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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 11
Geosci. Model Dev., 10, 4187-4205, 2017
https://doi.org/10.5194/gmd-10-4187-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 4187-4205, 2017
https://doi.org/10.5194/gmd-10-4187-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 17 Nov 2017

Development and technical paper | 17 Nov 2017

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

Mikko Auvinen1,2, Leena Järvi1, Antti Hellsten2, Üllar Rannik1, and Timo Vesala1,3 Mikko Auvinen et al.
  • 1Department of Physics, P.O. Box 64, University of Helsinki, 00014 Helsinki, Finland
  • 2Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
  • 3Department Forest Sciences, P.O. Box 27, University of Helsinki, 00014 Helsinki, Finland

Abstract. Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddy-covariance (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.

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Correct spatial interpretation of a micrometeorological measurement requires the determination of its effective source area, or footprint. In urban areas the use of analytical models becomes highly questionable. This work introduces a computational methodology that enables the generation of footprints for complex urban sites. The methodology is based on conducting high-resolution flow and particle analysis on a model that features a detailed topographic description of a real city environment.
Correct spatial interpretation of a micrometeorological measurement requires the determination...
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