Articles | Volume 18, issue 6
https://doi.org/10.5194/amt-18-1355-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-1355-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Observations of tall-building wakes using a scanning Doppler lidar
Natalie E. Theeuwes
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
now at: Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Janet F. Barlow
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
Antti Mannisenaho
Finnish Meteorological Institute, Helsinki, Finland
Denise Hertwig
Department of Meteorology, University of Reading, Reading, UK
Ewan O'Connor
Finnish Meteorological Institute, Helsinki, Finland
Alan Robins
Department of Mechanical Engineering Sciences, University of Surrey, Guildford, UK
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Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
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The value of numerical weather predictions can be enhanced in several ways, one is to improve the representations of small-scale processes in models. To understand what needs to be improved, the model results need to be evaluated. Following standardized principles, a file format has been defined to be as similar as possible for both observational and model data. Python packages and toolkits are presented as a community resource in the production of the files and evaluation analysis.
Jutta Kesti, Ewan J. O'Connor, Anne Hirsikko, John Backman, Maria Filioglou, Anu-Maija Sundström, Juha Tonttila, Heikki Lihavainen, Hannele Korhonen, and Eija Asmi
Atmos. Chem. Phys., 24, 9369–9386, https://doi.org/10.5194/acp-24-9369-2024, https://doi.org/10.5194/acp-24-9369-2024, 2024
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Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
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Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
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This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
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Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
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Geosci. Model Dev., 16, 2077–2094, https://doi.org/10.5194/gmd-16-2077-2023, https://doi.org/10.5194/gmd-16-2077-2023, 2023
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We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
Konstantinos Matthaios Doulgeris, Ville Vakkari, Ewan J. O'Connor, Veli-Matti Kerminen, Heikki Lihavainen, and David Brus
Atmos. Chem. Phys., 23, 2483–2498, https://doi.org/10.5194/acp-23-2483-2023, https://doi.org/10.5194/acp-23-2483-2023, 2023
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We investigated how different long-range-transported air masses can affect the microphysical properties of low-level clouds in a clean subarctic environment. A connection was revealed. Higher values of cloud droplet number concentrations were related to continental air masses, whereas the lowest values of number concentrations were related to marine air masses. These were characterized by larger cloud droplets. Clouds in all regions were sensitive to increases in cloud number concentration.
Samuel J. Cliff, Will Drysdale, James D. Lee, Carole Helfter, Eiko Nemitz, Stefan Metzger, and Janet F. Barlow
Atmos. Chem. Phys., 23, 2315–2330, https://doi.org/10.5194/acp-23-2315-2023, https://doi.org/10.5194/acp-23-2315-2023, 2023
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Emissions of nitrogen oxides (NOx) to the atmosphere are an ongoing air quality issue. This study directly measures emissions of NOx and carbon dioxide from a tall tower in central London during the coronavirus pandemic. It was found that transport NOx emissions had reduced by >73 % since 2017 as a result of air quality policy and reduced congestion during coronavirus restrictions. During this period, central London was thought to be dominated by point-source heat and power generation emissions.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Jenna Ritvanen, Ewan O'Connor, Dmitri Moisseev, Raisa Lehtinen, Jani Tyynelä, and Ludovic Thobois
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Doppler lidars and weather radars provide accurate wind measurements, with Doppler lidar usually performing better in dry weather conditions and weather radar performing better when there is precipitation. Operating both instruments together should therefore improve the overall performance. We investigate how well a co-located Doppler lidar and X-band radar perform with respect to various weather conditions, including changes in horizontal visibility, cloud altitude, and precipitation.
Will S. Drysdale, Adam R. Vaughan, Freya A. Squires, Sam J. Cliff, Stefan Metzger, David Durden, Natchaya Pingintha-Durden, Carole Helfter, Eiko Nemitz, C. Sue B. Grimmond, Janet Barlow, Sean Beevers, Gregor Stewart, David Dajnak, Ruth M. Purvis, and James D. Lee
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Measurements of NOx emissions are important for a good understanding of air quality. While there are many direct measurements of NOx concentration, there are very few measurements of its emission. Measurements of emissions provide constraints on emissions inventories and air quality models. This article presents measurements of NOx emission from the BT Tower in central London in 2017 and compares them with inventories, finding that they underestimate by a factor of ∼1.48.
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432, https://doi.org/10.5194/amt-15-2417-2022, https://doi.org/10.5194/amt-15-2417-2022, 2022
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To study the complex structure of the lowest tens of metres of atmosphere in urban areas, measurement methods with great spatial and temporal coverage are needed. In our study, we analyse measurements with a promising and relatively new method, distributed temperature sensing, capable of providing detailed information on the near-surface atmosphere. We present multiple ways to utilise these kinds of measurements, as well as important considerations for planning new studies using the method.
Jutta Kesti, John Backman, Ewan J. O'Connor, Anne Hirsikko, Eija Asmi, Minna Aurela, Ulla Makkonen, Maria Filioglou, Mika Komppula, Hannele Korhonen, and Heikki Lihavainen
Atmos. Chem. Phys., 22, 481–503, https://doi.org/10.5194/acp-22-481-2022, https://doi.org/10.5194/acp-22-481-2022, 2022
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In this study we combined aerosol particle measurements at the surface with a scanning Doppler lidar providing vertical profiles of the atmosphere to study the effect of different boundary layer conditions on aerosol particle properties in the understudied Arabian Peninsula region. The instrumentation used in this study enabled us to identify periods when pollution from remote sources was mixed down to the surface and initiated new particle formation in the growing boundary layer.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
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We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
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The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Ville Vakkari, Holger Baars, Stephanie Bohlmann, Johannes Bühl, Mika Komppula, Rodanthi-Elisavet Mamouri, and Ewan James O'Connor
Atmos. Chem. Phys., 21, 5807–5820, https://doi.org/10.5194/acp-21-5807-2021, https://doi.org/10.5194/acp-21-5807-2021, 2021
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The depolarization ratio is a valuable parameter for aerosol categorization from remote sensing measurements. Here, we introduce particle depolarization ratio measurements at the 1565 nm wavelength, which is substantially longer than previously utilized wavelengths and enhances our capabilities to study the wavelength dependency of the particle depolarization ratio.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
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We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
Peggy Achtert, Ewan J. O'Connor, Ian M. Brooks, Georgia Sotiropoulou, Matthew D. Shupe, Bernhard Pospichal, Barbara J. Brooks, and Michael Tjernström
Atmos. Chem. Phys., 20, 14983–15002, https://doi.org/10.5194/acp-20-14983-2020, https://doi.org/10.5194/acp-20-14983-2020, 2020
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We present observations of precipitating and non-precipitating Arctic liquid and mixed-phase clouds during a research cruise along the Russian shelf in summer and autumn of 2014. Active remote-sensing observations, radiosondes, and auxiliary measurements are combined in the synergistic Cloudnet retrieval. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. About 8 % of all liquid clouds show a liquid water path below the infrared black body limit.
Cited articles
Allwine, K. J., Shinn, J. H., Streit, G. E., Clawson, K. L., and Brown, M.: Overview of URBAN 2000: A multiscale field study of dispersion through an urban environment, B. Am. Meteorol. Soc., 83, 521–536, 2002. a
Aristodemou, E., Mottet, L., Constantinou, A., and Pain, C.: Turbulent Flows and Pollution Dispersion around Tall Buildings Using Adaptive Large Eddy Simulation (LES), Buildings, 10, 127, https://doi.org/10.3390/buildings10070127, 2020. a
Bächlin, W., Plate, E., and Kamarga, A.: Influence of the ratio of building height to boundary layer thickness and of the approach flow velocity profile on the roof pressure distribution of cubical buildings, J. Wind Eng. Ind. Aerod., 11, 63–74, https://doi.org/10.1016/0167-6105(83)90090-9, 1983. a
Banta, R. M., Pichugina, Y. L., Kelley, N. D., Hardesty, R. M., and Brewer, W. A.: Wind Energy Meteorology: Insight into Wind Properties in the Turbine-Rotor Layer of the Atmosphere from High-Resolution Doppler Lidar, B. Am. Meteorol. Soc., 94, 883–902, https://doi.org/10.1175/bams-d-11-00057.1, 2013. a
Barlow, J. F. and Theeuwes, N.: Doppler Wind Lidar and sonic anemometer data used in a study of tall building wakes in London, as reported in Theeuwes et al. (2025), AMT, Zenodo [data set], https://doi.org/10.5281/zenodo.14990250, 2025. a
Barlow, J. F., Dunbar, T. M., Nemitz, E. G., Wood, C. R., Gallagher, M. W., Davies, F., O'Connor, E., and Harrison, R. M.: Boundary layer dynamics over London, UK, as observed using Doppler lidar during REPARTEE-II, Atmos. Chem. Phys., 11, 2111–2125, https://doi.org/10.5194/acp-11-2111-2011, 2011a. a
Barlow, J. F., Harrison, J., Robins, A. G., and Wood, C. R.: A wind-tunnel study of flow distortion at a meteorological sensor on top of the BT Tower, London, UK, J. Wind Eng. Ind. Aerod., 99, 899–907, 2011b. a
Barthelmie, R., Pryor, S., Wildmann, N., and Menke, R.: Wind turbine wake characterization in complex terrain via integrated Doppler lidar data from the Perdigão experiment, J. Phys. Conf. Ser., 1037, 052022, https://doi.org/10.1088/1742-6596/1037/5/052022, 2018. a
Barthelmie, R. J., Crippa, P., Wang, H., Smith, C. M., Krishnamurthy, R., Choukulkar, A., Calhoun, R., Valyou, D., Marzocca, P., Matthiesen, D., Brown, G., and Pryor, S. C.: 3D Wind and Turbulence Characteristics of the Atmospheric Boundary Layer, B. Am. Meteorol. Soc., 95, 743–756, https://doi.org/10.1175/bams-d-12-00111.1, 2014. a
Bingöl, F., Mann, J., and Larsen, G. C.: Light detection and ranging measurements of wake dynamics part I: one-dimensional scanning, Wind Energy, 13, 51–61, https://doi.org/10.1002/we.352, 2010. a
Bodini, N., Zardi, D., and Lundquist, J. K.: Three-dimensional structure of wind turbine wakes as measured by scanning lidar, Atmos. Meas. Tech., 10, 2881–2896, https://doi.org/10.5194/amt-10-2881-2017, 2017. a
Calhoun, R., Heap, R., Princevac, M., Newsom, R., Fernando, H., and Ligon, D.: Virtual Towers Using Coherent Doppler Lidar during the Joint Urban 2003 Dispersion Experiment, J. Appl. Meteorol. Clim., 45, 1116–1126, https://doi.org/10.1175/jam2391.1, 2006. a
Castro, I. P. and Robins, A. G.: The flow around a surface-mounted cube in uniform and turbulent streams, J. Fluid Mech., 79, 307–335, https://doi.org/10.1017/s0022112077000172, 1977. a
Christen, A., Rotach, M. W., and Vogt, R.: The budget of turbulent kinetic energy in the urban roughness sublayer, Bound.-Lay. Meteorol., 131, 193–222, 2009. a
Collier, C. G., Davies, F., Bozier, K. E., Holt, A. R., Middleton, D. R., Pearson, G. N., Siemen, S., Willetts, D. V., Upton, G. J. G., and Young, R. I.: Dual-Doppler Lidar Measurements for Improving Dispersion Models, B. Am. Meteorol. Soc., 86, 825–838, https://doi.org/10.1175/bams-86-6-825, 2005. a
Drew, D. R., Barlow, J. F., and Lane, S. E.: Observations of wind speed profiles over Greater London, UK, using a Doppler lidar, J. Wind Eng. Ind. Aerod., 121, 98–105, https://doi.org/10.1016/j.jweia.2013.07.019, 2013. a
Filioglou, M., Preissler, J., Troiville, A., Thobois, L., Vakkari, V., Auvinen, M., Fortelius, C., Gregow, E., Hämäläinen, K., Hellsten, A., Järvi, L., O'Connor, E., Schönach, D., and Hirsikko, A.: Evaluating modelled winds over an urban area using ground-based Doppler lidar observations, Meteorol. Appl., 29, e2052, https://doi.org/10.1002/met.2052, 2022. a
Fuka, V., Xie, Z.-T., Castro, I. P., Hayden, P., Carpentieri, M., and Robins, A. G.: Scalar Fluxes Near a Tall Building in an Aligned Array of Rectangular Buildings, Bound.-Lay. Meteorol., 167, 53–76, https://doi.org/10.1007/s10546-017-0308-4, 2018. a
Hansen, K. S., Barthelmie, R. J., Jensen, L. E., and Sommer, A.: The impact of turbulence intensity and atmospheric stability on power deficits due to wind turbine wakes at Horns Rev wind farm, Wind Energy, 15, 183–196, https://doi.org/10.1002/we.512, 2011. a
Huang, X., Gao, L., Guo, D., and Yao, R.: Impacts of high-rise building on urban airflows and pollutant dispersion under different temperature stratifications: Numerical investigations, Atmos. Pollut. Res., 12, 100–112, https://doi.org/10.1016/j.apr.2021.02.001, 2021. a
Iungo, G. V., Wu, Y.-T., and Porté-Agel, F.: Field Measurements of Wind Turbine Wakes with Lidars, J. Atmos. Ocean. Tech., 30, 274–287, https://doi.org/10.1175/jtech-d-12-00051.1, 2013. a
Kastner-Klein, P. and Rotach, M. W.: Mean flow and turbulence characteristics in an urban roughness sublayer, Bound.-Lay. Meteorol., 111, 55–84, 2004. a
Kikumoto, H., Ooka, R., Sugawara, H., and Lim, J.: Observational study of power-law approximation of wind profiles within an urban boundary layer for various wind conditions, J. Wind Eng. Ind. Aerod., 164, 13–21, https://doi.org/10.1016/j.jweia.2017.02.003, 2017. a
Kongara, S., Calhoun, R., Choukulkar, A., and Boldi, M.-O.: Velocity retrieval for coherent Doppler lidar, Int. J. Remote Sens., 33, 3596–3613, 2012. a
Kotthaus, S., Bravo-Aranda, J. A., Collaud Coen, M., Guerrero-Rascado, J. L., Costa, M. J., Cimini, D., O'Connor, E. J., Hervo, M., Alados-Arboledas, L., Jiménez-Portaz, M., Mona, L., Ruffieux, D., Illingworth, A., and Haeffelin, M.: Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations, Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, 2023. a
Lam, K., Leung, M., and Zhao, J.: Interference effects on wind loading of a row of closely spaced tall buildings, J. Wind Eng. Ind. Aerod., 96, 562–583, 2008. a
Lane, S., Barlow, J. F., and Wood, C. R.: An assessment of a three-beam Doppler lidar wind profiling method for use in urban areas, J. Wind Eng. Ind. Aerod., 119, 53–59, 2013. a
Lindberg, F., Grimmond, C. S. B., Gabey, A., Huang, B., Kent, C. W., Sun, T., Theeuwes, N. E., Järvi, L., Ward, H. C., Capel-Timms, I., Chang, Y., Jonsson, P., Krave, N., Liu, D., Meyer, D., Olofson, K. F. G., Tan, J., Wästberg, D., Xue, L., and Zhang, Z.: Urban Multi-scale Environmental Predictor (UMEP): An integrated tool for city-based climate services, Environ. Model. Softw., 99, 70–87, 2018. a
Liu, J. and Niu, J.: CFD simulation of the wind environment around an isolated high-rise building: An evaluation of SRANS, LES and DES models, Build. Environ., 96, 91–106, 2016. a
Liu, X., Zhang, H., Wu, S., Wang, Q., He, Z., Zhang, J., Li, R., Liu, S., and Zhang, X.: Effects of buildings on wind shear at the airport: Field measurement by coherent Doppler lidar, J. Wind Eng. Ind. Aerod., 230, 105194, https://doi.org/10.1016/j.jweia.2022.105194, 2022. a
Manninen, A., Marke, T., Tuononen, M., and O'Connor, E.: Atmospheric boundary layer classification with Doppler lidar, J. Geophys. Res.-Atmos., 123, 8172–8189, 2018. a
Manninen, A. J., O'Connor, E. J., Vakkari, V., and Petäjä, T.: A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland, Atmos. Meas. Tech., 9, 817–827, https://doi.org/10.5194/amt-9-817-2016, 2016. a, b, c
Mishra, A., Placidi, M., Carpentieri, M., and Robins, A.: Wake Characterization of Building Clusters Immersed in Deep Boundary Layers, Bound.-Lay. Meteorol., 189, 163–187, 2023. a
Morrison, W., Yin, T., Lauret, N., Guilleux, J., Kotthaus, S., Gastellu-Etchegorry, J.-P., Norford, L., and Grimmond, S.: Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling, Remote Sens. Environ., 237, 111524, https://doi.org/10.1016/j.rse.2019.111524, 2020. a
Nafisifard, M., Jakobsen, J. B., Snæbjörnsson, J. T., Sjöholm, M., and Mann, J.: Lidar measurements of wake around a bridge deck, J. Wind Eng. Ind. Aerod., 240, 105491, https://doi.org/10.1016/j.jweia.2023.105491, 2023. a
Newsom, R. K., Brewer, W. A., Wilczak, J. M., Wolfe, D. E., Oncley, S. P., and Lundquist, J. K.: Validating precision estimates in horizontal wind measurements from a Doppler lidar, Atmos. Meas. Tech., 10, 1229–1240, https://doi.org/10.5194/amt-10-1229-2017, 2017. a
Oke, T.: Observing urban weather and climate, in: WMO Technical Conference on Meteorological and Environmental Instruments and Methods of Observation (TECO-98), Casablanca, Morocco, 13–15 May 1998, Instruments and Observing Methods Rep. 70, WMO/TD NO. 877, https://library.wmo.int/idurl/4/41861 (last access: 20 March 2024), 1998. a
Ortiz-Amezcua, P., Martínez-Herrera, A., Manninen, A. J., Pentikäinen, P. P., O'Connor, E. J., Guerrero-Rascado, J. L., and Alados-Arboledas, L.: Wind and Turbulence Statistics in the Urban Boundary Layer over a Mountain–Valley System in Granada, Spain, Remote Sens., 14, 2321, https://doi.org/10.3390/rs14102321, 2022. a, b
Päschke, E., Leinweber, R., and Lehmann, V.: An assessment of the performance of a 1.5 µm Doppler lidar for operational vertical wind profiling based on a 1-year trial, Atmos. Meas. Tech., 8, 2251–2266, https://doi.org/10.5194/amt-8-2251-2015, 2015. a, b, c
Pearson, G., Davies, F., and Collier, C.: An Analysis of the Performance of the UFAM Pulsed Doppler Lidar for Observing the Boundary Layer, J. Atmos. Ocean. Tech., 26, 240–250, https://doi.org/10.1175/2008jtecha1128.1, 2009. a
Raupach, M., Antonia, R., and Rajagopalan, S.: Rough-Wall Turbulent Boundary Layers, Appl. Mech. Rev., 44, 1–26, https://doi.org/10.1115/1.3119492, 1991. a
Robins, A. and McHugh, C.: Development and evaluation of the ADMS building effects module, Int. J. Environ. Pollut., 16, 161–174, 2001. a
Rotach, M. W.: On the influence of the urban roughness sublayer on turbulence and dispersion, Atmos. Environ., 33, 4001–4008, 1999. a
Rye, B. and Hardesty, R.: Discrete spectral peak estimation in incoherent backscatter heterodyne lidar. I. Spectral accumulation and the Cramer-Rao lower bound, IEEE T. Geosci. Remote, 31, 16–27, https://doi.org/10.1109/36.210440, 1993. a
Sheng, R., Perret, L., Calmet, I., Demouge, F., and Guilhot, J.: Wind tunnel study of wind effects on a high-rise building at a scale of 1 : 300, J. Wind Eng. Ind. Aerod., 174, 391–403, 2018. a
Song, J., Fan, S., Lin, W., Mottet, L., Woodward, H., Davies Wykes, M., Arcucci, R., Xiao, D., Debay, J.-E., ApSimon, H., Aristodemou, E., Birch, D., Carpentieri, M., Fang, F., Herzog, M., Hunt, G. R., Jones, R. L., Pain, C., Pavlidis, D., Robins, A. G., Short, C. A., and Linden, P. F.: Natural ventilation in cities: the implications of fluid mechanics, Build. Res. Inf., 46, 809–828, 2018. a, b
Stewart, I. D.: A systematic review and scientific critique of methodology in modern urban heat island literature, Int. J. Climatol., 31, 200–217, 2011. a
Sun, H., Gao, X., and Yang, H.: A review of full-scale wind-field measurements of the wind-turbine wake effect and a measurement of the wake-interaction effect, Renew. Sust. Energ. Rev., 132, 110042, https://doi.org/10.1016/j.rser.2020.110042, 2020. a
Theeuwes, N. E., Barlow, J. F., Teuling, A. J., Grimmond, C. S. B., and Kotthaus, S.: Persistent cloud cover over mega-cities linked to surface heat release, npj Climate and Atmospheric Science, 2, 1–6, 2019a. a
Theeuwes, N. E., Ronda, R. J., Harman, I. N., Christen, A., and Grimmond, C. S. B.: Parametrizing Horizontally-Averaged Wind and Temperature Profiles in the Urban Roughness Sublayer, Bound.-Lay. Meteorol., 173, 321–348, 2019b. a
Trujillo, J.-J., Bingöl, F., Larsen, G. C., Mann, J., and Kühn, M.: Light detection and ranging measurements of wake dynamics. Part II: two-dimensional scanning, Wind Energy, 14, 61–75, https://doi.org/10.1002/we.402, 2011. a
Vakkari, V., O'Connor, E. J., Nisantzi, A., Mamouri, R. E., and Hadjimitsis, D. G.: Low-level mixing height detection in coastal locations with a scanning Doppler lidar, Atmos. Meas. Tech., 8, 1875–1885, https://doi.org/10.5194/amt-8-1875-2015, 2015. a
Vasiljević, N., L. M. Palma, J. M., Angelou, N., Carlos Matos, J., Menke, R., Lea, G., Mann, J., Courtney, M., Frölen Ribeiro, L., and M. G. C. Gomes, V. M.: Perdigão 2015: methodology for atmospheric multi-Doppler lidar experiments, Atmos. Meas. Tech., 10, 3463–3483, https://doi.org/10.5194/amt-10-3463-2017, 2017. a
Wharton, S. and Lundquist, J. K.: Atmospheric stability affects wind turbine power collection, Environ. Res. Lett., 7, 014005, https://doi.org/10.1088/1748-9326/7/1/014005, 2012. a
Wildmann, N., Gerz, T., and Lundquist, J. K.: Long-range Doppler lidar measurements of wind turbine wakes and their interaction with turbulent atmospheric boundary-layer flow at Perdigao 2017, J. Phys. Conf. Ser., 1618, 032034, https://doi.org/10.1088/1742-6596/1618/3/032034, 2020. a
Wood, C., Lacser, A., Barlow, J. F., Padhra, A., Belcher, S. E., Nemitz, E., Helfter, C., Famulari, D., and Grimmond, C.: Turbulent flow at 190 m height above London during 2006–2008: a climatology and the applicability of similarity theory, Bound.-Lay. Meteorol., 137, 77–96, 2010. a
Short summary
A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall...