The exchange of heat, momentum, and mass in the atmosphere over mountainous terrain is controlled by synoptic-scale dynamics, thermally driven mesoscale circulations, and turbulence. This article reviews the key challenges relevant to the understanding of exchange processes in the mountain boundary layer and outlines possible research priorities for the future. The review describes the limitations of the experimental study of turbulent exchange over complex terrain, the impact of slope and valley breezes on the structure of the convective boundary layer, and the role of intermittent mixing and wave–turbulence interaction in the stable boundary layer. The interplay between exchange processes at different spatial scales is discussed in depth, emphasizing the role of elevated and ground-based stable layers in controlling multi-scale interactions in the atmosphere over and near mountains. Implications of the current understanding of exchange processes over mountains towards the improvement of numerical weather prediction and climate models are discussed, considering in particular the representation of surface boundary conditions, the parameterization of sub-grid-scale exchange, and the development of stochastic perturbation schemes.

The theoretical treatment of turbulence is largely based on the assumption of horizontally homogeneous and flat underlying surfaces. Correspondingly, approaches developed over the years to measure turbulence statistics in order to test this theoretical understanding or to provide model input, are also largely based on the same assumption of horizontally homogeneous and flat terrain. Here we discuss aspects of turbulence measurements that require special attention in mountainous terrain. We especially emphasize the importance of data quality (flux corrections, data quality assessment, uncertainty estimates) and address the issues of coordinate systems and different post-processing options in mountainous terrain. The appropriate choice of post-processing methods is then tested based on local scaling arguments. We demonstrate that conclusions drawn from turbulence measurements obtained in mountainous terrain are rather sensitive to these post-processing choices and give suggestions as to those that are most appropriate.

Monin-Obukhov similarity theory (MOST) forms the basis for parametrizations of turbulent exchange in virtually all numerical models of atmospheric flows. Yet, its limitations to flat and horizontally homogeneous terrain have plagued the theory since its inception. Here we present a first generalized extension of MOST based on the inclusion of turbulence anisotropy as an additional nondimensional term. This novel theory developed based on an unprecedented ensemble of complex atmospheric turbulence datasets covering flat to mountainous terrain, is shown to be valid in conditions in which MOST fails and thus paves the way to a better understanding of complex turbulence.

The flow and turbulence structure in the atmospheric boundary layer over complex mountainous terrain determines Earth–atmosphere interaction, that is, the exchange of energy, mass, and momentum between the surface over such terrain and the free atmosphere. Numerical models for weather and climate, even when operated at high or very high grid resolution, are known to be deficient, leading to inaccurate local forecasts (weather) or scenarios (climate). The nature and reasons for these deficiencies, however, are difficult to assess because systematic and long-term combined observational/modeling studies in mountainous terrain are missing. The Innsbruck Box (i-Box) project aims at filling in this gap through a network of long-term turbulence sites in truly complex terrain, complemented by similarly continuous (surface based) remote sensing and numerical modeling at high to highest [i.e., large-eddy simulation (LES)] resolution. This contribution details the i-Box approach, the experimental design, and available data, as well as the numerical modeling strategy. The first scientific highlights are presented to illustrate the potential of the i-Box data pool and possible future directions.

Turbulence data from the CASES‐99 field experiment, over comparatively horizontally homogeneous and flat terrain, are separated based on the anisotropy of the Reynolds stress tensor (into isotropic, two‐component axisymmetric and one‐component turbulence) and flux‐variance similarity scaling relations are tested. Results illustrate that different states of anisotropy correspond to different similarity relations, especially under unstable stratification. Experimental data with close to isotropic turbulence match similarity relationships well. On the other hand, very anisotropic turbulence deviates significantly from the traditional scaling relations. We examine in detail the characteristics of these states of anisotropy, identify conditions in which they occur and connect them with different governing parameters. The governing parameters of turbulence anisotropy are shown to be different for stable and unstable stratification, but are able to delineate clearly the conditions in which each of the anisotropy states occurs.

The correct simulation of the atmospheric boundary layer (ABL) is crucial for reliable weather forecasts in truly complex terrain. However, common assumptions for model parametrizations are only valid for horizontally homogeneous and flat terrain. Here, we evaluate the turbulence parametrization of the numerical weather prediction model COSMO with a horizontal grid spacing of $$\Delta x = 1.1\,\hbox {km}$$Δ x = 1.1 km for the Inn Valley, Austria. The long-term, high-resolution turbulence measurements of the i-Box measurement sites provide a useful data pool of the ABL structure in the valley and on slopes. We focus on days and nights when ABL processes dominate and a thermally-driven circulation is present. Simulations are performed for case studies with both a one-dimensional turbulence parametrization, which only considers the vertical turbulent exchange, and a hybrid turbulence parametrization, also including horizontal shear production and advection in the budget of turbulence kinetic energy (TKE). We find a general underestimation of TKE by the model with the one-dimensional turbulence parametrization. In the simulations with the hybrid turbulence parametrization, the modelled TKE has a more realistic structure, especially in situations when the TKE production is dominated by shear related to the afternoon up-valley flow, and during nights, when a stable ABL is present. The model performance also improves for stations on the slopes. An estimation of the horizontal shear production from the observation network suggests that three-dimensional effects are a relevant part of TKE production in the valley.