Articles | Volume 16, issue 8
https://doi.org/10.5194/gmd-16-2077-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2077-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluating wind profiles in a numerical weather prediction model with Doppler lidar
Pyry Pentikäinen
CORRESPONDING AUTHOR
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland
Ewan J. O'Connor
Finnish Meteorological Institute, Helsinki, Finland
Department of Meteorology, University of Reading, Reading, United Kingdom
Pablo Ortiz-Amezcua
Institute of Geophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland
Andalusian Institute for Earth System Research, Granada, Spain
Related authors
No articles found.
Sasu Karttunen, Matthias Sühring, Ewan O'Connor, and Leena Järvi
Geosci. Model Dev., 18, 5725–5757, https://doi.org/10.5194/gmd-18-5725-2025, https://doi.org/10.5194/gmd-18-5725-2025, 2025
Short summary
Short summary
This paper presents PALM-SLUrb, a single-layer urban canopy model for the PALM model system, designed to simulate urban–atmosphere interactions without resolving flow around individual buildings. The model is described in detail and evaluated against grid-resolved urban canopy simulations, demonstrating its ability to model urban surfaces accurately. By bridging the gap between computational efficiency and physical detail, PALM-SLUrb broadens PALM's potential for urban climate research.
Simo Tukiainen, Tuomas Siipola, Niko Leskinen, and Ewan O'Connor
Earth Syst. Sci. Data, 17, 3797–3806, https://doi.org/10.5194/essd-17-3797-2025, https://doi.org/10.5194/essd-17-3797-2025, 2025
Short summary
Short summary
Measurement campaigns are crucial for advancing the understanding of complex cloud–aerosol interactions in the atmosphere. Ground-based remote sensing measurements were conducted in Kenttärova, Finland, during the Pallas Cloud Experiment 2022 campaign. These measurements were processed using the Cloudnet methodology, and the data are available through the ACTRIS Cloudnet data portal.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025, https://doi.org/10.5194/amt-18-1355-2025, 2025
Short summary
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.
Maciej Karasewicz, Marta Wacławczyk, Pablo Ortiz-Amezcua, Łucja Janicka, Patryk Poczta, Camilla Kassar Borges, and Iwona S. Stachlewska
Atmos. Chem. Phys., 24, 13231–13251, https://doi.org/10.5194/acp-24-13231-2024, https://doi.org/10.5194/acp-24-13231-2024, 2024
Short summary
Short summary
This work concerns analysis of turbulence in the atmospheric boundary layer shortly before sunset. Based on a large set of measurements at a rural and an urban site, we analyze how turbulence properties change in time during rapid decay of convection. We explain the observations using recent theories of non-equilibrium turbulence. The presence of non-equilibrium suggests that classical parametrization schemes fail to predict turbulence statistics shortly before sunset.
Johanna Tjernström, Michael Gallagher, Jareth Holt, Gunilla Svensson, Matthew D. Shupe, Jonathan J. Day, Lara Ferrighi, Siri Jodha Khalsa, Leslie M. Hartten, Ewan O'Connor, Zen Mariani, and Øystein Godøy
EGUsphere, https://doi.org/10.5194/egusphere-2024-2088, https://doi.org/10.5194/egusphere-2024-2088, 2024
Preprint archived
Short summary
Short summary
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
Short summary
Short summary
The study combines aerosol particle measurements at the surface and vertical profiling of the atmosphere with a scanning Doppler lidar to investigate how particle transportation together with boundary layer evolution can affect particle and SO2 concentrations at the surface in the Arabian Peninsula region. The instrumentation enabled us to see elevated nucleation mode particle and SO2 concentrations at the surface when air masses transported from polluted areas are mixed in the boundary layer.
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
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
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
Short summary
Short summary
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
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
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
Short summary
Short summary
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.
Maria Filioglou, Ari Leskinen, Ville Vakkari, Ewan O'Connor, Minttu Tuononen, Pekko Tuominen, Samuli Laukkanen, Linnea Toiviainen, Annika Saarto, Xiaoxia Shang, Petri Tiitta, and Mika Komppula
Atmos. Chem. Phys., 23, 9009–9021, https://doi.org/10.5194/acp-23-9009-2023, https://doi.org/10.5194/acp-23-9009-2023, 2023
Short summary
Short summary
Pollen impacts climate and public health, and it can be detected in the atmosphere by lidars which measure the linear particle depolarization ratio (PDR), a shape-relevant optical parameter. As aerosols also cause depolarization, surface aerosol and pollen observations were combined with measurements from ground-based lidars operating at different wavelengths to determine the optical properties of birch and pine pollen and quantify their relative contribution to the PDR.
Jesús Abril-Gago, Pablo Ortiz-Amezcua, Diego Bermejo-Pantaleón, Juana Andújar-Maqueda, Juan Antonio Bravo-Aranda, María José Granados-Muñoz, Francisco Navas-Guzmán, Lucas Alados-Arboledas, Inmaculada Foyo-Moreno, and Juan Luis Guerrero-Rascado
Atmos. Chem. Phys., 23, 8453–8471, https://doi.org/10.5194/acp-23-8453-2023, https://doi.org/10.5194/acp-23-8453-2023, 2023
Short summary
Short summary
Validation activities of Aeolus wind products were performed in Granada with different upward-probing instrumentation (Doppler lidar system and radiosondes) and spatiotemporal collocation criteria. Specific advantages and disadvantages of each instrument were identified, and an optimal comparison criterion is proposed. Aeolus was proven to provide reliable wind products, and the upward-probing instruments were proven to be useful for Aeolus wind product validation activities.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
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
Short summary
Short summary
In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Atmos. Meas. Tech., 15, 6507–6519, https://doi.org/10.5194/amt-15-6507-2022, https://doi.org/10.5194/amt-15-6507-2022, 2022
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Jesús Abril-Gago, Juan Luis Guerrero-Rascado, Maria João Costa, Juan Antonio Bravo-Aranda, Michaël Sicard, Diego Bermejo-Pantaleón, Daniele Bortoli, María José Granados-Muñoz, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Adolfo Comerón, Pablo Ortiz-Amezcua, Vanda Salgueiro, Marta María Jiménez-Martín, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 22, 1425–1451, https://doi.org/10.5194/acp-22-1425-2022, https://doi.org/10.5194/acp-22-1425-2022, 2022
Short summary
Short summary
A validation of Aeolus reprocessed optical products is carried out via an intercomparison with ground-based measurements taken at several ACTRIS/EARLINET stations in western Europe. Case studies and a statistical analysis are presented. The stations are located in a hot spot between Africa and the rest of Europe, which guarantees a variety of aerosol types, from mineral dust layers to continental/anthropogenic aerosol, and allows us to test Aeolus performance under different scenarios.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jose Antonio Benavent-Oltra, Juan Andrés Casquero-Vera, Roberto Román, Hassan Lyamani, Daniel Pérez-Ramírez, María José Granados-Muñoz, Milagros Herrera, Alberto Cazorla, Gloria Titos, Pablo Ortiz-Amezcua, Andrés Esteban Bedoya-Velásquez, Gregori de Arruda Moreira, Noemí Pérez, Andrés Alastuey, Oleg Dubovik, Juan Luis Guerrero-Rascado, Francisco José Olmo-Reyes, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 21, 9269–9287, https://doi.org/10.5194/acp-21-9269-2021, https://doi.org/10.5194/acp-21-9269-2021, 2021
Short summary
Short summary
In this paper, we use the GRASP algorithm combining different remote sensing measurements to obtain the aerosol vertical and column properties during the SLOPE I and II campaigns. We show an overview of aerosol properties retrieved by GRASP during these campaigns and evaluate the retrievals of aerosol properties using the in situ measurements performed at a high-altitude station and airborne flights. For the first time we present an evaluation of the absorption coefficient by GRASP.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Ourania Soupiona, Alexandros Papayannis, Panagiotis Kokkalis, Romanos Foskinis, Guadalupe Sánchez Hernández, Pablo Ortiz-Amezcua, Maria Mylonaki, Christina-Anna Papanikolaou, Nikolaos Papagiannopoulos, Stefanos Samaras, Silke Groß, Rodanthi-Elisavet Mamouri, Lucas Alados-Arboledas, Aldo Amodeo, and Basil Psiloglou
Atmos. Chem. Phys., 20, 15147–15166, https://doi.org/10.5194/acp-20-15147-2020, https://doi.org/10.5194/acp-20-15147-2020, 2020
Short summary
Short summary
51 dust events over the Mediterranean from EARLINET were studied regarding the aerosol geometrical, optical and microphysical properties and radiative forcing. We found δp532 values of 0.24–0.28, LR532 values of 49–52 sr and AOT532 of 0.11–0.40. The aerosol mixing state was also examined. Depending on the dust properties, intensity and solar zenith angle, the estimated solar radiative forcing ranged from −59 to −22 W m−2 at the surface and from −24 to −1 W m−2 at the TOA (cooling effect).
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
Short summary
Short summary
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
Accadia, C., Zecchetto, S., Lavagnini, A., and Speranza, A.: Comparison of 10-m
wind forecasts from a Regional Area Model and QuikSCAT Scatterometer wind
observations over the Mediterranean Sea, Mon. Weather Rev., 135, 1945– 1960, https://doi.org/10.1175/MWR3370.1, 2007. a, b
Andersson, E.: How to evolve global observing systems, ECMWF Newsletter, 153,
37–40, https://doi.org/10.21957/9fxea2, 2017. a
Atmospheric Radiation Measurement (ARM) user facility: Balloon-Borne Sounding
System (SONDEWNPN), 2013-09-28 to 2022-05-29, ARM Mobile Facility (PVC)
Highland Center, Cape Cod MA; AMF1 (M1), Eastern North Atlantic (ENA) Graciosa
Island, Azores, Portugal (C1), Southern Great Plains (SGP) Central Facility,
Lamont, OK (C1), Tropical Western Pacific (TWP) Central Facility, Darwin,
Australia (C3), compiled by: Keeler, E., Coulter, R., Kyrouac, J., and
Holdridge, D., ARM Data Center [data set], https://doi.org/10.5439/1021460, 2013. a
Atmospheric Radiation Measurement (ARM) user facility: Doppler Lidar
Horizontal Wind Profiles (DLPROFWIND4NEWS), 2014-10-21 to 2022-03-20, ARM
Mobile Facility (PVC) Highland Center, Cape Cod MA; AMF1 (M1), Eastern North
Atlantic (ENA) Graciosa Island, Azores, Portugal (C1), Southern Great Plains
(SGP) Central Facility, Lamont, OK (C1), Tropical Western Pacific (TWP)
Central Facility, Darwin, Australia (C3), compiled by: Shippert, T., Newsom, R.,
and Riihimaki, L., ARM Data Center [data set], https://doi.org/10.5439/1178582, 2014. a
Beck, J., Nuret, M., and Bousquet, O.: Model wind field forecast verification
using multiple-Doppler syntheses from a national radar network, Weather
Forecast., 29, 331–348, https://doi.org/10.1175/WAF-D-13-00068.1, 2014. a
Bingöl, F., Mann, J., and Foussekis, D.: Conically scanning lidar error in
complex terrain, Meteorol. Z., 18, 189–195,
https://doi.org/10.1127/0941-2948/2009/0368, 2009. a
Bormann, N., Saarinen, S., Kelly, G., and Thépaut, J.-N.: The spatial
structure of observation errors in atmospheric motion vectors from
geostationary satellite data, Mon. Weather Rev., 131, 706–718, 2003. a
Casati, B., Wilson, L. J., Stephenson, D. B., Nurmi, P., Ghelli, A., Pocernich,
M., Damrath, U., Ebert, E. E., Brown, B. G., and Mason, S.: Forecast
verification: current status and future directions, Meteor. Appl., 15,
3–18, https://doi.org/10.1002/met.52, 2008. a, b
Cuxart, J., Telisman Prtenjak, M., and Matjacic, B.: Pannonian Basin nocturnal
boundary layer and fog formation: role of topography, Atmosphere, 12, 712,
https://doi.org/10.3390/atmos12060712, 2021. a
Ebert, E., Brown, B., Göber, M., Haiden, T., Mittermaier, M., Nurmi, P.,
Wilson, L., Jackson, S., Johnston, P., and Schuster, D.: The WMO challenge
to develop and demonstrate the best new user-oriented forecast verification
metric, Meteorol. Z., 27, 435–440, https://doi.org/10.1127/metz/2018/0892, 2018. a
Finnish Meteorological Institute: Doppler lidar wind profiles from Kumpula.
compiled by: O'Connor, E., Zenodo [data set], https://doi.org/10.5281/zenodo.6628968,
2022. a
Fovell, R. G. and Gallagher, A.: Boundary layer and surface verification of the
High-Resolution Rapid Refresh, Version 3, Weather Forecast., 35, 2255–2278, https://doi.org/10.1175/WAF-D-20-0101.1, 2020. a, b
Frehlich, R. G. and Kavaya, M. J.: Coherent laser radar performance for general
atmospheric refractive turbulence, Appl. Optics, 30, 5325–5352,
https://doi.org/10.1364/AO.30.005325, 1991. a
Gadde, S. N. and Stevens, R. J. A. M.: Effect of low-level jet height on wind
farm performance, J. Renew. Sustain. Ener., 13, 013305,
https://doi.org/10.1063/5.0026232, 2021. a
Gebauer, J. G., Shapiro, A., Fedorovich, E., and Klein, P.: Convection
initiation caused by heterogeneous low-level jets over the Great Plains,
Mon. Weather Rev., 146, 2615–2637, https://doi.org/10.1175/MWR-D-18-0002.1, 2018. a
Gultepe, I., Tardif, R., Michaelides, S., Cermak, J., Bott, A., Muller, M.,
Pagowski, M., Hansen, B., Ellrod, G., Jacobs, W., Toth, G., and Cober, S.:
Fog research: A review of past achievements and future perspectives, Pure
Appl. Geophys., 164, 1121–1159, 2007. a
Hersbach, H.: Comparison of C-Band scatterometer CMOD5.N equivalent neutral
winds with ECMWF, J. Atmos. Ocean. Tech., 27, 721–736,
https://doi.org/10.1175/2009JTECHO698.1, 2010. a
Holleman, I.: Quality Control and Verification of Weather Radar Wind Profiles,
J. Atmos. Ocean. Tech., 22, 1541–1550, https://doi.org/10.1175/JTECH1781.1,
2005. a
Houchi, K., Stoffelen, A., Marseille, G. J., and De Kloe, J.: Comparison of
wind and wind shear climatologies derived from high-resolution radiosondes
and the ECMWF model, J. Geophys. Res.-Atmos., 115, D22123,
https://doi.org/10.1029/2009JD013196, 2010. a, b
Klaas-Witt, T. and Emeis, S.: The five main influencing factors for lidar errors in complex terrain, Wind Energ. Sci., 7, 413–431, https://doi.org/10.5194/wes-7-413-2022, 2022. a
Kojo, H., Leviäkangas, P., Molarius, R., and Tuominen, A.: Extreme weather
impacts on transport systems, Tech. rep., VTT Working Papers No. 168,
https://publications.vtt.fi/pdf/workingpapers/2011/W168.pdf
(last access: 22 March 2022), 2011. a
Kurita, H., Sasaki, K., Muroga, H., Ueda, H., and Wakamatsu, S.: Long-range
transport of air pollution under light gradient wind conditions, J. Appl. Meteorol. Clim., 24, 425–434,
https://doi.org/10.1175/1520-0450(1985)024<0425:LRTOAP>2.0.CO;2, 1985. a
Lew, D., Milligan, M., Jordan, G., and Piwko, R.: Value of wind power
forecasting, in: Proc. of the 91st American Meteorological Society Annual
Meeting, the Second Conference on Weather, Climate, and the New Energy
Economy, Washington, DC,
https://www.osti.gov/biblio/1011280 (last access: 3 May 2022), 2011. a
Li, J., Sun, J., Zhou, M., Cheng, Z., Li, Q., Cao, X., and Zhang, J.: Observational analyses of dramatic developments of a severe air pollution event in the Beijing area, Atmos. Chem. Phys., 18, 3919–3935, https://doi.org/10.5194/acp-18-3919-2018, 2018. 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
Mass, C. F., Ovens, D., Westrick, K., and Colle, B. A.: Does increasing
horizontal resolution produce more skillful forecasts?: the results of two
years of real-time Numerical Weather Prediction over the Pacific
Northwest, B. Am. Meteorol. Soc., 83, 407–430, 2002. a
Mather, J. H., Turner, D. D., and Ackerman, T. P.: Scientific maturation of the
ARM Program, Meteorol. Monogr., 57, 4.1–4.19,
https://doi.org/10.1175/AMSMONOGRAPHS-D-15-0053.1, 2016. a
Newsom, R. K., Sivaraman, C., Shippert, T. R., and Riihimaki, L. D.: Doppler
Lidar Wind Value-Added Product, Tech. rep., DOE ARM Climate Research
Facility, Washington, DC, United States, https://doi.org/10.2172/1238069, 2015. a, b
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
Nijhuis, A. C. P. O., Thobois, L. P., Barbaresco, F., Haan, S. D.,
Dolfi-Bouteyre, A., Kovalev, D., Krasnov, O. A., Vanhoenacker-Janvier, D.,
Wilson, R., and Yarovoy, A. G.: Wind hazard and turbulence monitoring at
airports with lidar, radar and mode-S downlinks: the UFO Project, B. Am. Meteorol. Soc., 99, 2275–2294, 2018. a
O'Connor, E. J.: NWP model data (ECMWF IFS) for Pentikäinen et al. (2022) “Evaluating wind profiles in a numerical weather prediction model with Doppler lidar”, compiled by O'connor, E. J., Finnish Meteorological Institute [data set], https://doi.org/10.23728/FMI-B2SHARE.B14B1DF4A83F4C7DBB54BADC2EEF607A, 2022. a
Olson, J., Kenyon, J., Djalalova, I., Bianco, L., Turner, D., Pichugina, Y.,
Choukulkar, A., Toy, M., Brown, J., Angevine, W., Akish, E., Bao, J.-W.,
Jimenez, P., Kosovic, B., Lundquist, K., Draxl, C., Lundquist, J., McCaa, J.,
McCaffrey, K., and Cline, J.: Improving wind energy forecasting through
Numerical Weather Prediction model development, B. Am. Meteorol. Soc.,
100, 2201–2220, https://doi.org/10.1175/BAMS-D-18-0040.1, 2019. a, b
Ortiz-Amezcua, P.: Atmospheric profiling based on aerosol and Doppler lidar,
PhD thesis, Universidad de Granada,
http://hdl.handle.net/10481/57771 (last access: 14 March 2022), 2019. 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
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, d
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
Pennelly, C. and Reuter, G.: Verification of the Weather Research and
Forecasting Model when forecasting daily surface conditions in Southern
Alberta, Atmos.-Ocean, 55, 31–41, https://doi.org/10.1080/07055900.2017.1282345,
2017.
a
Pentikäinen, P., O'Connor, E. J., Manninen, A. J., and Ortiz-Amezcua, P.: Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar, Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, 2020. a
Pentikäinen, P. and O'Connor, E. J.: Processing code for gmd-2022-150, Zenodo
[code], https://doi.org/10.5281/zenodo.7235694, 2022. a
Pichugina, Y. L., Banta, R. M., Olson, J. B., Carley, J. R., Marquis, M. C.,
Brewer, W. A., Wilczak, J. M., Djalalova, I., Bianco, L., James, E. P.,
Benjamin, S. G., and Cline, J.: Assessment of NWP Forecast Models in
Simulating Offshore Winds through the Lower Boundary Layer by Measurements
from a Ship-Based Scanning Doppler Lidar, Mon. Weather Rev., 145, 4277–4301,
https://doi.org/10.1175/MWR-D-16-0442.1, 2017. a
Rahlves, C., Beyrich, F., and Raasch, S.: Scan strategies for wind profiling with Doppler lidar – an large-eddy simulation (LES)-based evaluation, Atmos. Meas. Tech., 15, 2839–2856, https://doi.org/10.5194/amt-15-2839-2022, 2022. a
Robey, R. and Lundquist, J. K.: Behavior and mechanisms of Doppler wind lidar error in varying stability regimes, Atmos. Meas. Tech., 15, 4585–4622, https://doi.org/10.5194/amt-15-4585-2022, 2022. a
Salonen, K., Järvinen, H., Järvenoja, S., Niemelä, S., and Eresmaa, R.:
Doppler radar radial wind data in NWP model validation, Meteorol. Appl., 15,
97–102, https://doi.org/10.1002/met.47, 2008. a
Sekuła, P., Bokwa, A., Bartyzel, J., Bochenek, B., Chmura, Ł., Gałkowski, M., and Zimnoch, M.: Measurement report: Effect of wind shear on PM10 concentration vertical structure in the urban boundary layer in a complex terrain, Atmos. Chem. Phys., 21, 12113–12139, https://doi.org/10.5194/acp-21-12113-2021, 2021. a
Skok, G. and Hladnik, V.: Verification of gridded wind forecasts in complex
alpine terrain: a new wind verification methodology based on the neighborhood
approach, Mon. Weather Rev., 146, 63–75, https://doi.org/10.1175/MWR-D-16-0471.1,
2018. a, b
Song, J., Liao, K., Coulter, R. L., and Lesht, B. M.: Climatology of the
low-level jet at the Southern Great Plains atmospheric boundary layer
experiments site, J. Appl. Meteorol., 44, 1593–1606,
https://doi.org/10.1175/JAM2294.1, 2005. a
Tuononen, M., O’Connor, E. J., Sinclair, V. A., and Vakkari, V.: Low-level
jets over Utö, Finland, based on Doppler lidar observations, J. Appl. Meteorol. Clim., 56, 2577–2594, https://doi.org/10.1175/JAMC-D-16-0411.1, 2017. a
University of Granada IISTA-CEAMA: Doppler lidar wind profiles from Granada,
compiled by: Ortiz-Amezcua, P. and Alados-Arboledas, L., Zenodo [data set],
https://doi.org/10.5281/zenodo.6628923, 2022. a
Short summary
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.
We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We...