Articles | Volume 9, issue 4
https://doi.org/10.5194/wes-9-821-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-9-821-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Apr 2024
Research article |
| 08 Apr 2024
| 08 Apr 2024
Machine learning methods to improve spatial predictions of coastal wind speed profiles and low-level jets using single-level ERA5 data
Christoffer Hallgren
CORRESPONDING AUTHOR
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Jeanie A. Aird
CORRESPONDING AUTHOR
Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA
Stefan Ivanell
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Heiner Körnich
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Ville Vakkari
Finnish Meteorological Institute, Helsinki, Finland
Atmospheric Chemistry Research Group, Chemical Resource Beneficiation, North-West University, Potchefstroom, South Africa
Rebecca J. Barthelmie
Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA
Sara C. Pryor
Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York, USA
Erik Sahlée
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
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Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
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Low-level jets (LLJs) are pronounced maxima in wind speed profiles affecting wind turbine performance and longevity. We present a climatology of LLJs over Iowa using output from the Weather Research and Forecasting (WRF) model and determine the rotor plane conditions when they occur. LLJ characteristics are highly sensitive to the identification criteria applied, and different (unique) LLJs are extracted with each criterion. LLJ characteristics also vary with different model output resolution.
Frederick W. Letson, Rebecca J. Barthelmie, Kevin I. Hodges, and Sara C. Pryor
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Janne Lampilahti, Katri Leino, Antti Manninen, Pyry Poutanen, Anna Franck, Maija Peltola, Paula Hietala, Lisa Beck, Lubna Dada, Lauriane Quéléver, Ronja Öhrnberg, Ying Zhou, Madeleine Ekblom, Ville Vakkari, Sergej Zilitinkevich, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 21, 7901–7915, https://doi.org/10.5194/acp-21-7901-2021, https://doi.org/10.5194/acp-21-7901-2021, 2021
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Stephanie Bohlmann, Xiaoxia Shang, Ville Vakkari, Elina Giannakaki, Ari Leskinen, Kari E. J. Lehtinen, Sanna Pätsi, and Mika Komppula
Atmos. Chem. Phys., 21, 7083–7097, https://doi.org/10.5194/acp-21-7083-2021, https://doi.org/10.5194/acp-21-7083-2021, 2021
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Measurements of the multi-wavelength Raman polarization lidar PollyXT and a Halo Photonics StreamLine Doppler lidar have been combined with measurements of pollen type and concentration using a traditional pollen trap at the rural forest site in Vehmasmäki, Finland. Depolarization ratios were measured at three wavelengths. High depolarization ratios were detected during an event with high birch and spruce pollen concentrations and a wavelength dependence of the depolarization ratio was observed.
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.
Evgenia Belova, Peter Voelger, Sheila Kirkwood, Susanna Hagelin, Magnus Lindskog, Heiner Körnich, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 14, 2813–2825, https://doi.org/10.5194/amt-14-2813-2021, https://doi.org/10.5194/amt-14-2813-2021, 2021
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We validate horizontal wind measurements at altitudes of 0.5–14 km made with atmospheric radars: ESRAD located near Kiruna in the Swedish Arctic and MARA at the Indian research station Maitri in Antarctica, by comparison with radiosondes, the regional model HARMONIE-AROME and the ECMWF ERA5 reanalysis. Good agreement was found in general, and radar bias and uncertainty were estimated. These radars are planned to be used for validation of winds measured by lidar by the ESA satellite Aeolus.
David Brus, Jani Gustafsson, Ville Vakkari, Osku Kemppinen, Gijs de Boer, and Anne Hirsikko
Atmos. Chem. Phys., 21, 517–533, https://doi.org/10.5194/acp-21-517-2021, https://doi.org/10.5194/acp-21-517-2021, 2021
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This paper summarizes Finnish Meteorological Institute and Kansas State University unmanned aerial vehicle measurements during the summer 2018 Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) campaign in the San Luis Valley, providing an overview of the rotorcraft deployed, payloads, scientific goals and flight strategies and presenting observations of atmospheric thermodynamics and aerosol and gas parameters in the vertical column.
Marta Wenta, David Brus, Konstantinos Doulgeris, Ville Vakkari, and Agnieszka Herman
Earth Syst. Sci. Data, 13, 33–42, https://doi.org/10.5194/essd-13-33-2021, https://doi.org/10.5194/essd-13-33-2021, 2021
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Representations of the atmospheric boundary layer over sea ice are a challenge for numerical weather prediction models. To increase our understanding of the relevant processes, a field campaign was carried out over the sea ice in the Baltic Sea from 27 February to 2 March 2020. Observations included 27 unmanned aerial vehicle flights, four photogrammetry missions, and shore-based automatic weather station and lidar wind measurements. The dataset obtained is used to validate model results.
Søren Juhl Andersen, Simon-Philippe Breton, Björn Witha, Stefan Ivanell, and Jens Nørkær Sørensen
Wind Energ. Sci., 5, 1689–1703, https://doi.org/10.5194/wes-5-1689-2020, https://doi.org/10.5194/wes-5-1689-2020, 2020
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The complexity of wind farm operation increases as the wind farms get larger and larger. Therefore, researchers from three universities have simulated numerous different large wind farms as part of an international benchmark. The study shows how simple engineering models can capture the general trends, but high-fidelity simulations are required in order to quantify the variability and uncertainty associated with power production of the wind farms and hence the potential profitability and risks.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
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The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Jill S. Johnson, Leighton A. Regayre, Masaru Yoshioka, Kirsty J. Pringle, Steven T. Turnock, Jo Browse, David M. H. Sexton, John W. Rostron, Nick A. J. Schutgens, Daniel G. Partridge, Dantong Liu, James D. Allan, Hugh Coe, Aijun Ding, David D. Cohen, Armand Atanacio, Ville Vakkari, Eija Asmi, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 9491–9524, https://doi.org/10.5194/acp-20-9491-2020, https://doi.org/10.5194/acp-20-9491-2020, 2020
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We use over 9000 monthly aggregated grid-box measurements of aerosol to constrain the uncertainty in the HadGEM3-UKCA climate model. Measurements of AOD, PM2.5, particle number concentrations, sulfate and organic mass concentrations are compared to 1 million
variantsof the model using an implausibility metric. Despite many compensating effects in the model, the procedure constrains the probability distributions of many parameters, and direct radiative forcing uncertainty is reduced by 34 %.
Henrik Asmuth, Hugo Olivares-Espinosa, and Stefan Ivanell
Wind Energ. Sci., 5, 623–645, https://doi.org/10.5194/wes-5-623-2020, https://doi.org/10.5194/wes-5-623-2020, 2020
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The presented work investigates the potential of the lattice Boltzmann method (LBM) for numerical simulations of wind turbine wakes. The LBM is a rather novel, alternative approach for computational fluid dynamics (CFD) that allows for significantly faster simulations. The study shows that the method provides similar results when compared to classical CFD approaches while only requiring a fraction of the computational demand.
Marcus B. Wallin, Joachim Audet, Mike Peacock, Erik Sahlée, and Mattias Winterdahl
Biogeosciences, 17, 2487–2498, https://doi.org/10.5194/bg-17-2487-2020, https://doi.org/10.5194/bg-17-2487-2020, 2020
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Here we show that small streams draining agricultural areas are potential hotspots for emissions of CO2 to the atmosphere. We further conclude that the variability in stream CO2 concentration over time is very high, caused by variations in both water discharge and primary production. Given the observed high levels of CO2 and its temporally variable nature, agricultural streams clearly need more attention in order to understand and incorporate these dynamics in large-scale extrapolations.
Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Wind Energ. Sci., 5, 331–347, https://doi.org/10.5194/wes-5-331-2020, https://doi.org/10.5194/wes-5-331-2020, 2020
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Wind turbine blade leading edge erosion (LEE) is potentially a significant source of energy loss and expense for wind farm operators. This study presents a novel approach to characterizing LEE potential from precipitation across the contiguous USA based on publicly available National Weather Service dual-polarization RADAR data. The approach is described in detail and illustrated using six locations distributed across parts of the USA that have substantial wind turbine deployments.
Matti Räsänen, Mika Aurela, Ville Vakkari, Johan P. Beukes, Juha-Pekka Tuovinen, Pieter G. Van Zyl, Miroslav Josipovic, Stefan J. Siebert, Tuomas Laurila, Markku Kulmala, Lauri Laakso, Janne Rinne, Ram Oren, and Gabriel Katul
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-651, https://doi.org/10.5194/hess-2019-651, 2020
Revised manuscript not accepted
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The annual ET is approximately equal to precipitation during six measured years for grazed savanna grassland. The computed annual transpiration was highly constrained when rainfall was near or above the long-term mean but was reduced during severe drought year. The developed methodologies can be used in a wide range of arid and semi-arid ecosystems.
Arnaud P. Praplan, Toni Tykkä, Dean Chen, Michael Boy, Ditte Taipale, Ville Vakkari, Putian Zhou, Tuukka Petäjä, and Heidi Hellén
Atmos. Chem. Phys., 19, 14431–14453, https://doi.org/10.5194/acp-19-14431-2019, https://doi.org/10.5194/acp-19-14431-2019, 2019
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Our study shows that, despite our best efforts and recent progress, our knowledge of the chemical composition of the air under the canopy of a boreal forest still cannot be fully characterized. The discrepancy between the measured total reactivity of the air and the reactivity derived from the known chemical composition highlights the need to better understand the emissions from vegetation, but also other sources, such as the forest soil.
Simo Hakala, Mansour A. Alghamdi, Pauli Paasonen, Ville Vakkari, Mamdouh I. Khoder, Kimmo Neitola, Lubna Dada, Ahmad S. Abdelmaksoud, Hisham Al-Jeelani, Ibrahim I. Shabbaj, Fahd M. Almehmadi, Anu-Maija Sundström, Heikki Lihavainen, Veli-Matti Kerminen, Jenni Kontkanen, Markku Kulmala, Tareq Hussein, and Antti-Pekka Hyvärinen
Atmos. Chem. Phys., 19, 10537–10555, https://doi.org/10.5194/acp-19-10537-2019, https://doi.org/10.5194/acp-19-10537-2019, 2019
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Atmospheric aerosols have significant effects on human health and the climate. A large fraction of these aerosols originate from new particle formation, where atmospheric vapors form small nanosized particles that grow into larger sizes, thus becoming climatically relevant. We show that large amounts of fast-growing particles are formed frequently at a site located in western Saudi Arabia and that these particles are likely connected to strong nearby emissions from human activities.
Rebecca J. Barthelmie and Sara C. Pryor
Atmos. Meas. Tech., 12, 3463–3484, https://doi.org/10.5194/amt-12-3463-2019, https://doi.org/10.5194/amt-12-3463-2019, 2019
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Wakes are volumes of air with low wind speed that form downwind of wind turbines. Their properties and behaviour determine optimal turbine spacing in wind farms. We use scanning Doppler lidar to accurately and precisely measure wake characteristics at a complex terrain site in Portugal. We develop and apply an automatic processing algorithm to detect wakes and quantify their characteristics. In higher wind speeds, the wake centres are lower. Wake centres are also lower in convective conditions.
Frederick Letson, Rebecca J. Barthelmie, Weifei Hu, and Sara C. Pryor
Atmos. Chem. Phys., 19, 3797–3819, https://doi.org/10.5194/acp-19-3797-2019, https://doi.org/10.5194/acp-19-3797-2019, 2019
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Wind gusts are a key driver of aerodynamic loading, and common approximations used to describe wind gust behavior may not be appropriate in complex terrain at heights relevant to wind turbines and other structures. High-resolution observations from sonic anemometers and vertically pointing Doppler lidars collected in the Perdigão experiment are analyzed to provide a foundation for improved wind gust characterization in complex terrain.
Ville Vakkari, Antti J. Manninen, Ewan J. O'Connor, Jan H. Schween, Pieter G. van Zyl, and Eleni Marinou
Atmos. Meas. Tech., 12, 839–852, https://doi.org/10.5194/amt-12-839-2019, https://doi.org/10.5194/amt-12-839-2019, 2019
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Commercially available Doppler lidars have been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more.
Stefan Ivanell, Johan Arnqvist, Matias Avila, Dalibor Cavar, Roberto Aurelio Chavez-Arroyo, Hugo Olivares-Espinosa, Carlos Peralta, Jamal Adib, and Björn Witha
Wind Energ. Sci., 3, 929–946, https://doi.org/10.5194/wes-3-929-2018, https://doi.org/10.5194/wes-3-929-2018, 2018
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This article describes a study in which modellers were challenged to compute the wind at a forested site with moderately complex topography. The target was to match the measured wind profile at one exact location for three directions. The input to the models consisted of detailed information on forest densities and ground height. Overall, the article gives an overview of how well different types of models are able to capture the flow physics at a moderately complex forested site.
Tracey Leah Laban, Pieter Gideon van Zyl, Johan Paul Beukes, Ville Vakkari, Kerneels Jaars, Nadine Borduas-Dedekind, Miroslav Josipovic, Anne Mee Thompson, Markku Kulmala, and Lauri Laakso
Atmos. Chem. Phys., 18, 15491–15514, https://doi.org/10.5194/acp-18-15491-2018, https://doi.org/10.5194/acp-18-15491-2018, 2018
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Surface O3 was measured at four sites in the north-eastern interior of South Africa, which revealed that O3 is a regional problem in continental South Africa, with elevated O3 levels found at rural background and industrial sites. Increased O3 concentrations were associated with high CO levels predominantly related to regional biomass burning, while the O3 production regime was established to be predominantly VOC limited. Increased O3 is associated with strong seasonality of precursor sources.
Tuomo Nieminen, Veli-Matti Kerminen, Tuukka Petäjä, Pasi P. Aalto, Mikhail Arshinov, Eija Asmi, Urs Baltensperger, David C. S. Beddows, Johan Paul Beukes, Don Collins, Aijun Ding, Roy M. Harrison, Bas Henzing, Rakesh Hooda, Min Hu, Urmas Hõrrak, Niku Kivekäs, Kaupo Komsaare, Radovan Krejci, Adam Kristensson, Lauri Laakso, Ari Laaksonen, W. Richard Leaitch, Heikki Lihavainen, Nikolaos Mihalopoulos, Zoltán Németh, Wei Nie, Colin O'Dowd, Imre Salma, Karine Sellegri, Birgitta Svenningsson, Erik Swietlicki, Peter Tunved, Vidmantas Ulevicius, Ville Vakkari, Marko Vana, Alfred Wiedensohler, Zhijun Wu, Annele Virtanen, and Markku Kulmala
Atmos. Chem. Phys., 18, 14737–14756, https://doi.org/10.5194/acp-18-14737-2018, https://doi.org/10.5194/acp-18-14737-2018, 2018
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Atmospheric aerosols have diverse effects on air quality, human health, and global climate. One important source of aerosols is their formation via nucleation and growth in the atmosphere. We have analyzed long-term observations of regional new particle formation events around the globe and provide a comprehensive view on the characteristics of this phenomenon in diverse environments. The results are useful in developing more realistic representation of atmospheric aerosols in global models.
Jennie Molinder, Heiner Körnich, Esbjörn Olsson, Hans Bergström, and Anna Sjöblom
Wind Energ. Sci., 3, 667–680, https://doi.org/10.5194/wes-3-667-2018, https://doi.org/10.5194/wes-3-667-2018, 2018
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This study shows that using probabilistic forecasting can improve next-day production forecasts for wind energy in cold climates. Wind turbines can suffer from severe production losses due to icing on the turbine blades. Short-range forecasts including the icing-related production losses are therefore valuable when planning for next-day energy production. Probabilistic forecasting can also provide a likelihood for icing and icing-related production losses.
Heidi Hellén, Arnaud P. Praplan, Toni Tykkä, Ilona Ylivinkka, Ville Vakkari, Jaana Bäck, Tuukka Petäjä, Markku Kulmala, and Hannele Hakola
Atmos. Chem. Phys., 18, 13839–13863, https://doi.org/10.5194/acp-18-13839-2018, https://doi.org/10.5194/acp-18-13839-2018, 2018
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Exceptionally large ambient air concentration datasets of VOCs were measured in a boreal forest. For the first time concentration of the main sesquiterpene (β-caryophyllene) emitted by the local trees was also measured. Sesquiterpenes were found to have a major impact on local atmospheric chemistry, even though their concentrations were 30 times lower than the monoterpene concentrations. In addition, sesquiterpenes are expected to have a high impact on local secondary organic aerosol production.
Sara C. Pryor, Tristan J. Shepherd, and Rebecca J. Barthelmie
Wind Energ. Sci., 3, 651–665, https://doi.org/10.5194/wes-3-651-2018, https://doi.org/10.5194/wes-3-651-2018, 2018
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The interannual variability (IAV) of annual energy production (AEP) from wind turbines due to IAV in wind speeds from proposed wind farms plays a key role in dictating project financing but is only poorly constrained. This study provides improved quantification of IAV over eastern N. America using purpose-performed long-term numerical simulations. It may be appropriate to reduce the IAV applied to preconstruction AEP estimates, which would decrease the cost of capital for wind farm developments.
Tomas Landelius, Magnus Lindskog, Heiner Körnich, and Sandra Andersson
Adv. Sci. Res., 15, 39–44, https://doi.org/10.5194/asr-15-39-2018, https://doi.org/10.5194/asr-15-39-2018, 2018
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During recent years the strong decrease in the prices of solar panels has lead to an increasing interest in harvesting solar energy. In this paper solar radiation forecasts from a global and a regional numerical weather prediction model are compared. The result is that regional ensemble models can indeed provide added value compared to global models when it comes to forecasting solar radiation available for power production.
Nikolaos Simisiroglou, Heracles Polatidis, and Stefan Ivanell
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2018-8, https://doi.org/10.5194/wes-2018-8, 2018
Preprint withdrawn
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The aim of the present study is to perform a comparative analysis of two actuator disc methods (ACD) and two analytical wake models for wind farm power production assessment. To do so wind turbine power production data from the Lillgrund offshore wind farm in Sweden is used. The measured power production for individual wind turbines is compared with results from simulations, done in the WindSim software.
Paula Doubrawa, Alex Montornès, Rebecca J. Barthelmie, Sara C. Pryor, and Pau Casso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2017-61, https://doi.org/10.5194/wes-2017-61, 2018
Preprint withdrawn
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We perform time-resolved, high-resolution simulations of the atmospheric boundary layer with a numerical weather prediction model. The downscaling is done within the model by defining nested domains, and we investigate different ways of treating turbulence modeling at intermediate spatial scales in which traditional turbulence parameterizations are inadequate. We focus on quantities of interest to wind energy and compare the simulations with measurements collected at a complex-terrain site.
Sara C. Pryor, Ryan C. Sullivan, and Justin T. Schoof
Atmos. Chem. Phys., 17, 14457–14471, https://doi.org/10.5194/acp-17-14457-2017, https://doi.org/10.5194/acp-17-14457-2017, 2017
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The air temperature and water vapor content are increasing globally due to the increased concentration of "heat-trapping" (greenhouse) gases. But not all regions are warming at the same rate. This analysis is designed to improve understanding of the causes of recent trends and year-to-year variability in summertime heat indices over the eastern US and to present a new model that can be used to make projections of future events that may cause loss of life and/or decreased human well-being.
Nikolaos Simisiroglou, Simon-Philippe Breton, and Stefan Ivanell
Wind Energ. Sci., 2, 587–601, https://doi.org/10.5194/wes-2-587-2017, https://doi.org/10.5194/wes-2-587-2017, 2017
Kgaugelo Euphinia Chiloane, Johan Paul Beukes, Pieter Gideon van Zyl, Petra Maritz, Ville Vakkari, Miroslav Josipovic, Andrew Derick Venter, Kerneels Jaars, Petri Tiitta, Markku Kulmala, Alfred Wiedensohler, Catherine Liousse, Gabisile Vuyisile Mkhatshwa, Avishkar Ramandh, and Lauri Laakso
Atmos. Chem. Phys., 17, 6177–6196, https://doi.org/10.5194/acp-17-6177-2017, https://doi.org/10.5194/acp-17-6177-2017, 2017
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This paper presents atmospheric black carbon (BC) data collected in South Africa (SA). In general, BC level were higher than in the developed world. At one site, five sources were identified, with household combustion as well as savannah and grassland fires the most significant sources during winter and spring, while coal-fired power stations, pyrometallurgical smelters and traffic contributed year round.
Andrew D. Venter, Pieter G. van Zyl, Johan P. Beukes, Micky Josipovic, Johan Hendriks, Ville Vakkari, and Lauri Laakso
Atmos. Chem. Phys., 17, 4251–4263, https://doi.org/10.5194/acp-17-4251-2017, https://doi.org/10.5194/acp-17-4251-2017, 2017
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Size-resolved trace metal concentrations were determined at a regional background site impacted by the major pollutant source regions in the interior of South Africa, which include a region holding a large number of pyrometallurgical smelters. ≥70% of trace metal species were in the smaller size fractions, indicating the influence of industrial activities, while the influence of wind-blown dust was reflected in the PM2.5–10 size fraction. Annual average Ni and As exceeded European standards.
Matti Räsänen, Mika Aurela, Ville Vakkari, Johan P. Beukes, Juha-Pekka Tuovinen, Pieter G. Van Zyl, Miroslav Josipovic, Andrew D. Venter, Kerneels Jaars, Stefan J. Siebert, Tuomas Laurila, Janne Rinne, and Lauri Laakso
Biogeosciences, 14, 1039–1054, https://doi.org/10.5194/bg-14-1039-2017, https://doi.org/10.5194/bg-14-1039-2017, 2017
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This study presents measurements of carbon dioxide exchange between the atmosphere and a grazed savanna grassland ecosystem for 3 years. We find that the yearly variation in carbon dioxide balance is largely determined by the changes in the early wet season balance (September to November) and in the mid-growing season balance (December to January).
Paola Crippa, Ryan C. Sullivan, Abhinav Thota, and Sara C. Pryor
Atmos. Chem. Phys., 17, 1511–1528, https://doi.org/10.5194/acp-17-1511-2017, https://doi.org/10.5194/acp-17-1511-2017, 2017
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Here we quantify WRF-CHEM sensitivity in simulating meteorological, chemical and aerosol properties as a function of spatial resolution.
We demonstrate that WRF-Chem at high resolution improves model performance of meteorological and gas-phase parameters and of mean and extreme aerosol properties over North America. A dry bias in specific humidity and precipitation in the coarse simulations is identified as cause of the better performance of the high-resolution simulations.
Kerneels Jaars, Pieter G. van Zyl, Johan P. Beukes, Heidi Hellén, Ville Vakkari, Micky Josipovic, Andrew D. Venter, Matti Räsänen, Leandra Knoetze, Dirk P. Cilliers, Stefan J. Siebert, Markku Kulmala, Janne Rinne, Alex Guenther, Lauri Laakso, and Hannele Hakola
Atmos. Chem. Phys., 16, 15665–15688, https://doi.org/10.5194/acp-16-15665-2016, https://doi.org/10.5194/acp-16-15665-2016, 2016
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Biogenic volatile organic compounds (BVOCs) – important in tropospheric ozone and secondary organic aerosol formation – were measured at a savannah grassland in South Africa. Results presented are the most extensive for this type of landscape. Compared to other parts of the world, monoterpene levels were similar, while very low isoprene levels led to significantly lower total BVOC levels. BVOC levels were an order of magnitude lower compared to anthropogenic VOC levels measured at Welgegund.
H. Wang, R. J. Barthelmie, P. Doubrawa, and S. C. Pryor
Atmos. Meas. Tech., 9, 4123–4139, https://doi.org/10.5194/amt-9-4123-2016, https://doi.org/10.5194/amt-9-4123-2016, 2016
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This paper investigates how long a sampling duration of lidar measurements should be in order to accurately estimate radial velocity variance to obtain turbulence statistics. Using observations and statistical simulations, it is demonstrated that large probe volumes in lidar measurements increase the autocorrelation values, and consequently the uncertainty in radial velocity variance estimates. It is further shown that the random error can exceed 10 % for 30–60 min sampling duration.
Fanni Mylläri, Eija Asmi, Tatu Anttila, Erkka Saukko, Ville Vakkari, Liisa Pirjola, Risto Hillamo, Tuomas Laurila, Anna Häyrinen, Jani Rautiainen, Heikki Lihavainen, Ewan O'Connor, Ville Niemelä, Jorma Keskinen, Miikka Dal Maso, and Topi Rönkkö
Atmos. Chem. Phys., 16, 7485–7496, https://doi.org/10.5194/acp-16-7485-2016, https://doi.org/10.5194/acp-16-7485-2016, 2016
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The primary emissions of a coal-fired power plant were highly affected by the flue-gas cleaning technologies. The primary emission results were used as input values for a Gaussian plume model and the model correlated well with the atmospheric measurements from the flue-gas plume. Concentrations of newly formed particles in the flue gas plume were higher than the primary particle concentration, and thus the source of particle-forming precursors should be characterized in more detail.
Hui Wang, Rebecca J. Barthelmie, Sara C. Pryor, and Gareth. Brown
Atmos. Meas. Tech., 9, 1653–1669, https://doi.org/10.5194/amt-9-1653-2016, https://doi.org/10.5194/amt-9-1653-2016, 2016
Antti J. Manninen, Ewan J. O'Connor, Ville Vakkari, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 817–827, https://doi.org/10.5194/amt-9-817-2016, https://doi.org/10.5194/amt-9-817-2016, 2016
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Current commercially available Doppler lidars provide a cost-effective solution for measuring vertical and horizontal wind velocities, and the co- and cross-polarised backscatter profiles. However, the background noise behaviour becomes a limiting factor for the instrument sensitivity in low aerosol load regions. In this paper we present a correction method which can improve the data availability up to 50 % and greatly improves the calculation of turbulent properties in weak signal regimes.
E. Asmi, V. Kondratyev, D. Brus, T. Laurila, H. Lihavainen, J. Backman, V. Vakkari, M. Aurela, J. Hatakka, Y. Viisanen, T. Uttal, V. Ivakhov, and A. Makshtas
Atmos. Chem. Phys., 16, 1271–1287, https://doi.org/10.5194/acp-16-1271-2016, https://doi.org/10.5194/acp-16-1271-2016, 2016
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Aerosol number size distributions were measured in Arctic Russia continuously during 4 years. The particles' seasonal characteristics and sources were identified based on these data. In early spring, elevated concentrations were detected during episodes of Arctic haze and during days of secondary particle formation. In summer, Siberian forests biogenic emissions had a significant impact on particle number and mass. These are the first such results obtained from the region.
E. W. Butt, A. Rap, A. Schmidt, C. E. Scott, K. J. Pringle, C. L. Reddington, N. A. D. Richards, M. T. Woodhouse, J. Ramirez-Villegas, H. Yang, V. Vakkari, E. A. Stone, M. Rupakheti, P. S. Praveen, P. G. van Zyl, J. P. Beukes, M. Josipovic, E. J. S. Mitchell, S. M. Sallu, P. M. Forster, and D. V. Spracklen
Atmos. Chem. Phys., 16, 873–905, https://doi.org/10.5194/acp-16-873-2016, https://doi.org/10.5194/acp-16-873-2016, 2016
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We estimate the impact of residential emissions (cooking and heating) on atmospheric aerosol, human health, and climate. We find large contributions to annual mean ambient PM2.5 in residential sources regions resulting in significant but uncertain global premature mortality when key uncertainties in emission flux are considered. We show that residential emissions exert an uncertain global radiative effect and suggest more work is needed to characterise residential emissions climate importance.
P. Crippa, R. C. Sullivan, A. Thota, and S. C. Pryor
Atmos. Chem. Phys., 16, 397–416, https://doi.org/10.5194/acp-16-397-2016, https://doi.org/10.5194/acp-16-397-2016, 2016
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We evaluate the performance of high-resolution simulations of the Weather Research and Forecasting model coupled with Chemistry in capturing spatiotemporal variability of aerosol optical properties by comparison with ground- and space- based remote-sensing observations and investigate causes of model biases. This work contributes to assessing the model's ability to describe drivers of aerosol direct radiative forcing in the contemporary climate and to improving confidence in future projections.
F. Yu, G. Luo, S. C. Pryor, P. R. Pillai, S. H. Lee, J. Ortega, J. J. Schwab, A. G. Hallar, W. R. Leaitch, V. P. Aneja, J. N. Smith, J. T. Walker, O. Hogrefe, and K. L. Demerjian
Atmos. Chem. Phys., 15, 13993–14003, https://doi.org/10.5194/acp-15-13993-2015, https://doi.org/10.5194/acp-15-13993-2015, 2015
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The role of low-volatility organics in new particle formation (NPF) in the atmosphere is assessed. An empirical formulation in which formation rate is a function of the concentrations of sulfuric acid and low-volatility organics significantly overpredicts NPF in the summer.
Two different schemes predict quite different nucleation rates (including their spatial patterns), concentrations of cloud condensation nuclei, and aerosol first indirect radiative forcing in North America.
V. M. N. C. S. Vieira, E. Sahlée, P. Jurus, E. Clementi, H. Pettersson, and M. Mateus
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-15901-2015, https://doi.org/10.5194/bgd-12-15901-2015, 2015
Manuscript not accepted for further review
V. M. N. C. S. Vieira, E. Sahlée, P. Jurus, E. Clementi, H. Pettersson, and M. Mateus
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-15925-2015, https://doi.org/10.5194/bgd-12-15925-2015, 2015
Manuscript not accepted for further review
F. Kuik, A. Lauer, J. P. Beukes, P. G. Van Zyl, M. Josipovic, V. Vakkari, L. Laakso, and G. T. Feig
Atmos. Chem. Phys., 15, 8809–8830, https://doi.org/10.5194/acp-15-8809-2015, https://doi.org/10.5194/acp-15-8809-2015, 2015
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The numerical model WRF-Chem is used to estimate the contribution of anthropogenic emissions to BC, aerosol optical depth and atmospheric heating rates over southern Africa. An evaluation of the model with observational data including long-term BC measurements shows that the basic meteorology is reproduced reasonably well but simulated near-surface BC concentrations are underestimated by up to 50%. It is found that up to 100% of the BC in highly industrialized regions is of anthropogenic origin.
E. Giannakaki, A. Pfüller, K. Korhonen, T. Mielonen, L. Laakso, V. Vakkari, H. Baars, R. Engelmann, J. P. Beukes, P. G. Van Zyl, M. Josipovic, P. Tiitta, K. Chiloane, S. Piketh, H. Lihavainen, K. E. J. Lehtinen, and M. Komppula
Atmos. Chem. Phys., 15, 5429–5442, https://doi.org/10.5194/acp-15-5429-2015, https://doi.org/10.5194/acp-15-5429-2015, 2015
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In this study we summarize 1 year of Raman lidar observations over South Africa. The analyses of lidar measurements presented here could assist in bridging existing gaps in the knowledge of vertical distribution of aerosols above South Africa, since limited long-term data of this type are available for this region. For the first time, we have been able to cover the full seasonal cycle on geometrical characteristics and optical properties of free tropospheric aerosol layers in the region.
A.-M. Sundström, A. Nikandrova, K. Atlaskina, T. Nieminen, V. Vakkari, L. Laakso, J. P. Beukes, A. Arola, P. G. van Zyl, M. Josipovic, A. D. Venter, K. Jaars, J. J. Pienaar, S. Piketh, A. Wiedensohler, E. K. Chiloane, G. de Leeuw, and M. Kulmala
Atmos. Chem. Phys., 15, 4983–4996, https://doi.org/10.5194/acp-15-4983-2015, https://doi.org/10.5194/acp-15-4983-2015, 2015
V. Vakkari, E. J. O'Connor, A. Nisantzi, R. E. Mamouri, and D. G. Hadjimitsis
Atmos. Meas. Tech., 8, 1875–1885, https://doi.org/10.5194/amt-8-1875-2015, https://doi.org/10.5194/amt-8-1875-2015, 2015
J. Backman, A. Virkkula, V. Vakkari, J. P. Beukes, P. G. Van Zyl, M. Josipovic, S. Piketh, P. Tiitta, K. Chiloane, T. Petäjä, M. Kulmala, and L. Laakso
Atmos. Meas. Tech., 7, 4285–4298, https://doi.org/10.5194/amt-7-4285-2014, https://doi.org/10.5194/amt-7-4285-2014, 2014
S. C. Pryor, K. E. Hornsby, and K. A. Novick
Atmos. Chem. Phys., 14, 11985–11996, https://doi.org/10.5194/acp-14-11985-2014, https://doi.org/10.5194/acp-14-11985-2014, 2014
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What role do forests play in determining the concentration (and composition) of climate-relevant aerosol particles? This study seeks to address two aspects of this question. Firstly, we document high in-canopy removal of recently formed particles. Then we show evidence that growth rates of particles are a function of soil water availability via a reduction in canopy emissions of gases responsible for particle growth to climate-relevant sizes during drought conditions.
E. Podgrajsek, E. Sahlée, D. Bastviken, J. Holst, A. Lindroth, L. Tranvik, and A. Rutgersson
Biogeosciences, 11, 4225–4233, https://doi.org/10.5194/bg-11-4225-2014, https://doi.org/10.5194/bg-11-4225-2014, 2014
J. Ortega, A. Turnipseed, A. B. Guenther, T. G. Karl, D. A. Day, D. Gochis, J. A. Huffman, A. J. Prenni, E. J. T. Levin, S. M. Kreidenweis, P. J. DeMott, Y. Tobo, E. G. Patton, A. Hodzic, Y. Y. Cui, P. C. Harley, R. S. Hornbrook, E. C. Apel, R. K. Monson, A. S. D. Eller, J. P. Greenberg, M. C. Barth, P. Campuzano-Jost, B. B. Palm, J. L. Jimenez, A. C. Aiken, M. K. Dubey, C. Geron, J. Offenberg, M. G. Ryan, P. J. Fornwalt, S. C. Pryor, F. N. Keutsch, J. P. DiGangi, A. W. H. Chan, A. H. Goldstein, G. M. Wolfe, S. Kim, L. Kaser, R. Schnitzhofer, A. Hansel, C. A. Cantrell, R. L. Mauldin, and J. N. Smith
Atmos. Chem. Phys., 14, 6345–6367, https://doi.org/10.5194/acp-14-6345-2014, https://doi.org/10.5194/acp-14-6345-2014, 2014
K. Korhonen, E. Giannakaki, T. Mielonen, A. Pfüller, L. Laakso, V. Vakkari, H. Baars, R. Engelmann, J. P. Beukes, P. G. Van Zyl, A. Ramandh, L. Ntsangwane, M. Josipovic, P. Tiitta, G. Fourie, I. Ngwana, K. Chiloane, and M. Komppula
Atmos. Chem. Phys., 14, 4263–4278, https://doi.org/10.5194/acp-14-4263-2014, https://doi.org/10.5194/acp-14-4263-2014, 2014
P. Tiitta, V. Vakkari, P. Croteau, J. P. Beukes, P. G. van Zyl, M. Josipovic, A. D. Venter, K. Jaars, J. J. Pienaar, N. L. Ng, M. R. Canagaratna, J. T. Jayne, V.-M. Kerminen, H. Kokkola, M. Kulmala, A. Laaksonen, D. R. Worsnop, and L. Laakso
Atmos. Chem. Phys., 14, 1909–1927, https://doi.org/10.5194/acp-14-1909-2014, https://doi.org/10.5194/acp-14-1909-2014, 2014
A. Hirsikko, V. Vakkari, P. Tiitta, J. Hatakka, V.-M. Kerminen, A.-M. Sundström, J. P. Beukes, H. E. Manninen, M. Kulmala, and L. Laakso
Atmos. Chem. Phys., 13, 5523–5532, https://doi.org/10.5194/acp-13-5523-2013, https://doi.org/10.5194/acp-13-5523-2013, 2013
V. Vakkari, J. P. Beukes, H. Laakso, D. Mabaso, J. J. Pienaar, M. Kulmala, and L. Laakso
Atmos. Chem. Phys., 13, 1751–1770, https://doi.org/10.5194/acp-13-1751-2013, https://doi.org/10.5194/acp-13-1751-2013, 2013
L. Riuttanen, M. Dal Maso, G. de Leeuw, I. Riipinen, L. Sogacheva, V. Vakkari, L. Laakso, and M. Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-4289-2013, https://doi.org/10.5194/acpd-13-4289-2013, 2013
Revised manuscript has not been submitted
A.-P. Hyvärinen, V. Vakkari, L. Laakso, R. K. Hooda, V. P. Sharma, T. S. Panwar, J. P. Beukes, P. G. van Zyl, M. Josipovic, R. M. Garland, M. O. Andreae, U. Pöschl, and A. Petzold
Atmos. Meas. Tech., 6, 81–90, https://doi.org/10.5194/amt-6-81-2013, https://doi.org/10.5194/amt-6-81-2013, 2013
Related subject area
Thematic area: Wind and the atmosphere | Topic: Wind and turbulence
Converging profile relationships for offshore wind speed and turbulence intensity
A simple steady-state inflow model of the neutral and stable atmospheric boundary layer applied to wind turbine wake simulations
Influences of lidar scanning parameters on wind turbine wake retrievals in complex terrain
Experimental evaluation of wind turbine wake turbulence impacts on a general aviation aircraft
On the lidar-turbulence paradox and possible countermeasures
Underestimation of strong wind speeds offshore in ERA5: evidence, discussion and correction
Brief communication: A simple axial induction modification to the Weather Research and Forecasting Fitch wind farm parameterization
Impact of swell waves on atmospheric surface turbulence: wave–turbulence decomposition methods
The Actuator Farm Model for LES of Wind Farm-Induced Atmospheric Gravity Waves and Farm-Farm Interaction
Machine-learning-based estimate of the wind speed over complex terrain using the long short-term memory (LSTM) recurrent neural network
Offshore wind farms modify low-level jets
Method to predict the minimum measurement and experiment durations needed to achieve converged and significant results in a wind energy field experiment
Evaluation of wind farm parameterizations in the WRF model under different atmospheric stability conditions with high-resolution wake simulations
Renewable Energy Complementarity (RECom) maps – a comprehensive visualisation tool to support spatial diversification
Control-oriented modelling of wind direction variability
Observations of wind farm wake recovery at an operating wind farm
Offshore low-level jet observations and model representation using lidar buoy data off the California coast
Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign
The fractal turbulent–non-turbulent interface in the atmosphere
TOSCA – an open-source, finite-volume, large-eddy simulation (LES) environment for wind farm flows
Characterization of Local Wind Profiles: A Random Forest Approach for Enhanced Wind Profile Extrapolation
Quantitative comparison of power production and power quality onshore and offshore: a case study from the eastern United States
The wind farm pressure field
Understanding the impact of data gaps on long-term offshore wind resource estimates
Realistic turbulent inflow conditions for estimating the performance of a floating wind turbine
Brief communication: On the definition of the low-level jet
A decision-tree-based measure–correlate–predict approach for peak wind gust estimation from a global reanalysis dataset
Revealing inflow and wake conditions of a 6 MW floating turbine
Stochastic gradient descent for wind farm optimization
Modelling the impact of trapped lee waves on offshore wind farm power output
Applying a random time mapping to Mann-modeled turbulence for the generation of intermittent wind fields
From shear to veer: theory, statistics, and practical application
Quantification and correction of motion influence for nacelle-based lidar systems on floating wind turbines
Gaussian mixture models for the optimal sparse sampling of offshore wind resource
Dependence of turbulence estimations on nacelle lidar scanning strategies
Vertical extrapolation of Advanced Scatterometer (ASCAT) ocean surface winds using machine-learning techniques
An investigation of spatial wind direction variability and its consideration in engineering models
From gigawatt to multi-gigawatt wind farms: wake effects, energy budgets and inertial gravity waves investigated by large-eddy simulations
Investigations of correlation and coherence in turbulence from a large-eddy simulation
Validation of turbulence intensity as simulated by the Weather Research and Forecasting model off the US northeast coast
On the laminar–turbulent transition mechanism on megawatt wind turbine blades operating in atmospheric flow
Brief communication: A momentum-conserving superposition method applied to the super-Gaussian wind turbine wake model
Turbulence structures and entrainment length scales in large offshore wind farms
Effect of different source terms and inflow direction in atmospheric boundary modeling over the complex terrain site of Perdigão
Comparison of large eddy simulations against measurements from the Lillgrund offshore wind farm
Adjusted spectral correction method for calculating extreme winds in tropical-cyclone-affected water areas
The Jensen wind farm parameterization
Current and future wind energy resources in the North Sea according to CMIP6
Optimization of wind farm portfolios for minimizing overall power fluctuations at selective frequencies – a case study of the Faroe Islands
Evaluating the mesoscale spatio-temporal variability in simulated wind speed time series over northern Europe
Gus Jeans
Wind Energ. Sci., 9, 2001–2015, https://doi.org/10.5194/wes-9-2001-2024, https://doi.org/10.5194/wes-9-2001-2024, 2024
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An extensive set of met mast data offshore northwestern Europe are used to reduce uncertainty in offshore wind speed and turbulence intensity. The performance of widely used industry standard relationships is quantified, while some new empirical relationships are derived for practical application. Motivations include encouraging appropriate convergence of traditionally separate technical disciplines within the rapidly growing offshore wind energy industry.
Maarten Paul van der Laan, Mark Kelly, Mads Baungaard, Antariksh Dicholkar, and Emily Louise Hodgson
Wind Energ. Sci., 9, 1985–2000, https://doi.org/10.5194/wes-9-1985-2024, https://doi.org/10.5194/wes-9-1985-2024, 2024
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Wind turbines are increasing in size and operate more frequently above the atmospheric surface layer, which requires improved inflow models for numerical simulations of turbine interaction. In this work, a novel steady-state model of the atmospheric boundary layer (ABL) is introduced. Numerical wind turbine flow simulations subjected to shallow and tall ABLs are conducted, and the proposed model shows improved performance compared to other state-of-the-art steady-state models.
Rachel Robey and Julie K. Lundquist
Wind Energ. Sci., 9, 1905–1922, https://doi.org/10.5194/wes-9-1905-2024, https://doi.org/10.5194/wes-9-1905-2024, 2024
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Measurements of wind turbine wakes with scanning lidar instruments contain complex errors. We model lidars in a simulated environment to understand how and why the measured wake may differ from the true wake and validate the results with observational data. The lidar smooths out the wake, making it seem more spread out and the slowdown of the winds less pronounced. Our findings provide insights into best practices for accurately measuring wakes with lidar and interpreting observational data.
Jonathan D. Rogers
Wind Energ. Sci., 9, 1849–1868, https://doi.org/10.5194/wes-9-1849-2024, https://doi.org/10.5194/wes-9-1849-2024, 2024
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This paper describes the results of a flight experiment to assess the existence of potential safety risks to a general aviation aircraft from added turbulence in the wake of a wind turbine. A general aviation aircraft was flown through the wake of an operating wind turbine at different downwind distances. Results indicated that there were small increases in disturbances to the aircraft due to added turbulence in the wake, but they never approached levels that would pose a safety risk.
Alfredo Peña, Ginka Georgieva Yankova, and Vasiliki Mallini
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-108, https://doi.org/10.5194/wes-2024-108, 2024
Revised manuscript accepted for WES
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Lidars are vastly used in wind energy but most users struggle when interpreting lidar turbulence measures. Here we explain why is difficult to convert them into standard measurements. We show two ways to convert lidar to in-situ turbulence measurements, both using neural networks with one of them based on physics while the other is purely data driven. They show promising results when compared to high-quality turbulence measurements from a tall mast.
Rémi Gandoin and Jorge Garza
Wind Energ. Sci., 9, 1727–1745, https://doi.org/10.5194/wes-9-1727-2024, https://doi.org/10.5194/wes-9-1727-2024, 2024
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ERA5 has become the workhorse of most wind resource assessment applications, as it compares better with in situ measurements than other reanalyses. However, for design purposes, ERA5 suffers from a drawback: it underestimates strong wind speeds offshore (approx. from 10 m s−1). This is not widely discussed in the scientific literature. We address this bias and proposes a simple, robust correction. This article supports the growing need for use-case-specific validations of reanalysis datasets.
Lukas Vollmer, Balthazar Arnoldus Maria Sengers, and Martin Dörenkämper
Wind Energ. Sci., 9, 1689–1693, https://doi.org/10.5194/wes-9-1689-2024, https://doi.org/10.5194/wes-9-1689-2024, 2024
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This study proposes a modification to a well-established wind farm parameterization used in mesoscale models. The wind speed at the location of the turbine, which is used to calculate power and thrust, is corrected to approximate the free wind speed. Results show that the modified parameterization produces more accurate estimates of the turbine’s power curve.
Mostafa Bakhoday Paskyabi
Wind Energ. Sci., 9, 1631–1645, https://doi.org/10.5194/wes-9-1631-2024, https://doi.org/10.5194/wes-9-1631-2024, 2024
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The exchange of momentum and energy between the atmosphere and ocean depends on air–sea processes, especially wave-related ones. Precision in representing these interactions is vital for offshore wind turbine and farm design and operation. The development of a reliable wave–turbulence decomposition method to remove wave-induced interference from single-height wind measurements is essential for these applications and enhances our grasp of wind coherence within the wave boundary layer.
Sebastiano Stipa, Arjun Ajay, and Joshua Brinkerhoff
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-89, https://doi.org/10.5194/wes-2024-89, 2024
Revised manuscript accepted for WES
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This study presents the actuator farm model, a new method for modeling wind turbines within large wind farms. The model greatly reduces computational cost when compared to traditional actuator wind turbine models and is beneficial for studying flow around large wind farms as well as the interaction between multiple wind farms. Results obtained from numerical simulations show excellent agreement with past wind turbine models showing its utility for future large-scale wind farm simulations.
Cássia Maria Leme Beu and Eduardo Landulfo
Wind Energ. Sci., 9, 1431–1450, https://doi.org/10.5194/wes-9-1431-2024, https://doi.org/10.5194/wes-9-1431-2024, 2024
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Extrapolating the wind profile for complex terrain through the long short-term memory model outperformed the traditional power law methodology, which due to its universal nature cannot capture local features as the machine-learning methodology does. Moreover, considering the importance of investigating the wind potential and the need for alternative energy sources, it is motivating to find that a short observational campaign can produce better results than the traditional techniques.
Daphne Quint, Julie K. Lundquist, and David Rosencrans
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-48, https://doi.org/10.5194/wes-2024-48, 2024
Revised manuscript accepted for WES
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Offshore wind farms will be built along the east coast of the United States. Low-level jets (LLJs) – layers of fast winds at low altitudes – also occur here. LLJs provide wind resources and also influence moisture and pollution transport, so it is important to understand how they might change. We develop and validate an automated tool to detect LLJs, and compare one year of simulations with and without wind farms. Here, we describe LLJ characteristics and how they change with wind farms.
Daniel R. Houck, Nathaniel B. de Velder, David C. Maniaci, and Brent C. Houchens
Wind Energ. Sci., 9, 1189–1209, https://doi.org/10.5194/wes-9-1189-2024, https://doi.org/10.5194/wes-9-1189-2024, 2024
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Experiments offer incredible value to science, but results must come with an uncertainty quantification to be meaningful. We present a method to simulate a proposed experiment, calculate uncertainties, and determine the measurement duration (total time of measurements) and the experiment duration (total time to collect the required measurement data when including condition variability and time when measurement is not occurring) required to produce statistically significant and converged results.
Oscar García-Santiago, Andrea N. Hahmann, Jake Badger, and Alfredo Peña
Wind Energ. Sci., 9, 963–979, https://doi.org/10.5194/wes-9-963-2024, https://doi.org/10.5194/wes-9-963-2024, 2024
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This study compares the results of two wind farm parameterizations (WFPs) in the Weather Research and Forecasting model, simulating a two-turbine array under three atmospheric stabilities with large-eddy simulations. We show that the WFPs accurately depict wind speeds either near turbines or in the far-wake areas, but not both. The parameterizations’ performance varies by variable (wind speed or turbulent kinetic energy) and atmospheric stability, with reduced accuracy in stable conditions.
Til Kristian Vrana and Harald G. Svendsen
Wind Energ. Sci., 9, 919–932, https://doi.org/10.5194/wes-9-919-2024, https://doi.org/10.5194/wes-9-919-2024, 2024
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We developed new ways to plot comprehensive wind resource maps that show the revenue potential of different locations for future wind power developments. The relative capacity factor is introduced as an indicator showing the expected mean power output. The market value factor is introduced, which captures the expected mean market value relative to other wind parks. The Renewable Energy Complementarity (RECom) index combines the two into a single index, resulting in the RECom map.
Scott Dallas, Adam Stock, and Edward Hart
Wind Energ. Sci., 9, 841–867, https://doi.org/10.5194/wes-9-841-2024, https://doi.org/10.5194/wes-9-841-2024, 2024
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This review presents the current understanding of wind direction variability in the context of control-oriented modelling of wind turbines and wind farms in a manner suitable to a wide audience. Motivation comes from the significant and commonly seen yaw error of horizontal axis wind turbines, which carries substantial negative impacts on annual energy production and the levellised cost of wind energy. Gaps in the literature are identified, and the critical challenges in this area are discussed.
Raghavendra Krishnamurthy, Rob Newsom, Colleen Kaul, Stefano Letizia, Mikhail Pekour, Nicholas Hamilton, Duli Chand, Donna M. Flynn, Nicola Bodini, and Patrick Moriarty
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-29, https://doi.org/10.5194/wes-2024-29, 2024
Revised manuscript accepted for WES
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The growth of wind farms in the central United States in the last decade has been staggering. This study looked at how wind farms affect the recovery of wind wakes – the disturbed air behind wind turbines. In places like the US Great Plains, phenomena such as low-level jets can form, changing how wind farms work. We studied how wind wakes recover under different weather conditions using real-world data, which is important for making wind energy more efficient and reliable.
Lindsay M. Sheridan, Raghavendra Krishnamurthy, William I. Gustafson Jr., Ye Liu, Brian J. Gaudet, Nicola Bodini, Rob K. Newsom, and Mikhail Pekour
Wind Energ. Sci., 9, 741–758, https://doi.org/10.5194/wes-9-741-2024, https://doi.org/10.5194/wes-9-741-2024, 2024
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In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas and provided valuable year-long analyses of offshore low-level jet (LLJ) characteristics at heights relevant to wind turbines. In addition to the LLJ climatology, this work provides validation of LLJ representation in atmospheric models that are essential for assessing the potential energy yield of offshore wind farms.
Eliot Quon
Wind Energ. Sci., 9, 495–518, https://doi.org/10.5194/wes-9-495-2024, https://doi.org/10.5194/wes-9-495-2024, 2024
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Engineering models used to design wind farms generally do not account for realistic atmospheric conditions that can rapidly evolve from minute to minute. This paper uses a first-principles simulation technique to predict the performance of five wind turbines during a wind farm control experiment. Challenges included limited observations and atypical conditions. The simulation accurately predicts the aerodynamics of a turbine when it is situated partially within the wake of an upstream turbine.
Lars Neuhaus, Matthias Wächter, and Joachim Peinke
Wind Energ. Sci., 9, 439–452, https://doi.org/10.5194/wes-9-439-2024, https://doi.org/10.5194/wes-9-439-2024, 2024
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Future wind turbines reach unprecedented heights and are affected by wind conditions that have not yet been studied in detail. With increasing height, a transition to laminar conditions with a turbulent–non-turbulent interface (TNTI) becomes more likely. In this paper, the presence and fractality of this TNTI in the atmosphere are studied. Typical fractalities known from ideal laboratory and numerical studies and a frequent occurrence of the TNTI at heights of multi-megawatt turbines are found.
Sebastiano Stipa, Arjun Ajay, Dries Allaerts, and Joshua Brinkerhoff
Wind Energ. Sci., 9, 297–320, https://doi.org/10.5194/wes-9-297-2024, https://doi.org/10.5194/wes-9-297-2024, 2024
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In the current study, we introduce TOSCA (Toolbox fOr Stratified Convective Atmospheres), an open-source computational fluid dynamics (CFD) tool, and demonstrate its capabilities by simulating the flow around a large wind farm, operating in realistic flow conditions. This is one of the grand challenges of the present decade and can yield better insight into physical phenomena that strongly affect wind farm operation but which are not yet fully understood.
Farkhondeh Rouholahnejad and Julia Gottschall
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-178, https://doi.org/10.5194/wes-2023-178, 2024
Revised manuscript accepted for WES
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In wind energy, precise wind speed prediction at hub-height is vital. Our study in the Dutch North Sea reveals that the on-site trained random forest model outperforms the global reanalysis data, ERA5, in accuracy and precision. Trained within a 200 km range, the model effectively extends the wind speed vertically but experiences bias. It also outperforms corrected ERA5 in capturing wind speed variations and fine wind patterns, highlighting its potential for offshore wind resource assessment.
Rebecca Foody, Jacob Coburn, Jeanie A. Aird, Rebecca J. Barthelmie, and Sara C. Pryor
Wind Energ. Sci., 9, 263–280, https://doi.org/10.5194/wes-9-263-2024, https://doi.org/10.5194/wes-9-263-2024, 2024
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Using lidar-derived wind speed measurements at approx. 150 m height at onshore and offshore locations, we quantify the advantages of deploying wind turbines offshore in terms of the amount of electrical power produced and the higher reliability and predictability of the electrical power.
Ronald B. Smith
Wind Energ. Sci., 9, 253–261, https://doi.org/10.5194/wes-9-253-2024, https://doi.org/10.5194/wes-9-253-2024, 2024
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Recent papers have investigated the impact of turbine drag on local wind patterns, but these studies have not given a full explanation of the induced pressure field. The pressure field blocks and deflects the wind and in other ways modifies farm efficiency. Current gravity wave models are complex and provide no estimation tools. We dig deeper into the cause of the pressure field and provide approximate closed-form expressions for pressure field effects.
Martin Georg Jonietz Alvarez, Warren Watson, and Julia Gottschall
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-127, https://doi.org/10.5194/wes-2023-127, 2023
Revised manuscript accepted for WES
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Offshore wind measurements are often affected by gaps. We investigated how these gaps affect wind resource assessments and whether filling them reduces their effect. We find that the gap effect on the estimated long-term wind resource is lower than expected and that data gap filling does not significantly change the outcome. These results indicate a need to reduce current wind data availability requirements for offshore measurement campaigns.
Cédric Raibaudo, Jean-Christophe Gilloteaux, and Laurent Perret
Wind Energ. Sci., 8, 1711–1725, https://doi.org/10.5194/wes-8-1711-2023, https://doi.org/10.5194/wes-8-1711-2023, 2023
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The work presented here proposes interfacing experimental measurements performed in a wind tunnel with simulations conducted with the aeroelastic code FAST and applied to a floating wind turbine model under wave-induced motion. FAST simulations using experiments match well with those obtained using the inflow generation method provided by TurbSim. The highest surge motion frequencies show a significant decrease in the mean power produced by the turbine and a mitigation of the flow dynamics.
Christoffer Hallgren, Jeanie A. Aird, Stefan Ivanell, Heiner Körnich, Rebecca J. Barthelmie, Sara C. Pryor, and Erik Sahlée
Wind Energ. Sci., 8, 1651–1658, https://doi.org/10.5194/wes-8-1651-2023, https://doi.org/10.5194/wes-8-1651-2023, 2023
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Low-level jets (LLJs) are special types of non-ideal wind profiles affecting both wind energy production and loads on a wind turbine. However, among LLJ researchers, there is no consensus regarding which definition to use to identify these profiles. In this work, we compare two different ways of identifying the LLJ – the falloff definition and the shear definition – and argue why the shear definition is better suited to wind energy applications.
Serkan Kartal, Sukanta Basu, and Simon J. Watson
Wind Energ. Sci., 8, 1533–1551, https://doi.org/10.5194/wes-8-1533-2023, https://doi.org/10.5194/wes-8-1533-2023, 2023
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Peak wind gust is a crucial meteorological variable for wind farm planning and operations. Unfortunately, many wind farms do not have on-site measurements of it. In this paper, we propose a machine-learning approach (called INTRIGUE, decIsioN-TRee-based wInd GUst Estimation) that utilizes numerous inputs from a public-domain reanalysis dataset, generating long-term, site-specific peak wind gust series.
Nikolas Angelou, Jakob Mann, and Camille Dubreuil-Boisclair
Wind Energ. Sci., 8, 1511–1531, https://doi.org/10.5194/wes-8-1511-2023, https://doi.org/10.5194/wes-8-1511-2023, 2023
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This study presents the first experimental investigation using two nacelle-mounted wind lidars that reveal the upwind and downwind conditions relative to a full-scale floating wind turbine. We find that in the case of floating wind turbines with small pitch and roll oscillating motions (< 1°), the ambient turbulence is the main driving factor that determines the propagation of the wake characteristics.
Julian Quick, Pierre-Elouan Rethore, Mads Mølgaard Pedersen, Rafael Valotta Rodrigues, and Mikkel Friis-Møller
Wind Energ. Sci., 8, 1235–1250, https://doi.org/10.5194/wes-8-1235-2023, https://doi.org/10.5194/wes-8-1235-2023, 2023
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Wind turbine positions are often optimized to avoid wake losses. These losses depend on atmospheric conditions, such as the wind speed and direction. The typical optimization scheme involves discretizing the atmospheric inputs, then considering every possible set of these discretized inputs in every optimization iteration. This work presents stochastic gradient descent (SGD) as an alternative, which randomly samples the atmospheric conditions during every optimization iteration.
Sarah J. Ollier and Simon J. Watson
Wind Energ. Sci., 8, 1179–1200, https://doi.org/10.5194/wes-8-1179-2023, https://doi.org/10.5194/wes-8-1179-2023, 2023
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This modelling study shows that topographic trapped lee waves (TLWs) modify flow behaviour and power output in offshore wind farms. We demonstrate that TLWs can substantially alter the wind speeds at individual wind turbines and effect the power output of the turbine and whole wind farm. The impact on wind speeds and power is dependent on which part of the TLW wave cycle interacts with the wind turbines and wind farm. Positive and negative impacts of TLWs on power output are observed.
Khaled Yassin, Arne Helms, Daniela Moreno, Hassan Kassem, Leo Höning, and Laura J. Lukassen
Wind Energ. Sci., 8, 1133–1152, https://doi.org/10.5194/wes-8-1133-2023, https://doi.org/10.5194/wes-8-1133-2023, 2023
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The current turbulent wind field models stated in the IEC 61400-1 standard underestimate the probability of extreme changes in wind velocity. This underestimation can lead to the false calculation of extreme and fatigue loads on the turbine. In this work, we are trying to apply a random time-mapping technique to one of the standard turbulence models to adapt to such extreme changes. The turbulent fields generated are compared with a standard wind field to show the effects of this new mapping.
Mark Kelly and Maarten Paul van der Laan
Wind Energ. Sci., 8, 975–998, https://doi.org/10.5194/wes-8-975-2023, https://doi.org/10.5194/wes-8-975-2023, 2023
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The turning of the wind with height, which is known as veer, can affect wind turbine performance. Thus far meteorology has only given idealized descriptions of veer, which has not yet been related in a way readily usable for wind energy. Here we derive equations for veer in terms of meteorological quantities and provide practically usable forms in terms of measurable shear (change in wind speed with height). Flow simulations and measurements at turbine heights support these developments.
Moritz Gräfe, Vasilis Pettas, Julia Gottschall, and Po Wen Cheng
Wind Energ. Sci., 8, 925–946, https://doi.org/10.5194/wes-8-925-2023, https://doi.org/10.5194/wes-8-925-2023, 2023
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Inflow wind field measurements from nacelle-based lidar systems offer great potential for different applications including turbine control, load validation and power performance measurements. On floating wind turbines nacelle-based lidar measurements are affected by the dynamic behavior of the floating foundations. Therefore, the effects on lidar wind speed measurements induced by floater dynamics must be well understood. A new model for quantification of these effects is introduced in our work.
Robin Marcille, Maxime Thiébaut, Pierre Tandeo, and Jean-François Filipot
Wind Energ. Sci., 8, 771–786, https://doi.org/10.5194/wes-8-771-2023, https://doi.org/10.5194/wes-8-771-2023, 2023
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A novel data-driven method is proposed to design an optimal sensor network for the reconstruction of offshore wind resources. Based on unsupervised learning of numerical weather prediction wind data, it provides a simple yet efficient method for the siting of sensors, outperforming state-of-the-art methods for this application. It is applied in the main French offshore wind energy development areas to provide guidelines for the deployment of floating lidars for wind resource assessment.
Wei Fu, Alessandro Sebastiani, Alfredo Peña, and Jakob Mann
Wind Energ. Sci., 8, 677–690, https://doi.org/10.5194/wes-8-677-2023, https://doi.org/10.5194/wes-8-677-2023, 2023
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Nacelle lidars with different beam scanning locations and two types of systems are considered for inflow turbulence estimations using both numerical simulations and field measurements. The turbulence estimates from a sonic anemometer at the hub height of a Vestas V52 turbine are used as references. The turbulence parameters are retrieved using the radial variances and a least-squares procedure. The findings from numerical simulations have been verified by the analysis of the field measurements.
Daniel Hatfield, Charlotte Bay Hasager, and Ioanna Karagali
Wind Energ. Sci., 8, 621–637, https://doi.org/10.5194/wes-8-621-2023, https://doi.org/10.5194/wes-8-621-2023, 2023
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Wind observations at heights relevant to the operation of modern offshore wind farms, i.e. 100 m and more, are required to optimize their positioning and layout. Satellite wind retrievals provide observations of the wind field over large spatial areas and extensive time periods, yet their temporal resolution is limited and they are only representative at 10 m height. Machine-learning models are applied to lift these satellite winds to higher heights, directly relevant to wind energy purposes.
Anna von Brandis, Gabriele Centurelli, Jonas Schmidt, Lukas Vollmer, Bughsin' Djath, and Martin Dörenkämper
Wind Energ. Sci., 8, 589–606, https://doi.org/10.5194/wes-8-589-2023, https://doi.org/10.5194/wes-8-589-2023, 2023
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We propose that considering large-scale wind direction changes in the computation of wind farm cluster wakes is of high relevance. Consequently, we present a new solution for engineering modeling tools that accounts for the effect of such changes in the propagation of wakes. The new model is evaluated with satellite data in the German Bight area. It has the potential to reduce uncertainty in applications such as site assessment and short-term power forecasting.
Oliver Maas
Wind Energ. Sci., 8, 535–556, https://doi.org/10.5194/wes-8-535-2023, https://doi.org/10.5194/wes-8-535-2023, 2023
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The study compares small vs. large wind farms regarding the flow and power output with a turbulence-resolving simulation model. It shows that a large wind farm (90 km length) significantly affects the wind direction and that the wind speed is higher in the large wind farm wake. Both wind farms excite atmospheric gravity waves that also affect the power output of the wind farms.
Regis Thedin, Eliot Quon, Matthew Churchfield, and Paul Veers
Wind Energ. Sci., 8, 487–502, https://doi.org/10.5194/wes-8-487-2023, https://doi.org/10.5194/wes-8-487-2023, 2023
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We investigate coherence and correlation and highlight their importance for disciplines like wind energy structural dynamic analysis, in which blade loading and fatigue depend on turbulence structure. We compare coherence estimates to those computed using a model suggested by international standards. We show the differences and highlight additional information that can be gained using large-eddy simulation, further improving analytical coherence models used in synthetic turbulence generators.
Sheng-Lun Tai, Larry K. Berg, Raghavendra Krishnamurthy, Rob Newsom, and Anthony Kirincich
Wind Energ. Sci., 8, 433–448, https://doi.org/10.5194/wes-8-433-2023, https://doi.org/10.5194/wes-8-433-2023, 2023
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Turbulence intensity is critical for wind turbine design and operation as it affects wind power generation efficiency. Turbulence measurements in the marine environment are limited. We use a model to derive turbulence intensity and test how sea surface temperature data may impact the simulated turbulence intensity and atmospheric stability. The model slightly underestimates turbulence, and improved sea surface temperature data reduce the bias. Error with unrealistic mesoscale flow is identified.
Brandon Arthur Lobo, Özge Sinem Özçakmak, Helge Aagaard Madsen, Alois Peter Schaffarczyk, Michael Breuer, and Niels N. Sørensen
Wind Energ. Sci., 8, 303–326, https://doi.org/10.5194/wes-8-303-2023, https://doi.org/10.5194/wes-8-303-2023, 2023
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Results from the DAN-AERO and aerodynamic glove projects provide significant findings. The effects of inflow turbulence on transition and wind turbine blades are compared to computational fluid dynamic simulations. It is found that the transition scenario changes even over a single revolution. The importance of a suitable choice of amplification factor is evident from the simulations. An agreement between the power spectral density plots from the experiment and large-eddy simulations is seen.
Frédéric Blondel
Wind Energ. Sci., 8, 141–147, https://doi.org/10.5194/wes-8-141-2023, https://doi.org/10.5194/wes-8-141-2023, 2023
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Accurate wind farm flow predictions based on analytical wake models are crucial for wind farm design and layout optimization. Wake superposition methods play a key role and remain a substantial source of uncertainty. In the present work, a momentum-conserving superposition method is extended to the superposition of super-Gaussian-type velocity deficit models, allowing the full wake velocity deficit estimation and design of closely packed wind farms.
Abdul Haseeb Syed, Jakob Mann, Andreas Platis, and Jens Bange
Wind Energ. Sci., 8, 125–139, https://doi.org/10.5194/wes-8-125-2023, https://doi.org/10.5194/wes-8-125-2023, 2023
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Wind turbines extract energy from the incoming wind flow, which needs to be recovered. In very large offshore wind farms, the energy is recovered mostly from above the wind farm in a process called entrainment. In this study, we analyzed the effect of atmospheric stability on the entrainment process in large offshore wind farms using measurements recorded by a research aircraft. This is the first time that in situ measurements are used to study the energy recovery process above wind farms.
Kartik Venkatraman, Trond-Ola Hågbo, Sophia Buckingham, and Knut Erik Teigen Giljarhus
Wind Energ. Sci., 8, 85–108, https://doi.org/10.5194/wes-8-85-2023, https://doi.org/10.5194/wes-8-85-2023, 2023
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This paper is focused on the impact of modeling different effects, such as forest canopy and Coriolis forces, on the wind resource over a complex terrain site located near Perdigão, Portugal. A numerical model is set up and results are compared with field measurements. The results show that including a forest canopy improves the predictions close to the ground at some locations on the site, while the model with inflow from a precursor performed better at other locations.
Ishaan Sood, Elliot Simon, Athanasios Vitsas, Bart Blockmans, Gunner C. Larsen, and Johan Meyers
Wind Energ. Sci., 7, 2469–2489, https://doi.org/10.5194/wes-7-2469-2022, https://doi.org/10.5194/wes-7-2469-2022, 2022
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In this work, we conduct a validation study to compare a numerical solver against measurements obtained from the offshore Lillgrund wind farm. By reusing a previously developed inflow turbulent dataset, the atmospheric conditions at the wind farm were recreated, and the general performance trends of the turbines were captured well. The work increases the reliability of numerical wind farm solvers while highlighting the challenges of accurately representing large wind farms using such solvers.
Xiaoli Guo Larsén and Søren Ott
Wind Energ. Sci., 7, 2457–2468, https://doi.org/10.5194/wes-7-2457-2022, https://doi.org/10.5194/wes-7-2457-2022, 2022
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A method is developed for calculating the extreme wind in tropical-cyclone-affected water areas. The method is based on the spectral correction method that fills in the missing wind variability to the modeled time series, guided by best track data. The paper provides a detailed recipe for applying the method and the 50-year winds of equivalent 10 min temporal resolution from 10 to 150 m in several tropical-cyclone-affected regions.
Yulong Ma, Cristina L. Archer, and Ahmadreza Vasel-Be-Hagh
Wind Energ. Sci., 7, 2407–2431, https://doi.org/10.5194/wes-7-2407-2022, https://doi.org/10.5194/wes-7-2407-2022, 2022
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Wind turbine wakes are important because they reduce the power production of wind farms and may cause unintended impacts on the weather around wind farms. Weather prediction models, like WRF and MPAS, are often used to predict both power and impacts of wind farms, but they lack an accurate treatment of wind farm wakes. We developed the Jensen wind farm parameterization, based on the existing Jensen model of an idealized wake. The Jensen parameterization is accurate and computationally efficient.
Andrea N. Hahmann, Oscar García-Santiago, and Alfredo Peña
Wind Energ. Sci., 7, 2373–2391, https://doi.org/10.5194/wes-7-2373-2022, https://doi.org/10.5194/wes-7-2373-2022, 2022
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We explore the changes in wind energy resources in northern Europe using output from simulations from the Climate Model Intercomparison Project (CMIP6) under the high-emission scenario. Our results show that climate change does not particularly alter annual energy production in the North Sea but could affect the seasonal distribution of these resources, significantly reducing energy production during the summer from 2031 to 2050.
Turið Poulsen, Bárður A. Niclasen, Gregor Giebel, and Hans Georg Beyer
Wind Energ. Sci., 7, 2335–2350, https://doi.org/10.5194/wes-7-2335-2022, https://doi.org/10.5194/wes-7-2335-2022, 2022
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Wind power is cheap and environmentally friendly, but it has a disadvantage: it is a variable power source. Because wind is not blowing everywhere simultaneously, optimal placement of wind farms can reduce the fluctuations.
This is explored for a small isolated area. Combining wind farms reduces wind power fluctuations for timescales up to 1–2 d. By optimally placing four wind farms, the hourly fluctuations are reduced by 15 %. These wind farms are located distant from each other.
Graziela Luzia, Andrea N. Hahmann, and Matti Juhani Koivisto
Wind Energ. Sci., 7, 2255–2270, https://doi.org/10.5194/wes-7-2255-2022, https://doi.org/10.5194/wes-7-2255-2022, 2022
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This paper presents a comprehensive validation of time series produced by a mesoscale numerical weather model, a global reanalysis, and a wind atlas against observations by using a set of metrics that we present as requirements for wind energy integration studies. We perform a sensitivity analysis on the numerical weather model in multiple configurations, such as related to model grid spacing and nesting arrangements, to define the model setup that outperforms in various time series aspects.
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Short summary
Knowing the wind speed across the rotor of a wind turbine is key in making good predictions of the power production. However, models struggle to capture both the speed and the shape of the wind profile. Using machine learning methods based on the model data, we show that the predictions can be improved drastically. The work focuses on three coastal sites, spread over the Northern Hemisphere (the Baltic Sea, the North Sea, and the US Atlantic coast) with similar results for all sites.
Knowing the wind speed across the rotor of a wind turbine is key in making good predictions of...
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