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Flux Similarity and Turbulent Transport of Momentum, Heat and Carbon Dioxide in the Urban Boundary Layer

  • M. SchmutzEmail author
  • R. Vogt
Research Article
  • 43 Downloads

Abstract

Turbulence characteristics in the urban boundary layer of a mid-latitude European city are investigated using a quadrant analysis of more than 12 years of eddy-covariance measurements at 39 m above street level. To describe the ongoing turbulent-exchange processes, particularly the properties of ejection and sweep events, presented here are the transfer efficiency and the similarity of momentum, heat, CO2 and H2O fluxes. In addition, an event-detection algorithm is applied to derive information on the importance of organized structures for the turbulent exchange, finding that momentum and heat fluxes are primarily controlled by atmospheric stability, whereas CO2 and H2O fluxes are more affected by the presence of active sources of the corresponding scalars (e.g. traffic for CO2 fluxes). The transfer efficiencies of momentum and heat can thus be modelled accurately, but the prediction for CO2 and H2O fluxes fails because of scalar dissimilarity. Generally, ejections are more important under buoyancy-driven unstable conditions and responsible for large structures, and sweeps are more characteristic of stable cases and smaller structures. The quadrant statistics enable the identification of scales between a hole-size factor of 10 and 20 where turbulent exchange is especially efficient and almost solely takes place by ejection–sweep cycles. This information is used to apply an event-detection algorithm, which quantifies flux fractions of such reoccurring structures to be around 0.5–0.8, with the time fraction being usually around 0.1.

Keywords

Flux similarity Long-term measurements Quadrant analysis Transport and transfer efficiency Urban boundary layer 

Notes

Acknowledgements

This research is funded from the project “Urban Climate Study of Bucharest” (IZERZ0_142160) made possible by the Romanian–Swiss Research Program. Special thanks go to E. Parlow and C. Feigenwinter from the MCR–Lab for supporting this research. The data used are listed in the references or available from the MCR–Lab on request (roland.vogt@unibas.ch).

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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Environmental Sciences, Atmospheric Sciences, Research Group Meteorology, Climatology, and Remote SensingUniversity of BaselBaselSwitzerland

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