Flux footprint models are often used for interpretation of flux tower measurements, to estimate position and size of surface source areas, and the relative contribution of passive scalar sources to measured fluxes. Accurate knowledge of footprints is of crucial importance for any upscaling exercises from single site flux measurements to local or regional scale. Hence, footprint models are ultimately also of considerable importance for improved greenhouse gas budgeting. With increasing numbers of flux towers within large monitoring networks such as FluxNet, ICOS (Integrated Carbon Observation System), NEON (National Ecological Observatory Network), or AmeriFlux, and with increasing temporal range of observations from such towers (of the order of decades) and availability of airborne flux measurements, there has been an increasing demand for reliable footprint estimation. Even though several sophisticated footprint models have been developed in recent years, most are still not suitable for application to long time series, due to their high computational demands. Existing fast footprint models, on the other hand, are based on surface layer theory and hence are of restricted validity for real-case applications. To remedy such shortcomings, we present the two-dimensional parameterisation for Flux Footprint Prediction (FFP), based on a novel scaling approach for the crosswind distribution of the flux footprint and on an improved version of the footprint parameterisation of Kljun et al. (2004b). Compared to the latter, FFP now provides not only the extent but also the width and shape of footprint estimates, and explicit consideration of the effects of the surface roughness length. The footprint parameterisation has been developed and evaluated using simulations of the backward Lagrangian stochastic particle dispersion model LPDM-B (Kljun et al., 2002). Like LPDM-B, the parameterisation is valid for a broad range of boundary layer conditions and measurement heights over the entire planetary boundary layer. Thus, it can provide footprint estimates for a wide range of real-case applications. The new footprint parameterisation requires input that can be easily determined from, for example, flux tower measurements or airborne flux data. FFP can be applied to data of long-term monitoring programmes as well as be used for quick footprint estimates in the field, or for designing new sites.
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.
Pollutant dispersion processes over complex terrain are much more complicated than over flat areas, as they are affected by atmospheric interactions with the orography at different spatial scales. This paper reviews recent findings and progress in this field, focusing on both experimental and modeling perspectives. It highlights open questions and challenges to our capability for better understanding and representing atmospheric processes controlling the fate of pollutants over mountainous areas. In particular, attention is focused on new measurement techniques for the retrieval of spatially distributed turbulence information and air quality parameters, and on challenges for meteorological and dispersion models to reproduce fine-scale processes influenced by the orography. Finally, specific needs in this field are discussed, along with possible directions for future research efforts.
Coupling of the earth’s surface with the atmosphere is achieved through an exchange of momentum, energy, and mass in the atmospheric boundary layer. In mountainous terrain, this exchange results from a combination of multiple transport processes, which act and interact on different spatial and temporal scales, including, for example, orographic gravity waves, thermally driven circulations, moist convection, and turbulent motions. Incorporating these exchange processes and previous studies, a new definition of the atmospheric boundary layer in mountainous terrain, a mountain boundary layer (MBL), is defined. This paper summarizes some of the major current challenges in measuring, understanding, and eventually parameterizing the relevant transport processes and the overall exchange between the MBL and the free atmosphere. Further details on many aspects of the exchange in the MBL are discussed in several other papers in this issue.
1 April 2017 in Bulletin of the American Meteorological Society
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.
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 $$\Delta x = 1.1\,\hbox {km}$$ 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.