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Boundary-Layer Meteorology

, Volume 168, Issue 2, pp 289–319 | Cite as

Assessment of Planetary-Boundary-Layer Schemes in the Weather Research and Forecasting Model Within and Above an Urban Canopy Layer

  • Enrico Ferrero
  • Stefano Alessandrini
  • Francois Vandenberghe
Research Article
  • 515 Downloads

Abstract

We tested several planetary-boundary-layer (PBL) schemes available in the Weather Research and Forecasting (WRF) model against measured wind speed and direction, temperature and turbulent kinetic energy (TKE) at three levels (5, 9, 25 m). The Urban Turbulence Project dataset, gathered from the outskirts of Turin, Italy and used for the comparison, provides measurements made by sonic anemometers for more than 1 year. In contrast to other similar studies, which have mainly focused on short-time periods, we considered 2 months of measurements (January and July) representing both the seasonal and the daily variabilities. To understand how the WRF-model PBL schemes perform in an urban environment, often characterized by low wind-speed conditions, we first compared six PBL schemes against observations taken by the highest anemometer located in the inertial sub-layer. The availability of the TKE measurements allows us to directly evaluate the performances of the model; results of the model evaluation are presented in terms of quantile versus quantile plots and statistical indices. Secondly, we considered WRF-model PBL schemes that can be coupled to the urban-surface exchange parametrizations and compared the simulation results with measurements from the two lower anemometers located inside the canopy layer. We find that the PBL schemes accounting for TKE are more accurate and the model representation of the roughness sub-layer improves when the urban model is coupled to each PBL scheme.

Keywords

Boundary-layer scheme Sonic anemometer data Urban model Weather Research and Forecasting model 

Notes

Acknowledgements

The authors are grateful to Luca Mortarini (ISAC-CNR, Italy) for providing the pre-processed UTP dataset and to Will Cheng (NCAR, USA) for his useful suggestions.

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Dipartimento di Scienze e Innovazione TecnologicaUniversità del Piemonte OrientaleAlessandriaItaly
  2. 2.Research Applications LaboratoryNational Center for Atmospheric ResearchBoulderUSA

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