach is to apply small perturbations to flow variables near the inflow planes of turbulence-resolving simulation domains nested within larger mesoscale domains. While this approach has been examined in numerous idealized and simple terrain cases, its efficacy in complex terrain environments has not yet been fully explored. Here, we examine the benefits of the stochastic cell perturbation method (CPM) over real complex terrain using data from the 2017 Perdigão field campaign, conducted in an approximately 2-km wide valley situated between two nearly parallel ridges. Following a typical configuration for multiscale simulation using nested domains within the WRF model to downscale from a mesoscale to an LES, we apply the CPM on a domain with a relatively coarse LES mesh spacing of 150 m. LES at this resolution often generates spurious coherent structures under unstable atmospheric conditions with moderate mean wind speeds. We examine the impacts of the CPM on the representation of turbulence within the nested LES domain under moderate mean flow conditions in three different stability regimes: weakly convective, strongly convective, and weakly stable. In addition, two different resolutions of the underlying terrain are used to explore the role of the complex topography itself in generating turbulent structures. We demonstrate that the CPM improves the representation of turbulence within the LES domains, relative to the use of high-resolution complex terrain alone. During the convective conditions, the CPM improves the rate at which smaller-scales of turbulence form, while also accelerating the attenuation of the spurious numerically-generated roll structures near the inflow boundary. During stable conditions, the coarse mesh spacing of the LES used herein was insufficient to maintain resolved turbulence using CPM as the flow develops downstream, highlighting the need for yet higher resolution under even weakly stable conditions. The CPM was particularly efficient during the evening transition period. A final study investigates fundamental controls on drainage flow dynamics. Historically called katabatic flow, drainage flow is buoyancy driven and directed downslope in response to surface cooling typical of the nocturnal period. Analogous upslope flow due to surface heating during the day is often called anabatic flow. A fundamental question is at what time during the evening transition does the slope wind system switch from anabatic to drainage flow. A natural benchmark for this transition is sunset, but the presence of terrain results in shadows cast onto east-facing slopes which can complicate this analysis. To guide this analysis, functional forms for the time of the shadow front propagation are presented for an idealized terrain shape used for an LES in WRF. Even with idealized topography, the present LES are significantly more advanced than previous models used to investigate idealized drainage flow, which prescribed surface cooling rather than prognosticating the cooling in response to the diurnal cycle of insolation and the characteristics of the surface and soil types, as done here. This complexity allows for potentially counterintuitive results, such as the onset of drainage flow occurring on the shadow-cast eastern slopes later than on the sunnier western slopes due to convective structures which persist after sunset. Despite these complications during the development of drainage flow in the evening, there are periods during the night when analytical solutions compare well to the LES solution of drainage flow profiles. A novel analytical solution also explains a dependence on the angle of the slope found in observation data but missing in the original (Prandtl 1942) solution by replacing the traditional Dirichlet with a Neumann boundary condition. The favorable comparison between analytical solutions and results from the high resolution numerical model are a first step towards the ultimate parameterization of drainage flow in coarser NWP models.