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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Alex Rybchuk, Timothy W. Juliano, Julie K. Lundquist, David Rosencrans, Nicola Bodini, and Mike Optis
Wind Energ. Sci., 7, 2085–2098, https://doi.org/10.5194/wes-7-2085-2022, https://doi.org/10.5194/wes-7-2085-2022, 2022
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Numerical weather prediction models are used to predict how wind turbines will interact with the atmosphere. Here, we characterize the uncertainty associated with the choice of turbulence parameterization on modeled wakes. We find that simulated wind speed deficits in turbine wakes can be significantly sensitive to the choice of turbulence parameterization. As such, predictions of future generated power are also sensitive to turbulence parameterization choice.
Rachel Robey and Julie K. Lundquist
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Our work investigates the behavior of errors in remote-sensing wind lidar measurements due to turbulence. Using a virtual instrument, we measured winds in simulated atmospheric flows and decomposed the resulting error. Dominant error mechanisms, particularly vertical velocity variations and interactions with shear, were identified in ensemble data over three test cases. By analyzing the underlying mechanisms, the response of the error behavior to further varying flow conditions may be projected.
Beatriz Cañadillas, Maximilian Beckenbauer, Juan J. Trujillo, Martin Dörenkämper, Richard Foreman, Thomas Neumann, and Astrid Lampert
Wind Energ. Sci., 7, 1241–1262, https://doi.org/10.5194/wes-7-1241-2022, https://doi.org/10.5194/wes-7-1241-2022, 2022
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Scanning lidar measurements combined with meteorological sensors and mesoscale simulations reveal the strong directional and stability dependence of the wake strength in the direct vicinity of wind farm clusters.
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-113, https://doi.org/10.5194/amt-2022-113, 2022
Revised manuscript not accepted
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A multi-copter system has been calibrated to obtain wind vector measurements from its attitude. The calibration was performed using only the data from the autopilot and a particular set of flights. This procedure is easily repeatable for other rotary-wing systems, regardless of the size and weight. The multi-copter can sample the wind vector at 0.1 Hz frequency with a standard deviation of 0.7 ms-1 and 8°. This system will be used in future measurement campaigns inside off-shore wind farms.
Vincent Pronk, Nicola Bodini, Mike Optis, Julie K. Lundquist, Patrick Moriarty, Caroline Draxl, Avi Purkayastha, and Ethan Young
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In this paper, we have assessed to which extent mesoscale numerical weather prediction models are more accurate than state-of-the-art reanalysis products in characterizing the wind resource at heights of interest for wind energy. The conclusions of our work will be of primary importance to the wind industry for recommending the best data sources for wind resource modeling.
Tobias Klaas-Witt and Stefan Emeis
Wind Energ. Sci., 7, 413–431, https://doi.org/10.5194/wes-7-413-2022, https://doi.org/10.5194/wes-7-413-2022, 2022
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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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Wind turbine wake behavior in hilly terrain depends on various atmospheric conditions. We modeled a wind turbine located on top of a ridge in Portugal during typical nighttime and daytime atmospheric conditions and validated these model results with observational data. During nighttime conditions, the wake deflected downwards following the terrain. During daytime conditions, the wake deflected upwards. These results can provide insight into wind turbine siting and operation in hilly regions.
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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In this paper, we assess whether hub-height turbulence can easily be quantified from either other hub-height variables or ground-level measurements in complex terrain. We find a large variability across the three considered locations when trying to model hub-height turbulence intensity and turbulence kinetic energy. Our results highlight the nonlinear and complex nature of atmospheric turbulence, so that more powerful techniques should instead be recommended to model hub-height turbulence.
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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Winds decelerate upstream of a wind plant as turbines obstruct and extract energy from the flow. This effect is known as wind plant blockage. We assess how atmospheric stability modifies the upstream wind plant blockage. We find stronger stability amplifies this effect. We also explore different approaches to quantifying blockage from field-like observations. We find different methodologies may induce errors of the same order of magnitude as the blockage-induced velocity deficits.
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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This paper provides an overview of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign, held from 14 to 20 July 2018. This field campaign spanned a 1-week deployment to Colorado's San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. This overview paper provides insight into the campaign for a special issue focused on the datasets collected during LAPSE-RATE.
Antonia Englberger, Julie K. Lundquist, and Andreas Dörnbrack
Wind Energ. Sci., 5, 1623–1644, https://doi.org/10.5194/wes-5-1623-2020, https://doi.org/10.5194/wes-5-1623-2020, 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
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
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Air quality modeling intercomparison and multiscale ensemble chain for Latin America
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Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
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Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
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GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
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Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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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 in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification 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 model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
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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 rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
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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 more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
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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...
