Articles | Volume 10, issue 11
https://doi.org/10.5194/gmd-10-4187-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-4187-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
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
Department of Physics, P.O. Box 64, University of Helsinki, 00014 Helsinki, Finland
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Leena Järvi
Department of Physics, P.O. Box 64, University of Helsinki, 00014 Helsinki, Finland
Antti Hellsten
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Üllar Rannik
Department of Physics, P.O. Box 64, University of Helsinki, 00014 Helsinki, Finland
Timo Vesala
Department of Physics, P.O. Box 64, University of Helsinki, 00014 Helsinki, Finland
Department Forest Sciences, P.O. Box 27, University of Helsinki, 00014 Helsinki,
Finland
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21 citations as recorded by crossref.
- A framework combining multi-scale model and unmanned aerial vehicle for investigating urban micro-meteorology, thermal comfort, and energy balance J. Hang et al. https://doi.org/10.1016/j.scs.2024.105847
- Source area definition for local climate zones studies. A systematic review M. Núñez Peiró et al. https://doi.org/10.1016/j.buildenv.2018.10.050
- Residential air quality near noise barriers strongly affected by wind velocity A. Kooh Andaz et al. https://doi.org/10.1016/j.scitotenv.2025.180304
- Footprints in an urban array model under multiple wind directions: A wind tunnel experiment investigation H. Jia et al. https://doi.org/10.1063/5.0211137
- Numerical Simulation of Particulate Matter Transport in the Atmospheric Urban Boundary Layer Using the Lagrangian Approach: Physical Problems and Parallel Implementation A. Varentsov et al. https://doi.org/10.1134/S0361768823080248
- A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations S. Stagakis et al. https://doi.org/10.1016/j.scitotenv.2023.166035
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. https://doi.org/10.1080/20964471.2024.2325019
- Uncertainty of eddy covariance flux measurements over an urban area based on two towers L. Järvi et al. https://doi.org/10.5194/amt-11-5421-2018
- Study of Realistic Urban Boundary Layer Turbulence with High-Resolution Large-Eddy Simulation M. Auvinen et al. https://doi.org/10.3390/atmos11020201
- SEBU: A novel fully automated Google Earth Engine surface energy balance model for urban areas Y. Abunnasr et al. https://doi.org/10.1016/j.uclim.2022.101187
- Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0 A. Criado et al. https://doi.org/10.5194/gmd-16-2193-2023
- Mean flow and turbulence in unsteady canopy layers W. Li & M. Giometto https://doi.org/10.1017/jfm.2023.801
- Wind Tunnel Experiment on the Footprint of a Block-Arrayed Urban Model in a Neutrally Stratified Boundary Layer H. Jia et al. https://doi.org/10.1007/s10546-024-00883-9
- Evaluating modelled winds over an urban area using ground‐based Doppler lidar observations M. Filioglou et al. https://doi.org/10.1002/met.2052
- Budgets of Second-Order Turbulence Moments over a Real Urban Canopy E. Akinlabi et al. https://doi.org/10.1007/s10546-023-00816-y
- Urban Boundary Layer Growth and Turbulence in Paris Using Large-Eddy Simulations J. Strömberg et al. https://doi.org/10.1007/s10546-026-00980-x
- Ventilation and Air Quality in City Blocks Using Large-Eddy Simulation—Urban Planning Perspective M. Kurppa et al. https://doi.org/10.3390/atmos9020065
- Overview of the PALM model system 6.0 B. Maronga et al. https://doi.org/10.5194/gmd-13-1335-2020
- Implementation of the sectional aerosol module SALSA2.0 into the PALM model system 6.0: model development and first evaluation M. Kurppa et al. https://doi.org/10.5194/gmd-12-1403-2019
- Backward-Eulerian Footprint Modelling Based on the Adjoint Equation for Atmospheric and Urban-Terrain Dispersion H. Jia & H. Kikumoto https://doi.org/10.1007/s10546-023-00807-z
- Open questions in atmospheric turbulence: A synthesis from the centenary workshop “100 years of turbulence: Innsbruck 1922 -2022” I. Stiperski et al. https://doi.org/10.1016/j.jemets.2025.100022
21 citations as recorded by crossref.
- A framework combining multi-scale model and unmanned aerial vehicle for investigating urban micro-meteorology, thermal comfort, and energy balance J. Hang et al. https://doi.org/10.1016/j.scs.2024.105847
- Source area definition for local climate zones studies. A systematic review M. Núñez Peiró et al. https://doi.org/10.1016/j.buildenv.2018.10.050
- Residential air quality near noise barriers strongly affected by wind velocity A. Kooh Andaz et al. https://doi.org/10.1016/j.scitotenv.2025.180304
- Footprints in an urban array model under multiple wind directions: A wind tunnel experiment investigation H. Jia et al. https://doi.org/10.1063/5.0211137
- Numerical Simulation of Particulate Matter Transport in the Atmospheric Urban Boundary Layer Using the Lagrangian Approach: Physical Problems and Parallel Implementation A. Varentsov et al. https://doi.org/10.1134/S0361768823080248
- A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations S. Stagakis et al. https://doi.org/10.1016/j.scitotenv.2023.166035
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. https://doi.org/10.1080/20964471.2024.2325019
- Uncertainty of eddy covariance flux measurements over an urban area based on two towers L. Järvi et al. https://doi.org/10.5194/amt-11-5421-2018
- Study of Realistic Urban Boundary Layer Turbulence with High-Resolution Large-Eddy Simulation M. Auvinen et al. https://doi.org/10.3390/atmos11020201
- SEBU: A novel fully automated Google Earth Engine surface energy balance model for urban areas Y. Abunnasr et al. https://doi.org/10.1016/j.uclim.2022.101187
- Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0 A. Criado et al. https://doi.org/10.5194/gmd-16-2193-2023
- Mean flow and turbulence in unsteady canopy layers W. Li & M. Giometto https://doi.org/10.1017/jfm.2023.801
- Wind Tunnel Experiment on the Footprint of a Block-Arrayed Urban Model in a Neutrally Stratified Boundary Layer H. Jia et al. https://doi.org/10.1007/s10546-024-00883-9
- Evaluating modelled winds over an urban area using ground‐based Doppler lidar observations M. Filioglou et al. https://doi.org/10.1002/met.2052
- Budgets of Second-Order Turbulence Moments over a Real Urban Canopy E. Akinlabi et al. https://doi.org/10.1007/s10546-023-00816-y
- Urban Boundary Layer Growth and Turbulence in Paris Using Large-Eddy Simulations J. Strömberg et al. https://doi.org/10.1007/s10546-026-00980-x
- Ventilation and Air Quality in City Blocks Using Large-Eddy Simulation—Urban Planning Perspective M. Kurppa et al. https://doi.org/10.3390/atmos9020065
- Overview of the PALM model system 6.0 B. Maronga et al. https://doi.org/10.5194/gmd-13-1335-2020
- Implementation of the sectional aerosol module SALSA2.0 into the PALM model system 6.0: model development and first evaluation M. Kurppa et al. https://doi.org/10.5194/gmd-12-1403-2019
- Backward-Eulerian Footprint Modelling Based on the Adjoint Equation for Atmospheric and Urban-Terrain Dispersion H. Jia & H. Kikumoto https://doi.org/10.1007/s10546-023-00807-z
- Open questions in atmospheric turbulence: A synthesis from the centenary workshop “100 years of turbulence: Innsbruck 1922 -2022” I. Stiperski et al. https://doi.org/10.1016/j.jemets.2025.100022
Saved (final revised paper)
Latest update: 15 Oct 2026
Short summary
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...
