Strength and Challenges of global model MPAS with regional mesh refinement for mid-latitude storm forecasting: a case study
Wind Energy Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Xiaoli Guo Larsén
Wind Energy Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Neil Davis
Wind Energy Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
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Wind Energ. Sci., 8, 819–848, https://doi.org/10.5194/wes-8-819-2023, https://doi.org/10.5194/wes-8-819-2023, 2023
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Offshore wind farms are more commonly installed in wind farm clusters, where wind farm interaction can lead to energy losses. In this work, an efficient numerical method is presented that can be used to estimate these energy losses. The novel method is verified with higher-fidelity numerical models and validated with measurements of an existing wind farm cluster.
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We study how climate change will impact extreme winds and choice of turbine class. We use data from 18 CMIP6 members from a historic and a future period to access the change in the extreme winds. The analysis shows an overall increase in the extreme winds in the North Sea and the southern Baltic Sea, but a decrease over the Scandinavian Peninsula and most of the Baltic Sea. The analysis is inconclusive to whether higher or lower classes of turbines will be installed in the future.
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Tropical cyclone winds are challenging for wind turbines. We analyze a tropical cyclone before landfall in a mesoscale model. The simulated wind speeds and storm structure are sensitive to the boundary parametrization. However, independent of the boundary layer parametrization, the median change in wind speed and wind direction with height is small relative to wind turbine design standards. Strong spatial organization of wind shear and veer along the rainbands may increase wind turbine loads.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Maarten Paul van der Laan, Oscar García-Santiago, Mark Kelly, Alexander Meyer Forsting, Camille Dubreuil-Boisclair, Knut Sponheim Seim, Marc Imberger, Alfredo Peña, Niels Nørmark Sørensen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 8, 819–848, https://doi.org/10.5194/wes-8-819-2023, https://doi.org/10.5194/wes-8-819-2023, 2023
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Offshore wind farms are more commonly installed in wind farm clusters, where wind farm interaction can lead to energy losses. In this work, an efficient numerical method is presented that can be used to estimate these energy losses. The novel method is verified with higher-fidelity numerical models and validated with measurements of an existing wind farm cluster.
Xiaoli Guo Larsén, Marc Imberger, Ásta Hannesdóttir, and Andrea N. Hahmann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2022-102, https://doi.org/10.5194/wes-2022-102, 2023
Revised manuscript not accepted
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We study how climate change will impact extreme winds and choice of turbine class. We use data from 18 CMIP6 members from a historic and a future period to access the change in the extreme winds. The analysis shows an overall increase in the extreme winds in the North Sea and the southern Baltic Sea, but a decrease over the Scandinavian Peninsula and most of the Baltic Sea. The analysis is inconclusive to whether higher or lower classes of turbines will be installed in the future.
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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.
Jana Fischereit, Kurt Schaldemose Hansen, Xiaoli Guo Larsén, Maarten Paul van der Laan, Pierre-Elouan Réthoré, and Juan Pablo Murcia Leon
Wind Energ. Sci., 7, 1069–1091, https://doi.org/10.5194/wes-7-1069-2022, https://doi.org/10.5194/wes-7-1069-2022, 2022
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Wind turbines extract kinetic energy from the flow to create electricity. This induces a wake of reduced wind speed downstream of a turbine and consequently downstream of a wind farm. Different types of numerical models have been developed to calculate this effect. In this study, we compared models of different complexity, together with measurements over two wind farms. We found that higher-fidelity models perform better and the considered rapid models cannot fully capture the wake effect.
Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, https://doi.org/10.5194/esd-13-251-2022, 2022
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A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
Marcus Reckermann, Anders Omstedt, Tarmo Soomere, Juris Aigars, Naveed Akhtar, Magdalena Bełdowska, Jacek Bełdowski, Tom Cronin, Michał Czub, Margit Eero, Kari Petri Hyytiäinen, Jukka-Pekka Jalkanen, Anders Kiessling, Erik Kjellström, Karol Kuliński, Xiaoli Guo Larsén, Michelle McCrackin, H. E. Markus Meier, Sonja Oberbeckmann, Kevin Parnell, Cristian Pons-Seres de Brauwer, Anneli Poska, Jarkko Saarinen, Beata Szymczycha, Emma Undeman, Anders Wörman, and Eduardo Zorita
Earth Syst. Dynam., 13, 1–80, https://doi.org/10.5194/esd-13-1-2022, https://doi.org/10.5194/esd-13-1-2022, 2022
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As part of the Baltic Earth Assessment Reports (BEAR), we present an inventory and discussion of different human-induced factors and processes affecting the environment of the Baltic Sea region and their interrelations. Some are naturally occurring and modified by human activities, others are completely human-induced, and they are all interrelated to different degrees. The findings from this study can largely be transferred to other comparable marginal and coastal seas in the world.
Xiaoli G. Larsén and Jana Fischereit
Geosci. Model Dev., 14, 3141–3158, https://doi.org/10.5194/gmd-14-3141-2021, https://doi.org/10.5194/gmd-14-3141-2021, 2021
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For the first time, turbulent kinetic energy (TKE) calculated from the explicit wake parameterization (EWP) in WRF is examined using high-frequency measurements over a wind farm and compared with that calculated using the Fitch et al. (2012) scheme. We examined the effect of farm-induced TKE advection in connection with the Fitch scheme. Through a case study with a low-level jet (LLJ), we analyzed the key features of LLJs and raised the issue of interaction between wind farms and LLJs.
Andrea N. Hahmann, Tija Sīle, Björn Witha, Neil N. Davis, Martin Dörenkämper, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Bjarke T. Olsen, and Stefan Söderberg
Geosci. Model Dev., 13, 5053–5078, https://doi.org/10.5194/gmd-13-5053-2020, https://doi.org/10.5194/gmd-13-5053-2020, 2020
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Wind energy resource assessment routinely uses numerical weather prediction model output. We describe the evaluation procedures used for picking the suitable blend of model setup and parameterizations for simulating European wind climatology with the WRF model. We assess the simulated winds against tall mast measurements using a suite of metrics, including the Earth Mover's Distance, which diagnoses the performance of each ensemble member using the full wind speed and direction distribution.
Martin Dörenkämper, Bjarke T. Olsen, Björn Witha, Andrea N. Hahmann, Neil N. Davis, Jordi Barcons, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Mariano Sastre-Marugán, Tija Sīle, Wilke Trei, Mark Žagar, Jake Badger, Julia Gottschall, Javier Sanz Rodrigo, and Jakob Mann
Geosci. Model Dev., 13, 5079–5102, https://doi.org/10.5194/gmd-13-5079-2020, https://doi.org/10.5194/gmd-13-5079-2020, 2020
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This is the second of two papers that document the creation of the New European Wind Atlas (NEWA). The paper includes a detailed description of the technical and practical aspects that went into running the mesoscale simulations and the microscale downscaling for generating the climatology. A comprehensive evaluation of each component of the NEWA model chain is presented using observations from a large set of tall masts located all over Europe.
Jianting Du, Rodolfo Bolaños, Xiaoli Guo Larsén, and Mark Kelly
Ocean Sci., 15, 361–377, https://doi.org/10.5194/os-15-361-2019, https://doi.org/10.5194/os-15-361-2019, 2019
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Ocean surface waves generated by wind and dissipated by white capping are two important physics processes for numerical wave simulations. In this study, a new pair of wind–wave generation and dissipation source functions is implemented in the wave model SWAN, and it shows better performance in real wave simulations during two North Sea storms. The new source functions can be further used in other wave models for both academic and engineering purposes.
Rogier Floors, Peter Enevoldsen, Neil Davis, Johan Arnqvist, and Ebba Dellwik
Wind Energ. Sci., 3, 353–370, https://doi.org/10.5194/wes-3-353-2018, https://doi.org/10.5194/wes-3-353-2018, 2018
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Applying erroneous boundary conditions (surface roughness) for wind flow modelling can have a large impact on the estimated performance of wind turbines, particularly in forested areas. Traditionally the estimation of the surface roughness is based on a subjective process that requires assigning a value to each land use class in the vicinity of the wind farm. Here we propose a new method which converts lidar scans from a plane into maps that can be used for wind flow modelling.
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Short summary
Events like mid-latitude storms with their high winds have an impact on wind energy production and forecasting of such events is crucial. This study investigates the capabilities of a global weather prediction model MPAS and looks at how key parameters like storm intensity, arrival time and duration are represented compared to measurements and traditional methods. It is found that storm intensity is represented well while model drifts negatively influence estimation of arrival time and duration.
Events like mid-latitude storms with their high winds have an impact on wind energy production...