Stable boundary layers over mountainous terrain

Stable boundary layers (SBLs) are the least-understood group of boundary layers due to suppressed turbulence and interaction of myriad processes on different spatiotemporal scales that form its structure. In mountainous terrain SBLs are particularly important for pollutant dispersion, minimum temperature forecasting, road icing and fog formation, yet non- stationarity and intermittency, caused by poorly-understood organized non-turbulent motions, and the unknown influence of complex orography prevent the application of similarity theory and other concepts to SBLs in mountainous terrain, and lead to poor forecast skill of numerical models. The interaction of processes on different scales has so far not been systematically studied in mountainous terrain over longer periods of time, nor in the context of orographic influences. Understanding these interactions and identifying the dominant forcings of near-surface submeso and mesoscale motions will help develop better parameterizations and improve forecasts in SBLs in mountainous terrain. The premise of this research is that (i) motions on all scales are present in SBLs in mountainous terrain, (ii) they contribute significantly to the total exchange of momentum, heat and mass and (iii) are to a part related to orographic scales themselves. In order to study interactions between processes on different scales in mountainous SBLs we use a unique multi year dataset from a network of near-surface turbulent measurements in the Inn valley, Austria (valley floor to mountain top). First we will examine the general SBL turbulence structure in the Inn Valley, focusing on identifying areas with non-stationary, intermittent conditions, or with continuous mixing, and locations where submeso motions bridge the spectral gap. Secondly we will focus on identifying non-turbulent motion at different temporal scales, by detecting the signature of these motions in time series with wavelets and a novel method for event detection and classification. Characteristics of these organized motions will then be analyzed so as to determine common types at each scale, and their importance in contributing to the total flux at each station. We will identify how these motions are related to orographic forcing. Physical mechanisms and possible forcings inducing these organized motions will be examined so as to determine if it is possible to parameterize the influence of these non-turbulent organized motions on SBL in mountainous terrain and develop a similarity framework. Finally, two field campaigns will be conducted with additional spatially distributed network of stations and remote sensing instrumentation. We will use this fine-scale dataset to test and challenge the hypotheses obtained from the previous components of the project and study the spatiotemporal characteristics of submeso motions in more detail and identify the physical mechanisms causing them. Particular stress will be placed on the influence of orographic scales (slope angle, scale of local and mesoscale orographic features) on the submeso motions.

Turbulence is one of the great remaining challenges in physics and mathematics. It controls how energy, mass and momentum are transported between the Earth surface and the atmosphere. Atmospheric turbulence affects phenomena as diverse as the climate, weather systems, strength of tornadoes, hurricanes and downslope windstorms, air pollution, agriculture as well as glacial melt and runoff. Stable boundary layers are the least- understood group of boundary layers. They form during nighttime or over cold surfaces when the radiative balance is negative. Stable boundary layers are characterised by suppressed turbulence and significant interaction with motions on spatio-temporal scales larger than turbulence. Over mountainous terrain, understanding turbulence is particularly challenging because of horizontal heterogeneity of the mountain surface and the influence of terrain- induced flows on the near-surface turbulence structure. This lack of understanding of complex-terrain turbulence and the absence of the appropriate statistical representation of turbulence effects in mountainous terrain leads to a significant uncertainty in numerical weather prediction and other applications over mountainous areas. In this study turbulence structure over terrain of various complexity and surface characteristics was investigated. We used data from measurement sites ranging from flat to highly complex mountainous terrain, from semi-desert to glaciers. It was shown that turbulence characteristics are strongly influenced by the shape of turbulence, through the so-called anisotropy. Turbulence anisotropy on the other hand depends strongly on how turbulence is produced, i.e. whether the atmosphere is stable or unstable, and if there is large change of wind speed with height. Stably stratified turbulence in particular is significantly deformed under conditions when the wind speed is weak and the motions on scales larger than turbulence strongly influence turbulence. Such deformed turbulence is also more persistent, and does not conform to known statistical representations. During the unstable daytime conditions on the other hand, turbulence will be least deformed (isotropic) when wind speed is weak and buoyancy is a dominant source of turbulence. It was shown that periods that have the same type of anisotropy have similar behaviour irrespective of the complexity of the underlying surface (slope angle, ice surface vs. debris covered). Therefore when anisotropy is taken into account the statistical characteristics of turbulence from all complex mountainous sites show the same relationships as turbulence over flat-terrain. This can in the future help develop a universal statistical representation of turbulence in numerical models that has the potential to significantly improve numerical weather models, hydrological applications, pollution modelling, glacier mass balance modelling, foehn prediction, precipitation forecasts etc.