Case Study Analysis of Submeso Motions in Moderately Complex Terrain of Central PA
Open Access
- Author:
- Hoover, Joshua Daniel
- Graduate Program:
- Meteorology
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- March 26, 2013
- Committee Members:
- Scott James Richardson, Thesis Advisor/Co-Advisor
- Keywords:
- submeso
complex terrain
stable boundary layer - Abstract:
- Transport and dispersion in the stable boundary layer (SBL) is a complicated atmospheric problem, especially in cases of weak mean wind (roughly < 2 ms-1 at 2 m above ground level (AGL)). In these cases, submeso motions (i.e., non-turbulent motions with horizontal scales of a few meters up to 2 km) of uncertain origin can dominate the shear-generation of turbulence and vertical mixing, as well as generate “meandering” horizontal motions and substantial horizontal dispersion in the SBL. It is thought that submeso motions in moderately complex terrain may be associated with internal gravity waves and terrain effects such as slope flows and cold pool interactions, or a combination of both. Data to confirm this hypothesis have been largely unavailable. To better understand the physical processes involved, we propose a method involving both observational and modeling techniques. Case studies of seven nights in late August and early September 2011 were chosen based on quiescent weather conditions and full availability of observational data from our central PA network of eight ground-based towers (ranging in height from 2-50 m AGL) and two SOund Detection And Ranging (SODAR) systems (with remotely observed wind and atmospheric stability measurements from 30 m up to ~250 m AGL). Observational data from this network have been continuously collected since 2007, generating a much larger data archive than most other studies of the SBL. Using numerical modeling results from the Penn State Realtime Weather Research and Forecasting (WRF) model at sub-kilometer (∆x=444 m) horizontal grid spacing in central PA, and archived wind and temperature data from the towers and sodars, we determine the dominant sources and types of submeso motions present and their effects on the surface flow. The combination of the high vertical resolution of observations and accompanying high-resolution, realtime, daily WRF model forecasts makes the Rock Springs network unique compared to other networks. The proximity of the Rock Springs network to complex terrain features leads to a large percentage of nocturnal periods that are characterized by very weak winds, even when compared to other SBL environments. Combining network observations and model forecasts with data on the synoptic conditions and the properties of the submeso motions, we hypothesize that local terrain and roughness elements (trees, buildings, etc.) can perturb the flow and therefore be responsible for the generation of submeso motions. Gravity waves and drainage flows appear to be dominant sources for many of the submeso fluctuations in the network. We classify each of the seven cases as very stable or weakly stable according to the percentage of bulk Richardson number values exceeding a transition value for each 12-hour case. The bulk Richardson number is constructed from 1-minute averaged wind and temperature observations. We find that submeso motions exist in all seven cases of this study, regardless of stability class. Furthermore, the stability classification chosen here is insufficient for predicting the occurrence or types of observed submeso motions. On the other hand, the characteristics of lower atmosphere synoptic conditions relative to the local terrain are much more important for determining submeso motions in our instrument network. In particular, we find that synoptic scale wind speed, wind direction, and cloud cover can influence characteristics of near-surface submeso motions. The case study results presented here can be used to enrich the community’s knowledge of the SBL and motivate the development of numerical parameterizations of unresolved submeso motions to improve the accuracy of plume dispersion models.