Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

Abstract

Abstract. Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddycovariance (EC) flux measurements in urban studies. This work introduces a computational methodology that enables the generation of detailed footprints in arbitrarily complex urban flux measurements sites. The methodology is based on conducting high-resolution large-eddy simulation (LES) and Lagrangian stochastic (LS) particle analysis on a model that features a detailed topographic description of a real urban environment. The approach utilizes an arbitrarily sized target volume set around the sensor in the LES domain, to collect a dataset of LS particles which are seeded from the potential source area of the measurement and captured at the sensor site. The urban footprint is generated from this dataset through a piecewise postprocessing procedure, which divides the footprint evaluation into multiple independent processes that each yield an intermediate result. These results are ultimately selectively combined to produce the final footprint. The strategy reduces the computational cost of the LES-LS simulation and incorporates techniques to account for the complications that arise when the EC sensor is mounted on a building instead of a conventional flux tower. The presented computational framework also introduces a result assessment strategy which utilizes the obtained urban footprint together with a detailed land cover type dataset to estimate the potential error that may arise if analytically derived footprint models were employed instead. The methodology is demonstrated with a case study that concentrates on generating the footprint for a building-mounted EC measurement station in downtown Helsinki, Finland, under the neutrally stratified atmospheric boundary layer.

Overview of the PALM model system 6.0

“…In the last years, the embedded LPM has been successfully used to study scalar dispersion in urban environments (e.g. Auvinen et al, 2017;Lo and Ngan, 2017;Gronemeier and Sühring, 2019). The LPM is based on Weil et al (2004) to separate the particle speed into a deterministic and a stochastic contribution, which corresponds to dividing the turbulent flow field into a resolvedscale and a SGS portion, respectively.…”

Uncertainty of eddy covariance flux measurements over an urban area based on two towers

“…Thus, the systems are located at 60.3 m which is 2.5 times the mean building height and therefore they should be above the roughness sublayer and blending height where local-scale surface sources and sinks have aggregated together (Raupach et al, 1991). The centre of Helsinki is located on a peninsula, but previous analyses on the source area of EC1 system have shown the flux footprint to lie above the city and not the sea (Kurppa et al, 2015;Auvinen et al, 2017). The downside of the measurement location is that the upper masonry disturbs the flow and we choose to neglect 30 data for certain wind directions based on quality considerations.…”

Implementation of the sectional aerosol module SALSA into the PALM model system 6.0: Model development and first evaluation

“…Furthermore, other PALM-4U components, such as chemistry and indoor climate modules, have or are currently being implemented in the PALM model system to develop a modern and highly-efficient urban climate model. Due to its excellent scalability on massively parallel computer architectures, PALM is applicable for carrying out computationally expensive simulations over large, neighbourhood-and city-scale domains with a sufficiently high grid resolution for urban LES (Auvinen et al, 2017;Xie and Castro, 2006). The performance of PALM over urban-like surfaces has been successfully evaluated against wind tunnel simulations, previous LES studies and field measurements (Kanda et al, 2013;Letzel et al, 2008;Park et al, 2015;Razak et al, 2013).…”