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Evaluating modelled winds over an urban area using ground‐based Doppler lidar observations
Author(s) -
Filioglou Maria,
Preissler Jana,
Troiville Anselme,
Thobois Ludovic,
Vakkari Ville,
Auvinen Mikko,
Fortelius Carl,
Gregow Erik,
Hämäläinen Karoliina,
Hellsten Antti,
Järvi Leena,
O'Connor Ewan,
Schönach David,
Hirsikko Anne
Publication year - 2022
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.2052
Subject(s) - lidar , environmental science , meteorology , wind speed , numerical weather prediction , sea breeze , wind direction , maximum sustained wind , remote sensing , geography , wind gradient
Wind information in urban areas is essential for many applications related to air pollution, urban climate and planning, safety of drone‐related operations, and assessment of urban wind energy potential. These applications require accurate wind forecasts, and obtaining this information in an urban environment is challenging as the morphology of a city varies from street to street, altering the wind flow. Remote sensing techniques such as Doppler lidars (light detection and ranging) provide a unique opportunity for wind forecast verification as they can provide both the vertical profile of the horizontal wind and the spatial variation in the horizontal domain at high resolution. In this study, the performance of numerical weather prediction (NWP) models, analysis systems, and large‐eddy simulation (LES) models have been analysed by comparing the modelled winds against Doppler lidar observations under various atmospheric conditions and from season to season, in the coastal environment of Helsinki, Finland. The long‐term mean vertical profile of the modelled horizontal wind shows good agreement with observations; the NWP model and the analysis systems selected here exhibit different strengths and weaknesses depending on the atmospheric conditions but no significant diurnal variation in performance. However, both the model and analysis systems show differences in their spatially‐averaged bias when investigating different wind directions. LES verification shows that these models can potentially provide winds down to street level, given pre‐computed scenarios of atmospheric conditions. For Helsinki, the observed winds are stronger during winter than summer, and, on average, higher wind speeds were observed at the urban site than the sub‐urban site.

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