Articles | Volume 13, issue 1
https://doi.org/10.5194/gmd-13-249-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-249-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
29 Jan 2020
Model evaluation paper |
| 29 Jan 2020
| 29 Jan 2020
Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)
Simon K. Siedersleben
CORRESPONDING AUTHOR
Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Partenkirchen, Germany
Andreas Platis
Environmental Physics, ZAG, University of Tübingen, Tübingen, Germany
Julie K. Lundquist
University of Colorado, Department of Atmospheric and Oceanic Sciences, Boulder, CO, USA
National Renewable Energy Laboratory, Golden, CO, USA
Bughsin Djath
Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Geesthacht, Germany
Astrid Lampert
Institute of Flight Guidance, Technische Universität Braunschweig, Braunschweig, Germany
Konrad Bärfuss
Institute of Flight Guidance, Technische Universität Braunschweig, Braunschweig, Germany
Beatriz Cañadillas
UL-DEWI Gmbh, Oldenburg, Germany
Johannes Schulz-Stellenfleth
Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Geesthacht, Germany
Jens Bange
Environmental Physics, ZAG, University of Tübingen, Tübingen, Germany
Tom Neumann
UL-DEWI Gmbh, Oldenburg, Germany
Stefan Emeis
Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Partenkirchen, Germany
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Rachel Robey and Julie K. Lundquist
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Beatriz Cañadillas, Maximilian Beckenbauer, Juan J. Trujillo, Martin Dörenkämper, Richard Foreman, Thomas Neumann, and Astrid Lampert
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Matteo Bramati, Martin Schön, Daniel Schulz, Vasileios Savvakis, Jens Bange, and Andreas Platis
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Revised manuscript not accepted
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Vincent Pronk, Nicola Bodini, Mike Optis, Julie K. Lundquist, Patrick Moriarty, Caroline Draxl, Avi Purkayastha, and Ethan Young
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Tobias Klaas-Witt and Stefan Emeis
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Adam S. Wise, James M. T. Neher, Robert S. Arthur, Jeffrey D. Mirocha, Julie K. Lundquist, and Fotini K. Chow
Wind Energ. Sci., 7, 367–386, https://doi.org/10.5194/wes-7-367-2022, https://doi.org/10.5194/wes-7-367-2022, 2022
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Hannah Livingston, Nicola Bodini, and Julie K. Lundquist
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-68, https://doi.org/10.5194/wes-2021-68, 2021
Preprint withdrawn
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Miguel Sanchez Gomez, Julie K. Lundquist, Petra M. Klein, and Tyler M. Bell
Earth Syst. Sci. Data, 13, 3539–3549, https://doi.org/10.5194/essd-13-3539-2021, https://doi.org/10.5194/essd-13-3539-2021, 2021
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In July 2018, the International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) hosted a flight week to demonstrate unmanned aircraft systems' capabilities in sampling the atmospheric boundary layer. Three Doppler lidars were deployed during this week-long experiment. We use data from these lidars to estimate turbulence dissipation rate. We observe large temporal variability and significant differences in dissipation for lidars with different sampling techniques.
Miguel Sanchez Gomez, Julie K. Lundquist, Jeffrey D. Mirocha, Robert S. Arthur, and Domingo Muñoz-Esparza
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-57, https://doi.org/10.5194/wes-2021-57, 2021
Revised manuscript not accepted
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Alex Rybchuk, Mike Optis, Julie K. Lundquist, Michael Rossol, and Walt Musial
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-50, https://doi.org/10.5194/gmd-2021-50, 2021
Preprint withdrawn
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We characterize the wind resource off the coast of California by conducting simulations with the Weather Research and Forecasting (WRF) model between 2000 and 2019. We compare newly simulated winds to those from the WIND Toolkit. The newly simulated winds are substantially stronger, particularly in the late summer. We also conduct a refined analysis at three areas that are being considered for commercial development, finding that stronger winds translates to substantially more power here.
Tyler M. Bell, Petra M. Klein, Julie K. Lundquist, and Sean Waugh
Earth Syst. Sci. Data, 13, 1041–1051, https://doi.org/10.5194/essd-13-1041-2021, https://doi.org/10.5194/essd-13-1041-2021, 2021
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In July 2018, numerous weather sensing remotely piloted aircraft systems (RPASs) were flown in a flight week called Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). As part of LAPSE-RATE, ground-based remote and in situ systems were also deployed to supplement and enhance observations from the RPASs. These instruments include multiple Doppler lidars, thermodynamic profilers, and radiosondes. This paper describes data from these systems.
Moritz Mauz, Bram van Kesteren, Andreas Platis, Stefan Emeis, and Jens Bange
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-21, https://doi.org/10.5194/wes-2021-21, 2021
Preprint withdrawn
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The study aims for a computationally inexpensive model describing the wind deficit behind a wind energy converter analytically using some assumptions and basic governing equations of the atmosphere. Thus, the influence of different atmospheric conditions onto the wake development can be studied in the future which is important e.g. in wind park planning. The model is compared to conventional empirical wake models and in-situ UAS measurements captured along the wake at hub height.
Bart M. Doekemeijer, Stefan Kern, Sivateja Maturu, Stoyan Kanev, Bastian Salbert, Johannes Schreiber, Filippo Campagnolo, Carlo L. Bottasso, Simone Schuler, Friedrich Wilts, Thomas Neumann, Giancarlo Potenza, Fabio Calabretta, Federico Fioretti, and Jan-Willem van Wingerden
Wind Energ. Sci., 6, 159–176, https://doi.org/10.5194/wes-6-159-2021, https://doi.org/10.5194/wes-6-159-2021, 2021
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This article presents the results of a field experiment investigating wake steering on an onshore wind farm. The measurements show that wake steering leads to increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions. The results suggest that further research is necessary before wake steering will consistently lead to energy gains in wind farms.
Caroline Draxl, Rochelle P. Worsnop, Geng Xia, Yelena Pichugina, Duli Chand, Julie K. Lundquist, Justin Sharp, Garrett Wedam, James M. Wilczak, and Larry K. Berg
Wind Energ. Sci., 6, 45–60, https://doi.org/10.5194/wes-6-45-2021, https://doi.org/10.5194/wes-6-45-2021, 2021
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Mountain waves can create oscillations in low-level wind speeds and subsequently in the power output of wind plants. We document such oscillations by analyzing sodar and lidar observations, nacelle wind speeds, power observations, and Weather Research and Forecasting model simulations. This research describes how mountain waves form in the Columbia River basin and affect wind energy production and their impact on operational forecasting, wind plant layout, and integration of power into the grid.
Jessica M. Tomaszewski and Julie K. Lundquist
Wind Energ. Sci., 6, 1–13, https://doi.org/10.5194/wes-6-1-2021, https://doi.org/10.5194/wes-6-1-2021, 2021
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We use a mesoscale numerical weather prediction model to conduct a case study of a thunderstorm outflow passing over and interacting with a wind farm. These simulations and observations from a nearby radar and surface station confirm that interactions with the wind farm cause the outflow to reduce its speed by over 20 km h−1, with brief but significant impacts on the local meteorology, including temperature, moisture, and winds. Precipitation accumulation across the region was unaffected.
Gijs de Boer, Adam Houston, Jamey Jacob, Phillip B. Chilson, Suzanne W. Smith, Brian Argrow, Dale Lawrence, Jack Elston, David Brus, Osku Kemppinen, Petra Klein, Julie K. Lundquist, Sean Waugh, Sean C. C. Bailey, Amy Frazier, Michael P. Sama, Christopher Crick, David Schmale III, James Pinto, Elizabeth A. Pillar-Little, Victoria Natalie, and Anders Jensen
Earth Syst. Sci. Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020, https://doi.org/10.5194/essd-12-3357-2020, 2020
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Wind turbines rotate clockwise. The rotational direction of the rotor interacts with the nighttime veering wind, resulting in a rotational-direction impact on the wake. In the case of counterclockwise-rotating blades the streamwise velocity in the wake is larger in the Northern Hemisphere whereas it is smaller in the Southern Hemisphere.
Antonia Englberger, Andreas Dörnbrack, and Julie K. Lundquist
Wind Energ. Sci., 5, 1359–1374, https://doi.org/10.5194/wes-5-1359-2020, https://doi.org/10.5194/wes-5-1359-2020, 2020
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At night, the wind direction often changes with height, and this veer affects structures near the surface like wind turbines. Wind turbines usually rotate clockwise, but this rotational direction interacts with veer to impact the flow field behind a wind turbine. If another turbine is located downwind, the direction of the upwind turbine's rotation will affect the downwind turbine.
Nicola Bodini, Julie K. Lundquist, and Mike Optis
Geosci. Model Dev., 13, 4271–4285, https://doi.org/10.5194/gmd-13-4271-2020, https://doi.org/10.5194/gmd-13-4271-2020, 2020
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While turbulence dissipation rate (ε) is an essential parameter for the prediction of wind speed, its current representation in weather prediction models is inaccurate, especially in complex terrain. In this study, we leverage the potential of machine-learning techniques to provide a more accurate representation of turbulence dissipation rate. Our results show a 30 % reduction in the average error compared to the current model representation of ε and a total elimination of its average bias.
Patrick Murphy, Julie K. Lundquist, and Paul Fleming
Wind Energ. Sci., 5, 1169–1190, https://doi.org/10.5194/wes-5-1169-2020, https://doi.org/10.5194/wes-5-1169-2020, 2020
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We present and evaluate an improved method for predicting wind turbine power production based on measurements of the wind speed and direction profile across the rotor disk for a wind turbine in complex terrain. By comparing predictions to actual power production from a utility-scale wind turbine, we show this method is more accurate than methods based on hub-height wind speed or surface-based atmospheric characterization.
Paul Fleming, Jennifer King, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, David Jager, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 5, 945–958, https://doi.org/10.5194/wes-5-945-2020, https://doi.org/10.5194/wes-5-945-2020, 2020
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This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in a companion paper (https://wes.copernicus.org/articles/4/273/2019/). The authors implemented wake steering on two turbine pairs and compared results with the latest FLORIS model of wake steering, showing good agreement in overall energy increase.
Tuukka Petäjä, Ella-Maria Duplissy, Ksenia Tabakova, Julia Schmale, Barbara Altstädter, Gerard Ancellet, Mikhail Arshinov, Yurii Balin, Urs Baltensperger, Jens Bange, Alison Beamish, Boris Belan, Antoine Berchet, Rossana Bossi, Warren R. L. Cairns, Ralf Ebinghaus, Imad El Haddad, Beatriz Ferreira-Araujo, Anna Franck, Lin Huang, Antti Hyvärinen, Angelika Humbert, Athina-Cerise Kalogridis, Pavel Konstantinov, Astrid Lampert, Matthew MacLeod, Olivier Magand, Alexander Mahura, Louis Marelle, Vladimir Masloboev, Dmitri Moisseev, Vaios Moschos, Niklas Neckel, Tatsuo Onishi, Stefan Osterwalder, Aino Ovaska, Pauli Paasonen, Mikhail Panchenko, Fidel Pankratov, Jakob B. Pernov, Andreas Platis, Olga Popovicheva, Jean-Christophe Raut, Aurélie Riandet, Torsten Sachs, Rosamaria Salvatori, Roberto Salzano, Ludwig Schröder, Martin Schön, Vladimir Shevchenko, Henrik Skov, Jeroen E. Sonke, Andrea Spolaor, Vasileios K. Stathopoulos, Mikko Strahlendorff, Jennie L. Thomas, Vito Vitale, Sterios Vratolis, Carlo Barbante, Sabine Chabrillat, Aurélien Dommergue, Konstantinos Eleftheriadis, Jyri Heilimo, Kathy S. Law, Andreas Massling, Steffen M. Noe, Jean-Daniel Paris, André S. H. Prévôt, Ilona Riipinen, Birgit Wehner, Zhiyong Xie, and Hanna K. Lappalainen
Atmos. Chem. Phys., 20, 8551–8592, https://doi.org/10.5194/acp-20-8551-2020, https://doi.org/10.5194/acp-20-8551-2020, 2020
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The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. Here we summarize initial results from our integrative project exploring the Arctic environment and pollution to deliver data products, metrics, and indicators for stakeholders.
Barbara Altstädter, Konrad Deetz, Bernhard Vogel, Karmen Babić, Cheikh Dione, Federica Pacifico, Corinne Jambert, Friederike Ebus, Konrad Bärfuss, Falk Pätzold, Astrid Lampert, Bianca Adler, Norbert Kalthoff, and Fabienne Lohou
Atmos. Chem. Phys., 20, 7911–7928, https://doi.org/10.5194/acp-20-7911-2020, https://doi.org/10.5194/acp-20-7911-2020, 2020
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We present the high vertical variability of the black carbon (BC) mass concentration measured with the unmanned aerial system ALADINA during the field experiment of DACCIWA. The COSMO-ART model output was applied for the campaign period and is compared with the observational BC data during a case study on 14–15 July 2016. Enhanced BC concentrations were related to transport processes to the measurement site by maritime inflow and not to local emissions as initially expected.
Moritz Mauz, Bram van Kesteren, Andreas Platis, Stefan Emeis, and Jens Bange
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-92, https://doi.org/10.5194/wes-2020-92, 2020
Revised manuscript not accepted
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The submitted manuscript suggests an analytical model/approach to connect the near-wake wind deficit with the mid an far-wake deficit. The atmospheric turbulence is considered as the main driver for the wind deficit decay rate in this approach. The analytical solution is backed by a numerical solution of the momentum conservation equation derived from Navier-Stokes equations. In-situ wake UAS measurements are the basis and motivation for the model approach shown in the manuscript.
Jessica M. Tomaszewski and Julie K. Lundquist
Geosci. Model Dev., 13, 2645–2662, https://doi.org/10.5194/gmd-13-2645-2020, https://doi.org/10.5194/gmd-13-2645-2020, 2020
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Wind farms can briefly impact the nearby environment by reducing wind speeds and mixing warmer air down to the surface. The wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF) model is a tool that numerically simulates wind farms and these meteorological impacts. We highlight the importance of choice in model settings and find that sufficiently fine vertical and horizontal grids with turbine turbulence are needed to accurately simulate wind farm meteorological impacts.
Michel Tchilibou, Lionel Gourdeau, Florent Lyard, Rosemary Morrow, Ariane Koch Larrouy, Damien Allain, and Bughsin Djath
Ocean Sci., 16, 615–635, https://doi.org/10.5194/os-16-615-2020, https://doi.org/10.5194/os-16-615-2020, 2020
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This paper focuses on internal tides in the marginal Solomon Sea where LLWBCs transit. The objective is to characterize such internal tides and to give some insights into their impacts on water mass transformation in this area of interest for the global circulation. Results are discussed for two contrasted ENSO conditions with different mesoscale activity and stratification. Such study is motivated by the next altimetric SWOT mission that will be able to observe such phenomena.
Astrid Lampert, Konrad Bärfuss, Andreas Platis, Simon Siedersleben, Bughsin Djath, Beatriz Cañadillas, Robert Hunger, Rudolf Hankers, Mark Bitter, Thomas Feuerle, Helmut Schulz, Thomas Rausch, Maik Angermann, Alexander Schwithal, Jens Bange, Johannes Schulz-Stellenfleth, Thomas Neumann, and Stefan Emeis
Earth Syst. Sci. Data, 12, 935–946, https://doi.org/10.5194/essd-12-935-2020, https://doi.org/10.5194/essd-12-935-2020, 2020
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With the research aircraft Do-128 of TU Braunschweig, meteorological measurements were performed in the wakes of offshore wind parks during the project WIPAFF. During stable atmospheric conditions, the areas of reduced wind speed and enhanced turbulence behind wind parks had an extension larger than 45 km downwind. The data set consisting of 41 measurement flights is presented. Parameters include wind vector, temperature, humidity and significant wave height.
Astrid Lampert, Falk Pätzold, Magnus O. Asmussen, Lennart Lobitz, Thomas Krüger, Thomas Rausch, Torsten Sachs, Christian Wille, Denis Sotomayor Zakharov, Dominik Gaus, Stephan Bansmer, and Ellen Damm
Atmos. Meas. Tech., 13, 1937–1952, https://doi.org/10.5194/amt-13-1937-2020, https://doi.org/10.5194/amt-13-1937-2020, 2020
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Methane has high climate warming potential. Sources of methane can be distinguished by the isotopic composition. To investigate the origin of methane, an airborne sampling system has been developed that can take air samples worldwide and at various altitudes. The article shows the performance of the overall system, from taking samples to laboratory analyses. As known methane source, a rewetted peatland site, was studied, and the vertical distribution of the isotopic composition is investigated.
Philipp Gasch, Andreas Wieser, Julie K. Lundquist, and Norbert Kalthoff
Atmos. Meas. Tech., 13, 1609–1631, https://doi.org/10.5194/amt-13-1609-2020, https://doi.org/10.5194/amt-13-1609-2020, 2020
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We present an airborne Doppler lidar simulator (ADLS) based on high-resolution atmospheric wind fields (LES). The ADLS is used to evaluate the retrieval accuracy of airborne wind profiling under turbulent, inhomogeneous wind field conditions inside the boundary layer. With the ADLS, the error due to the violation of the wind field homogeneity assumption used for retrieval can be revealed. For the conditions considered, flow inhomogeneities exert a dominant influence on wind profiling error.
Miguel Sanchez Gomez and Julie K. Lundquist
Wind Energ. Sci., 5, 125–139, https://doi.org/10.5194/wes-5-125-2020, https://doi.org/10.5194/wes-5-125-2020, 2020
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Wind turbine performance depends on various atmospheric conditions. We quantified the effect of the change in wind direction and speed with height (direction and speed wind shear) on turbine power at a wind farm in Iowa. Turbine performance was affected during large direction shear and small speed shear conditions and favored for the opposite scenarios. These effects make direction shear significant when analyzing the influence of different atmospheric variables on turbine operation.
Norman Wildmann, Nicola Bodini, Julie K. Lundquist, Ludovic Bariteau, and Johannes Wagner
Atmos. Meas. Tech., 12, 6401–6423, https://doi.org/10.5194/amt-12-6401-2019, https://doi.org/10.5194/amt-12-6401-2019, 2019
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Turbulence is the variation of wind velocity on short timescales. In this study we introduce a new method to measure turbulence in a two-dimensionial plane with lidar instruments. The method allows for the detection and quantification of subareas of distinct turbulence conditions in the observed plane. We compare the results to point and profile measurements with more established instruments. It is shown that turbulence below low-level jets and in wind turbine wakes can be investigated this way.
Laura Bianco, Irina V. Djalalova, James M. Wilczak, Joseph B. Olson, Jaymes S. Kenyon, Aditya Choukulkar, Larry K. Berg, Harindra J. S. Fernando, Eric P. Grimit, Raghavendra Krishnamurthy, Julie K. Lundquist, Paytsar Muradyan, Mikhail Pekour, Yelena Pichugina, Mark T. Stoelinga, and David D. Turner
Geosci. Model Dev., 12, 4803–4821, https://doi.org/10.5194/gmd-12-4803-2019, https://doi.org/10.5194/gmd-12-4803-2019, 2019
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During the second Wind Forecast Improvement Project, improvements to the parameterizations were applied to the High Resolution Rapid Refresh model and its nested version. The impacts of the new parameterizations on the forecast of 80 m wind speeds and power are assessed, using sodars and profiling lidars observations for comparison. Improvements are evaluated as a function of the model’s initialization time, forecast horizon, time of the day, season, site elevation, and meteorological phenomena.
Daniel Leukauf, Asmae El-Bahlouli, Kjell zum Berge, Martin Schön, Hermann Knaus, and Jens Bange
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-68, https://doi.org/10.5194/wes-2019-68, 2019
Revised manuscript not accepted
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Hilltops are in principle favorable locations for wind turbines due to the increased mean wind speed that can be found over hills. However, the more complex terrain leads to more complex flow conditions and increased turbulence. Numerical simulations are required to understand the flow conditions at sites in hilly terrain. A numerical simulation of the passage of a cold front over the site shows that increased drag caused by the nearby forests must be included in the model.
Moritz Mauz, Alexander Rautenberg, Andreas Platis, Marion Cormier, and Jens Bange
Wind Energ. Sci., 4, 451–463, https://doi.org/10.5194/wes-4-451-2019, https://doi.org/10.5194/wes-4-451-2019, 2019
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UAS systems provide in situ measurements of turbulence and wind conditions. In the presented paper, the tip vortex generated by wind energy converters (WECs) is measured by a fixed-wing UAS and compared to an analytical model as well as a literature value. The results show good agreement. The presented method is a basis for future measurement campaigns to compare UAS measurements with numerical simulations of WEC wakes.
Paul Fleming, Jennifer King, Katherine Dykes, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, Hector Lopez, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 4, 273–285, https://doi.org/10.5194/wes-4-273-2019, https://doi.org/10.5194/wes-4-273-2019, 2019
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Wake steering is a form of wind farm control in which turbines use yaw offsets to affect wakes in order to yield an increase in total energy production. In this first phase of a study of wake steering at a commercial wind farm, two turbines implement a schedule of offsets. For two closely spaced turbines, an approximate 14 % increase in energy was measured on the downstream turbine over a 10° sector, with a 4 % increase in energy production of the combined turbine pair.
Nicola Bodini, Julie K. Lundquist, Raghavendra Krishnamurthy, Mikhail Pekour, Larry K. Berg, and Aditya Choukulkar
Atmos. Chem. Phys., 19, 4367–4382, https://doi.org/10.5194/acp-19-4367-2019, https://doi.org/10.5194/acp-19-4367-2019, 2019
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To improve the parameterization of the turbulence dissipation rate (ε) in numerical weather prediction models, we have assessed its temporal and spatial variability at various scales in the Columbia River Gorge during the WFIP2 field experiment. The turbulence dissipation rate shows large spatial variability, even at the microscale, with larger values in sites located downwind of complex orographic structures or in wind farm wakes. Distinct diurnal and seasonal cycles in ε have also been found.
Johannes Schulz-Stellenfleth and Joanna Staneva
Ocean Sci., 15, 249–268, https://doi.org/10.5194/os-15-249-2019, https://doi.org/10.5194/os-15-249-2019, 2019
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Errors of observations and numerical model data are analysed with a focus on heterogeneous coastal areas. An extension of the triple collocation method is proposed, which takes into account gradients in the collocation of datasets separated by distances which may not be acceptable for a nearest-neigbour approximation, but still be feasible for linear or higher order interpolations. The technique is applied to wave height data from in situ stations, models, and the Sentinel-3A altimeter.
Claudio Crazzolara, Martin Ebner, Andreas Platis, Tatiana Miranda, Jens Bange, and Annett Junginger
Atmos. Meas. Tech., 12, 1581–1598, https://doi.org/10.5194/amt-12-1581-2019, https://doi.org/10.5194/amt-12-1581-2019, 2019
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A newly developed in situ measurement method provides new insights into the propagation behaviour of aerosol particles such as pollen grains and spores, possibly improving the pollen prognosis for allergy sufferers and providing new discoveries in the propagation behaviour of fine dust particles of different origins. This publication describes the development of the remote-controlled multicopter-based system as well as initial tests and validations to overcome various technical challenges.
Robert Menke, Nikola Vasiljević, Jakob Mann, and Julie K. Lundquist
Atmos. Chem. Phys., 19, 2713–2723, https://doi.org/10.5194/acp-19-2713-2019, https://doi.org/10.5194/acp-19-2713-2019, 2019
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This research utilizes several months of lidar measurements from the Perdigão 2017 campaign to investigate flow recirculation zones that occur at the two parallel ridges at the measurement site in Portugal. We found that recirculation occurs in over 50 % of the time when the wind direction is perpendicular to the direction of the ridges. Moreover, we show three-dimensional changes of the zones along the ridges and the implications of recirculation on wind turbines that are operating downstream.
Anne Wiese, Joanna Staneva, Johannes Schulz-Stellenfleth, Arno Behrens, Luciana Fenoglio-Marc, and Jean-Raymond Bidlot
Ocean Sci., 14, 1503–1521, https://doi.org/10.5194/os-14-1503-2018, https://doi.org/10.5194/os-14-1503-2018, 2018
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The increase of data quality of wind and wave measurements provided by the new Sentinel-3A satellite in coastal areas is demonstrated compared to measurements of older satellites with in situ data and spectral wave model simulations. Furthermore, the sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, where an hourly temporal resolution is necessary to represent the peak of extreme events better.
Joseph C. Y. Lee, M. Jason Fields, and Julie K. Lundquist
Wind Energ. Sci., 3, 845–868, https://doi.org/10.5194/wes-3-845-2018, https://doi.org/10.5194/wes-3-845-2018, 2018
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To find the ideal way to quantify long-term wind-speed variability, we compare 27 metrics using 37 years of wind and energy data. We conclude that the robust coefficient of variation can effectively assess and correlate wind-speed and energy-production variabilities. We derive adequate results via monthly mean data, whereas uncertainty arises in interannual variability calculations. We find that reliable estimates of wind-speed variability require 10 ± 3 years of monthly mean wind data.
Jessica M. Tomaszewski, Julie K. Lundquist, Matthew J. Churchfield, and Patrick J. Moriarty
Wind Energ. Sci., 3, 833–843, https://doi.org/10.5194/wes-3-833-2018, https://doi.org/10.5194/wes-3-833-2018, 2018
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Wind energy development has increased rapidly in rural locations of the United States, areas that also serve general aviation airports. The spinning rotor of a wind turbine creates an area of increased turbulence, and we question if this turbulent air could pose rolling hazards for light aircraft flying behind turbines. We analyze high-resolution simulations of wind flowing past a turbine to quantify the rolling risk and find that wind turbines pose no significant roll hazards to light aircraft.
Michel Tchilibou, Lionel Gourdeau, Rosemary Morrow, Guillaume Serazin, Bughsin Djath, and Florent Lyard
Ocean Sci., 14, 1283–1301, https://doi.org/10.5194/os-14-1283-2018, https://doi.org/10.5194/os-14-1283-2018, 2018
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This paper is motivated by the next SWOT altimetric mission dedicated to the observation of mesoscale and submesoscale oceanic features. It focuses on tropical areas with a strong discrepancy in the spectral signature between altimetry and models. The paper reviews the spectral signature of tropical turbulence which presents a rich variety of phenomena depending on the latitudinal dependence of the Coriolis force. Internal tides observed by altimetry explain the discrepancy with the model.
Nicola Bodini, Julie K. Lundquist, and Rob K. Newsom
Atmos. Meas. Tech., 11, 4291–4308, https://doi.org/10.5194/amt-11-4291-2018, https://doi.org/10.5194/amt-11-4291-2018, 2018
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Turbulence within the atmospheric boundary layer is critically important to transfer heat, momentum, and moisture. Currently, improved turbulence parametrizations are crucially needed to refine the accuracy of model results at fine horizontal scales. In this study, we calculate turbulence dissipation rate from sonic anemometers and discuss a novel approach to derive turbulence dissipation from profiling lidar measurements.
Rochelle P. Worsnop, Michael Scheuerer, Thomas M. Hamill, and Julie K. Lundquist
Wind Energ. Sci., 3, 371–393, https://doi.org/10.5194/wes-3-371-2018, https://doi.org/10.5194/wes-3-371-2018, 2018
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This paper uses four statistical methods to generate probabilistic wind speed and power ramp forecasts from the High Resolution Rapid Refresh model. The results show that these methods can provide necessary uncertainty information of power ramp forecasts. These probabilistic forecasts can aid in decisions regarding power production and grid integration of wind power.
Barbara Altstädter, Andreas Platis, Michael Jähn, Holger Baars, Janine Lückerath, Andreas Held, Astrid Lampert, Jens Bange, Markus Hermann, and Birgit Wehner
Atmos. Chem. Phys., 18, 8249–8264, https://doi.org/10.5194/acp-18-8249-2018, https://doi.org/10.5194/acp-18-8249-2018, 2018
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This article describes the appearance of ultrafine aerosol particles (size < 12 nm) within the atmospheric boundary layer under cloudy conditions. New particle formation (NPF) was observed with the ALADINA unmanned aerial system in relation to increased turbulence near the inversion layer. Fast mixing processes and rapid dilution of surrounding air led to an insufficient particle growth rate, seen in sporadic clusters at ground. These events might not have been classified as NPF by surface data.
Astrid Lampert, Jörg Hartmann, Falk Pätzold, Lennart Lobitz, Peter Hecker, Katrin Kohnert, Eric Larmanou, Andrei Serafimovich, and Torsten Sachs
Atmos. Meas. Tech., 11, 2523–2536, https://doi.org/10.5194/amt-11-2523-2018, https://doi.org/10.5194/amt-11-2523-2018, 2018
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We compared two different fast-response humidity sensors simultaneously on different airborne platforms. One is a particular, well-establed Lyman-alpha hygrometer that has been used for decades as the standard for fast airborne humidity measurements. However, it is not available any more. The other one is a hygrometer based on the absorption of infrared radiation, from LI-COR. For an environment of low vibrations, the LI-COR sensor is suitable for fast airborne water vapour measurements.
Joseph C. Y. Lee and Julie K. Lundquist
Geosci. Model Dev., 10, 4229–4244, https://doi.org/10.5194/gmd-10-4229-2017, https://doi.org/10.5194/gmd-10-4229-2017, 2017
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We evaluate the wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF) model, a powerful tool to simulate wind farms and their meteorological impacts numerically. In our case study, the WFP simulations with fine vertical grid resolution are skilful in matching the observed winds and the actual power productions. Moreover, the WFP tends to underestimate power in windy conditions. We also illustrate that the modeled wind speed is a critical determinant to improve the WFP.
Nicola Bodini, Dino Zardi, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 2881–2896, https://doi.org/10.5194/amt-10-2881-2017, https://doi.org/10.5194/amt-10-2881-2017, 2017
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Wind turbine wakes have considerable impacts on downwind turbines in wind farms, given their slower wind speeds and increased turbulence. Based on lidar measurements, we apply a quantitative algorithm to assess wake parameters for wakes from a row of four turbines in CWEX-13 campaign. We describe how wake characteristics evolve, and for the first time we quantify the relation between wind veer and a stretching of the wake structures, and we highlight different results for inner and outer wakes.
Caroline Brosy, Karina Krampf, Matthias Zeeman, Benjamin Wolf, Wolfgang Junkermann, Klaus Schäfer, Stefan Emeis, and Harald Kunstmann
Atmos. Meas. Tech., 10, 2773–2784, https://doi.org/10.5194/amt-10-2773-2017, https://doi.org/10.5194/amt-10-2773-2017, 2017
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Vertical and horizontal sounding of the planetary boundary layer can be complemented by unmanned aerial vehicles (UAV). Utilizing a multicopter-type UAV spatial sampling of air and simultaneously sensing of meteorological variables is possible for the study of surface exchange processes. During stable atmospheric conditions, vertical methane gradients of about 300 ppb were found. This approach extended the vertical profile height of existing tower-based infrastructure by a factor of five.
Clara M. St. Martin, Julie K. Lundquist, Andrew Clifton, Gregory S. Poulos, and Scott J. Schreck
Wind Energ. Sci., 2, 295–306, https://doi.org/10.5194/wes-2-295-2017, https://doi.org/10.5194/wes-2-295-2017, 2017
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We use upwind and nacelle-based measurements from a wind turbine and investigate the influence of atmospheric stability and turbulence regimes on nacelle transfer functions (NTFs) used to correct nacelle-mounted anemometer measurements. This work shows that correcting nacelle winds using NTFs results in similar energy production estimates to those obtained using upwind tower-based wind speeds. Further, stability and turbulence metrics have been found to have an effect on NTFs below rated speed.
Burkard Baschek, Friedhelm Schroeder, Holger Brix, Rolf Riethmüller, Thomas H. Badewien, Gisbert Breitbach, Bernd Brügge, Franciscus Colijn, Roland Doerffer, Christiane Eschenbach, Jana Friedrich, Philipp Fischer, Stefan Garthe, Jochen Horstmann, Hajo Krasemann, Katja Metfies, Lucas Merckelbach, Nino Ohle, Wilhelm Petersen, Daniel Pröfrock, Rüdiger Röttgers, Michael Schlüter, Jan Schulz, Johannes Schulz-Stellenfleth, Emil Stanev, Joanna Staneva, Christian Winter, Kai Wirtz, Jochen Wollschläger, Oliver Zielinski, and Friedwart Ziemer
Ocean Sci., 13, 379–410, https://doi.org/10.5194/os-13-379-2017, https://doi.org/10.5194/os-13-379-2017, 2017
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The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the heavily used German Bight in the North Sea. The automated observing and modelling system is designed to monitor real-time conditions, to provide short-term forecasts and data products, and to assess the impact of anthropogenically induced change.
Laura Bianco, Katja Friedrich, James M. Wilczak, Duane Hazen, Daniel Wolfe, Ruben Delgado, Steven P. Oncley, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 1707–1721, https://doi.org/10.5194/amt-10-1707-2017, https://doi.org/10.5194/amt-10-1707-2017, 2017
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XPIA is a study held in 2015 at NOAA's Boulder Atmospheric Observatory facility, aimed at assessing remote-sensing capabilities for wind energy applications. We use well-defined reference systems to validate temperature retrieved by two microwave radiometers (MWRs) and virtual temperature measured by wind profiling radars with radio acoustic sounding systems (RASSs). Water vapor density and relative humidity by the MWRs were also compared with similar measurements from the reference systems.
Rob K. Newsom, W. Alan Brewer, James M. Wilczak, Daniel E. Wolfe, Steven P. Oncley, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 1229–1240, https://doi.org/10.5194/amt-10-1229-2017, https://doi.org/10.5194/amt-10-1229-2017, 2017
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Doppler lidars are remote sensing instruments that use infrared light to measure wind velocity in the lowest 2 to 3 km of the atmosphere. Quantifying the uncertainty in these measurements is crucial for applications ranging from wind resource assessment to model data assimilation. In this study, we evaluate three methods for estimating the random uncertainty by comparing the lidar wind measurements with nearly collocated in situ wind measurements at multiple levels on a tall tower.
Mithu Debnath, Giacomo Valerio Iungo, W. Alan Brewer, Aditya Choukulkar, Ruben Delgado, Scott Gunter, Julie K. Lundquist, John L. Schroeder, James M. Wilczak, and Daniel Wolfe
Atmos. Meas. Tech., 10, 1215–1227, https://doi.org/10.5194/amt-10-1215-2017, https://doi.org/10.5194/amt-10-1215-2017, 2017
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The XPIA experiment was conducted in 2015 at the Boulder Atmospheric Observatory to estimate capabilities of various remote-sensing techniques for the characterization of complex atmospheric flows. Among different tests, XPIA provided the unique opportunity to perform simultaneous virtual towers with Ka-band radars and scanning Doppler wind lidars. Wind speed and wind direction were assessed against lidar profilers and sonic anemometer data, highlighting a good accuracy of the data retrieved.
Mithu Debnath, G. Valerio Iungo, Ryan Ashton, W. Alan Brewer, Aditya Choukulkar, Ruben Delgado, Julie K. Lundquist, William J. Shaw, James M. Wilczak, and Daniel Wolfe
Atmos. Meas. Tech., 10, 431–444, https://doi.org/10.5194/amt-10-431-2017, https://doi.org/10.5194/amt-10-431-2017, 2017
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Triple RHI scans were performed with three simultaneous scanning Doppler wind lidars and assessed with lidar profiler and sonic anemometer data. This test is part of the XPIA experiment. The scan strategy consists in two lidars performing co-planar RHI scans, while a third lidar measures the transversal velocity component. The results show that horizontal velocity and wind direction are measured with good accuracy, while the vertical velocity is typically measured with a significant error.
Katherine McCaffrey, Paul T. Quelet, Aditya Choukulkar, James M. Wilczak, Daniel E. Wolfe, Steven P. Oncley, W. Alan Brewer, Mithu Debnath, Ryan Ashton, G. Valerio Iungo, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 393–407, https://doi.org/10.5194/amt-10-393-2017, https://doi.org/10.5194/amt-10-393-2017, 2017
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During the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) field campaign, the wake and flow distortion from a 300-meter meteorological tower was identified using pairs of sonic anemometers mounted on opposite sides of the tower, as well as profiling and scanning lidars. Wind speed deficits up to 50% and TKE increases of 2 orders of magnitude were observed at wind directions in the wake, along with wind direction differences (flow deflection) outside of the wake.
Aditya Choukulkar, W. Alan Brewer, Scott P. Sandberg, Ann Weickmann, Timothy A. Bonin, R. Michael Hardesty, Julie K. Lundquist, Ruben Delgado, G. Valerio Iungo, Ryan Ashton, Mithu Debnath, Laura Bianco, James M. Wilczak, Steven Oncley, and Daniel Wolfe
Atmos. Meas. Tech., 10, 247–264, https://doi.org/10.5194/amt-10-247-2017, https://doi.org/10.5194/amt-10-247-2017, 2017
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This paper discusses trade-offs among various wind measurement strategies using scanning Doppler lidars. It is found that the trade-off exists between being able to make highly precise point measurements versus covering large spatial extents. The highest measurement precision is achieved when multiple lidar systems make wind measurements at one point in space, while highest spatial coverage is achieved through using single lidar scanning measurements and using complex retrieval techniques.
Clara M. St. Martin, Julie K. Lundquist, Andrew Clifton, Gregory S. Poulos, and Scott J. Schreck
Wind Energ. Sci., 1, 221–236, https://doi.org/10.5194/wes-1-221-2016, https://doi.org/10.5194/wes-1-221-2016, 2016
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We use turbine nacelle-based measurements and measurements from an upwind tower to calculate wind turbine power curves and predict the production of energy. We explore how different atmospheric parameters impact these power curves and energy production estimates. Results show statistically significant differences between power curves and production estimates calculated with turbulence and stability filters, and we suggest implementing an additional step in analyzing power performance data.
Emil V. Stanev, Johannes Schulz-Stellenfleth, Joanna Staneva, Sebastian Grayek, Sebastian Grashorn, Arno Behrens, Wolfgang Koch, and Johannes Pein
Ocean Sci., 12, 1105–1136, https://doi.org/10.5194/os-12-1105-2016, https://doi.org/10.5194/os-12-1105-2016, 2016
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This paper describes coastal ocean forecasting practices exemplified for the North Sea and Baltic Sea. It identifies new challenges, most of which are associated with the nonlinear behavior of coastal oceans. It describes the assimilation of remote sensing, in situ and HF radar data, prediction of wind waves and storm surges, as well as applications to search and rescue operations. Seamless applications to coastal and estuarine modeling are also presented.
Guylaine Canut, Fleur Couvreux, Marie Lothon, Dominique Legain, Bruno Piguet, Astrid Lampert, William Maurel, and Eric Moulin
Atmos. Meas. Tech., 9, 4375–4386, https://doi.org/10.5194/amt-9-4375-2016, https://doi.org/10.5194/amt-9-4375-2016, 2016
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Turbulent processes of the atmospheric boundary layer contribute the most to transfers between the surface and the atmosphere. Typically, turbulent boundary layer parameters are measured by sonic anemometers on masts and by research aircraft. This is to measure in situ turbulent parameters in the planetary boundary layer (PBL) at altitudes above 50 m. For this purpose, our team have developed a system under a tethered balloon which has been in use since 2010.
Nicola Bodini, Julie K. Lundquist, Dino Zardi, and Mark Handschy
Wind Energ. Sci., 1, 115–128, https://doi.org/10.5194/wes-1-115-2016, https://doi.org/10.5194/wes-1-115-2016, 2016
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Year-to-year variability of wind speeds limits the certainty of wind-plant preconstruction energy estimates ("resource assessments"). Using 62-year records from 60 stations across Canada we show that resource highs and lows persist for decades, which makes estimates 2–3 times less certain than if annual levels were uncorrelated. Comparing chronological data records with randomly permuted versions of the same data reveals this in an unambiguous and easy-to-understand way.
Astrid Lampert, Falk Pätzold, Maria Antonia Jiménez, Lennart Lobitz, Sabrina Martin, Gerald Lohmann, Guylaine Canut, Dominique Legain, Jens Bange, Dani Martínez-Villagrasa, and Joan Cuxart
Atmos. Chem. Phys., 16, 8009–8021, https://doi.org/10.5194/acp-16-8009-2016, https://doi.org/10.5194/acp-16-8009-2016, 2016
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For a large field experiment in summer 2011 in southern France (BLLAST campaign), the development of turbulence in the atmosphere was analysed during the afternoon and evening. Besides ground-based remote sensing and in situ observations, turbulence parameters were measured with an unmanned aerial vehicle and analysed by numerical simulation. Turbulence decreased during the afternoon, but increased after sunset due to local wind systems. Turbulent eddies lost symmetry during the transition.
B. Altstädter, A. Platis, B. Wehner, A. Scholtz, N. Wildmann, M. Hermann, R. Käthner, H. Baars, J. Bange, and A. Lampert
Atmos. Meas. Tech., 8, 1627–1639, https://doi.org/10.5194/amt-8-1627-2015, https://doi.org/10.5194/amt-8-1627-2015, 2015
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The unmanned research aircraft Carolo P360 "ALADINA" is a flexible tool for investigating the horizontal and vertical distribution of freshly formed particles in the atmospheric boundary layer (ABL) combined with measurements of turbulent fluxes derived by fast meteorological sensors. First results of a feasibility study show, among others, events of particle bursts in an internal
layer of the ABL. Comparisons with ground-based instruments and a lidar present the reliability of the new system.
J. K. Lundquist, M. J. Churchfield, S. Lee, and A. Clifton
Atmos. Meas. Tech., 8, 907–920, https://doi.org/10.5194/amt-8-907-2015, https://doi.org/10.5194/amt-8-907-2015, 2015
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Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications like wind energy, but their use often relies on assuming homogeneity in the wind. Using numerical simulations of stable flow past a wind turbine, we quantify the error expected because of the inhomogeneity of the flow. Large errors (30%) in winds are found near the wind turbine, but by three rotor diameters downwind, errors in the horizontal components have decreased to 15% of the inflow.
N. Wildmann, F. Kaufmann, and J. Bange
Atmos. Meas. Tech., 7, 3059–3069, https://doi.org/10.5194/amt-7-3059-2014, https://doi.org/10.5194/amt-7-3059-2014, 2014
N. Wildmann, M. Hofsäß, F. Weimer, A. Joos, and J. Bange
Adv. Sci. Res., 11, 55–61, https://doi.org/10.5194/asr-11-55-2014, https://doi.org/10.5194/asr-11-55-2014, 2014
N. Wildmann, S. Ravi, and J. Bange
Atmos. Meas. Tech., 7, 1027–1041, https://doi.org/10.5194/amt-7-1027-2014, https://doi.org/10.5194/amt-7-1027-2014, 2014
K. Schäfer, M. Elsasser, J. M. Arteaga-Salas, J. Gu, M. Pitz, J. Schnelle-Kreis, J. Cyrys, S. Emeis, A. S. H. Prevot, and R. Zimmermann
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-2235-2014, https://doi.org/10.5194/acpd-14-2235-2014, 2014
Revised manuscript not accepted
N. Wildmann, M. Mauz, and J. Bange
Atmos. Meas. Tech., 6, 2101–2113, https://doi.org/10.5194/amt-6-2101-2013, https://doi.org/10.5194/amt-6-2101-2013, 2013
Related subject area
Atmospheric sciences
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Implementation of a dry deposition module (DEPAC v3.11) in a large eddy simulation code (DALES v4.4)
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
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High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Cited articles
Abkar, M. and Porté-Agel, F.: A new wind-farm parameterization for
large-scale atmospheric models, J. Renew. Sustain. Ener.,
7, 013121, https://doi.org/10.1063/1.4907600, 2015. a
Ahsbahs, T., Badger, M., Volker, P., Hansen, K. S., and Hasager, C. B.: Applications of satellite winds for the offshore wind farm site Anholt, Wind Energ. Sci., 3, 573–588, https://doi.org/10.5194/wes-3-573-2018, 2018. a
Bärfuss, K., Hankers, R., Bitter, M., Feuerle, T., Schulz, H.,
Rausch, T., Platis, A., Bange, J., and Lampert, A.: In-situ airborne
measurements of atmospheric and sea surface parameters related to offshore
wind parks in the German Bight,
https://doi.org/10.1594/PANGAEA.902845, 2019. a
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface-Hydrology
Model with the Penn State-NCAR0 MM5 Modeling System. Part
I: Model Implementation and Sensitivity, Mon. Weather Rev., 129,
569–585, https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. a
Christiansen, M. B. and Hasager, C. B.: Wake effects of large offshore wind
farms identified from satellite SAR, Remote Sens. Environ., 98,
251–268, https://doi.org/10.1016/j.rse.2005.07.009, 2005. a
Corsmeier, U., Hankers, R., and Wieser, A.: Airborne turbulence measurements in
the lower troposphere onboard the research aircraft Dornier 128-6, D-IBUF,
Meteorol. Z., 10, 315–329,
https://doi.org/10.1127/0941-2948/2001/0010-0315,
2001. a
Djath, B., Schulz-Stellenfleth, J., and Cañadillas, B.: Impact of
atmospheric stability on X-band and C-band synthetic aperture radar
imagery of offshore windpark wakes, J. Renew. Sustain.
Ener., 10, 043301, https://doi.org/10.1063/1.5020437, 2018. a, b
Dörenkämper, M., Optis, M., Monahan, A., and Steinfeld, G.: On the
Offshore Advection of Boundary-Layer Structures and the Influence
on Offshore Wind Conditions, Bound.-Lay. Meteorol., 155,
459–482, https://doi.org/10.1007/s10546-015-0008-x, 2015. a
Emeis, S.: A simple analytical wind park model considering atmospheric
stability, Wind Energy, 13, 459–469, https://doi.org/10.1002/we.367, 2010. a
Emeis, S.: Wind energy meteorology: atmospheric physics for wind power
generation, Springer, 2nd Edn., 2018. a
Emeis, S., Siedersleben, S., Lampert, A., Platis, A., Bange, J., Djath, B.,
Schulz-Stellenfleth, J., and Neumann, T.: Exploring the wakes of large
offshore wind farms, J. Phys. Conf. Ser., 753, 092014,
https://doi.org/10.1088/1742-6596/753/9/092014,
2016. a
Eriksson, O., Lindvall, J., Breton, S.-P., and Ivanell, S.: Wake downstream of
the Lillgrund wind farm-A Comparison between LES using the actuator disc
method and a Wind farm Parametrization in WRF, J. Phys. Conf.
Ser., 625, p. 012028,
https://doi.org/10.1088/1742-6596/625/1/012028, 2015. a, b
Fitch, A. C., Olson, J. B., Lundquist, J. K., Dudhia, J., Gupta, A. K.,
Michalakes, J., and Barstad, I.: Local and Mesoscale Impacts of Wind
Farms as Parameterized in a Mesoscale NWP Model, Mon. Weather
Rev., 140, 3017–3038, https://doi.org/10.1175/MWR-D-11-00352.1, 2012. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v
Fraunhofer ISE: energy charts, available at:
https://https://www.energy-charts.de/, last access: 21 September 2019. a
Hahmann, A. N., Vincent, C. L., Peña, A., Lange, J., and Hasager, C. B.:
Wind climate estimation using WRF model output: method and model
sensitivities over the sea, Int. J. Climatol., 35, 3422–3439,
https://doi.org/10.1002/joc.4217, 2015. a
Hasager, C. B., Nielsen, M., Astrup, P., Barthelmie, R., Dellwik, E., Jensen,
N. O., Jørgensen, B. H., Pryor, S., Rathmann, O., and Furevik, B.:
Offshore wind resource estimation from satellite SAR wind field maps, Wind
Energy, 8, 403–419, https://doi.org/10.1002/we.150, 2005. a
Hasager, C. B., Vincent, P., Badger, J., Badger, M., Di Bella, A., Peña,
A., Husson, R., and Volker, P. J.: Using Satellite SAR to
Characterize the Wind Flow Around Offshore Wind Farms,
Energies, 8, 5413–5439, https://doi.org/10.3390/en8065413, 2015. a
Hersbach, H., Stoffelen, A., and de Haan, S.: An improved C-band
scatterometer ocean geophysical model function: CMOD5, J. Geophys. Res.,
112, C03006, https://doi.org/10.1029/2006JC003743, 2007. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci.
Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A.,
and Collins, W. D.: Radiative forcing by long-lived greenhouse gases:
Calculations with the AER radiative transfer models, J. Geophys. Res.,
113, D13103, https://doi.org/10.1029/2008JD009944, 2008. a
Ivanova, L. A. and Nadyozhina, E. D.: Numerical simulation of wind farm
influence on wind flow, Wind Engineering, 24, 257–269,
https://doi.org/10.1260/0309524001495620, 2000. a
Kain, J. S.: The Kain–Fritsch Convective Parameterization: An
Update, J. Appl. Meteorol. Clim., 43, 170–181,
https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004. a
Keith, D. W., DeCarolis, J. F., Denkenberger, D. C., Lenschow, D. H., Malyshev,
S. L., Pacala, S., and Rasch, P. J.: The influence of large-scale wind power
on global climate, P. Natl. Acad. Sci. USA, 101,
16115–16120, https://doi.org/10.1073/pnas.0406930101, 2004. a
Ladwig, W.: wrf-python (version 1.3.0) [Software], Tech. rep., UCAR, NCAR,
Boulder, Colorado, USA, available at: https://github.com/NCAR/wrf-python, last access: 14 September 2019. a
Lampert, A., Bärfuss, K., Platis, A., Siedersleben, S., Djath, B., Cañadillas, B., Hankers, R., Bitter, M., Feuerle, T., Schulz, H., Rausch, T., Angermann, M., Schwithal, A., Bange, J., Schulz-Stellenfleth, J., Neumann, T., and Emeis, S.: In-situ airborne measurements of atmospheric and sea surface parameters related to offshore wind parks in the German Bight, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-214, in review, 2019. a
Lee, J. C. Y. and Lundquist, J. K.: Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data, Geosci. Model Dev., 10, 4229–4244, https://doi.org/10.5194/gmd-10-4229-2017, 2017. a, b, c
Li, X., Chi, L., Chen, X., Ren, Y., and Lehner, S.: SAR observation and
numerical modeling of tidal current wakes at the East China Sea offshore wind
farm, J. Geophys. Res.-Oceans, 119, 4958–4971,
https://doi.org/10.1002/2014JC009822, 2014. a
Lim, K.-S. S. and Hong, S.-Y.: Development of an effective double-moment cloud
microphysics scheme with prognostic cloud condensation nuclei (CCN) for
weather and climate models, Mon. Weather Rev., 138, 1587–1612,
https://doi.org/10.1175/2009MWR2968.1, 2010. a
Mangara, R. J., Guo, Z., and Li, S.: Performance of the Wind Farm
Parameterization Scheme Coupled with the Weather Research and Forecasting
Model under Multiple Resolution Regimes for Simulating an Onshore Wind Farm,
Adv. Atmos. Sci., 36, 119–132,
https://doi.org/10.1007/s00376-018-8028-3, 2019. a
Miller, L. M. and Keith, D. W.: Climatic Impacts of Wind Power, Joule, 12, 2618–2632, https://doi.org/10.1016/j.joule.2018.09.009,
2018. a
Nakanishi, M. and Niino, H.: An improved Mellor–Yamada level-3 model: Its
numerical stability and application to a regional prediction of advection
fog, Bound.-Lay. Meteorol., 119, 397–407,
https://doi.org/10.1007/s10546-005-9030-8, 2006. a, b
National Center of Atmospheric Research (NCAR): WRF model, available at: http://www2.mmm.ucar.edu/wrf/users/downloads.htm, last access: 2 February 2017. a
Nygaard, N. G. and Hansen, S. D.: Wake effects between two neighbouring wind
farms, J. Phys. Conf. Ser., 753, 032020,
https://doi.org/10.1088/1742-6596/753/3/032020, 2016. a
Pan, Y. and Archer, C. L.: A Hybrid Wind-Farm Parametrization for Mesoscale and
Climate Models, Bound.-Lay. Meteorol., 168, 469–495,
https://doi.org/10.1007/s10546-018-0351-9, 2018. a
Platis, A., Siedersleben, S. K., Bange, J., Lampert, A., Baerfuss, K., Hankers,
R., Canadillas, B., Foreman, R., Schulz-Stellenfleth, J., Djath, B., Neuman,
T., and Emeis, S.: First in situ evidence of wakes in the far field behind
offshore wind farms, Sci. Rep., 8, 2163, https://doi.org/10.1038/s41598-018-20389-y,
2018. a, b, c, d
Redfern, S., Olson, J. B., Lundquist, J. K., and Clack, C. T.: Incorporation of
the Rotor-Equivalent Wind Speed into the Weather Research and Forecasting
Model's Wind Farm Parameterization, Mon. Weather Rev., 147, 1029–1046,
https://doi.org/10.1175/MWR-D-18-0194.1,
2019. a
Siedersleben, S. K., Lundquist, J. K., Platis, A., Bange, J., Bärfuss, K.,
Lampert, A., Cañadillas, B., Neumann, T., and Emeis, S.: Micrometeorological
impacts of offshore wind farms as seen in observations and simulations,
Environ. Res. Lett., 13, 124012,
https://doi.org/10.1088/1748-9326/aaea0b, 2018a. a, b
Siedersleben, S. K., Platis, A., Lundquist, J. K., Lampert, A., Bärfuss,
K., Cañadillas, B., Djath, B., Schulz-Stellenfleth, J., Bange, J.,
Neumann, T., and Emeis, S.: Evaluation of a Wind Farm Parametrization for
Mesoscale Atmospheric Flow Models with Aircraft Measurements, Meteorol.
Z., 27, 401–415,
https://doi.org/10.1127/metz/2018/0900, 2018b. a, b, c, d, e, f, g, h
Siedersleben, S. K., Platis, A., Lundquist, J. K., Djath, B., Lampert, A., Bärfuss, K., Canadillas, B., Schulz-Stellenfleth, J., Bange, J., Neumann, T., and Emeis, S.: Turbulent kinetic energy over large wind farms observed and simulated by the mesoscale model WRF (3.8.1) (Version 0.1) [Data set], Zenodo, https://doi.org/10.5281/zenodo.3490732, 2019. a, b
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., Duda, M., Huang,
X., Wang, W., and Powers, J.: A description of the advanced research WRF
version 3, NCAR, Tech. rep., Mesoscale and Microscale Meteorology
Division, National Center for Atmospheric Research, Boulder, Colorado, USA,
https://doi.org/10.5065/D68S4MVH, 2008. a, b
Skamarock, W. C.: Evaluating mesoscale NWP models using kinetic energy
spectra, Mon. Weather Rev., 132, 3019–3032, https://doi.org/10.1175/MWR2830.1, 2004. a
Smedman, A.-S., Bergström, H., and Grisogono, B.: Evolution of stable
internal boundary layers over a cold sea, J. Phys. Conf. Ser., 102,
1091–1099, https://doi.org/10.1029/96JC02782, 1997. a
Stauffer, R., Mayr, G. J., Dabernig, M., and Zeileis, A.: Somewhere over the
rainbow: How to make effective use of colors in meteorological
visualizations, B. Am. Meteorol. Soc., 96, 203–216,
https://doi.org/10.1175/BAMS-D-13-00155.1, 2015. a
Svensson, N., Bergström, H., Sahlée, E., and Rutgersson, A.: Stable
atmospheric conditions over the Baltic Sea: model evaluation and
climatology, Boreal Environ. Res., 21, 387–404, 2016. a
Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M., and DiMarco,
S. F.: True colors of oceanography: Guidelines for effective and accurate
colormap selection, Oceanography, 29, 9–13,
https://doi.org/10.5670/oceanog.2016.66, 2016. a
Vanderwende, B. J., Kosović, B., Lundquist, J. K., and Mirocha, J. D.:
Simulating effects of a wind-turbine array using LES and RANS, J.
Adv. Model. Earth Sy., 8, 1376–1390,
https://doi.org/10.1002/2016MS000652, 2016. a, b, c
Vautard, R., Thais, F., Tobin, I., Bréon, F.-M., De Lavergne, J.-g. D.,
Colette, A., Yiou, P., and Ruti, P. M.: Regional climate model simulations
indicate limited climatic impacts by operational and planned European wind
farms, Nat. Commun., 5, 3196, https://doi.org/10.1038/ncomms4196, 2014.
a
Verhoef, A., Portabella, M., Stoffelen, A., and Hersbach, H.: CMOD5. n-the
CMOD5 GMF for neutral winds, Tech. rep., KNMI, De Bilt,
Netherlands, 2008. a
Volker, P. J., Hahmann, A. N., Badger, J., and Jørgensen, H. E.: Prospects
for generating electricity by large onshore and offshore wind farms, Environ.
Res. Lett., 12, 034022,
https://doi.org/10.1088/1748-9326/aa5d86, 2017. a
Volker, P. J. H., Badger, J., Hahmann, A. N., and Ott, S.: The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF, Geosci. Model Dev., 8, 3715–3731, https://doi.org/10.5194/gmd-8-3715-2015, 2015. a, b, c, d
WindEurope: Offshore wind in Europe, available at:
https://windeurope.org/about-wind/reports (last access: 21 February 2018), 2017. a
Zuhlke, M., Fomferra, N., Brockmann, C., Peters, M., Veci, L., Malik, J., and Regner, P.: SNAP (sentinel application platform) and
the ESA sentinel 3 toolbox, in Proceedings of the Sentinel-3 for Science Workshop, Venice, Italy, Volume 734, 2015. a
Short summary
Wind farms affect local weather and microclimates. These effects can be simulated in weather models, usually by removing momentum at the location of the wind farm. Some debate exists whether additional turbulence should be added to capture the enhanced mixing of wind farms. By comparing simulations to measurements from airborne campaigns near offshore wind farms, we show that additional turbulence is necessary. Without added turbulence, the mixing is underestimated during stable conditions.
Wind farms affect local weather and microclimates. These effects can be simulated in weather...
