Articles | Volume 15, issue 13
https://doi.org/10.5194/gmd-15-5195-2022
© Author(s) 2022. 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-15-5195-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
07 Jul 2022
Model evaluation paper |
| 07 Jul 2022
| 07 Jul 2022
Evaluation of a forest parameterization to improve boundary layer flow simulations over complex terrain. A case study using WRF-LES V4.0.1
Julian Quimbayo-Duarte
CORRESPONDING AUTHOR
Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, Frankfurt am Main,
Germany
Grupo de Investigación de Calidad del Aire (GICA), Universidad Nacional de Colombia, Bogotá, 111071, Colombia
Johannes Wagner
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt e.V., Oberpfaffenhofen, Germany
Norman Wildmann
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt e.V., Oberpfaffenhofen, Germany
Thomas Gerz
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt e.V., Oberpfaffenhofen, Germany
Juerg Schmidli
Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, Frankfurt am Main,
Germany
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Norman Wildmann and Laszlo Györy
EGUsphere, https://doi.org/10.5194/egusphere-2025-241, https://doi.org/10.5194/egusphere-2025-241, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Fast temperature sensors are deployed on drones to accurately measure temperature changes and fluctuations in the atmosphere. Compared to standard sensors, these new sensors showed better accuracy, especially in rapidly changing temperatures. Over 100 drone flights confirmed the sensors' ability to measure temperature fast enough to compare to standard meteorological instruments. This new method provides valuable data for understanding atmospheric energy balance.
Johannes Kistner, Lars Neuhaus, and Norman Wildmann
Atmos. Meas. Tech., 17, 4941–4955, https://doi.org/10.5194/amt-17-4941-2024, https://doi.org/10.5194/amt-17-4941-2024, 2024
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We use a fleet of multicopter drones to measure wind. To improve the accuracy of this wind measurement and to evaluate this improvement, we conducted experiments with the drones in a wind tunnel under various conditions. This wind tunnel can generate different kinds and intensities of wind. Here we measured with the drones and with other sensors as a reference and compared the results. We were able to improve our wind measurement and show how accurately it works in different situations.
Linus Wrba, Antonia Englberger, Andreas Dörnbrack, Gerard Kilroy, and Norman Wildmann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-12, https://doi.org/10.5194/wes-2024-12, 2024
Revised manuscript under review for WES
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It is crucial to understand the loads and power production of wind turbines under different atmospheric situations (e.g. night and day changes). Computational simulations are a widely used tool to get more knowledge of the performance and the wake of wind turbines. In this study realistic velocity profiles of the atmosphere are used as input for simulations so that these simulations become more realistic. The generated realistic flow is used as inflow for wind-turbine simulations.
Andreas Forstmaier, Jia Chen, Florian Dietrich, Juan Bettinelli, Hossein Maazallahi, Carsten Schneider, Dominik Winkler, Xinxu Zhao, Taylor Jones, Carina van der Veen, Norman Wildmann, Moritz Makowski, Aydin Uzun, Friedrich Klappenbach, Hugo Denier van der Gon, Stefan Schwietzke, and Thomas Röckmann
Atmos. Chem. Phys., 23, 6897–6922, https://doi.org/10.5194/acp-23-6897-2023, https://doi.org/10.5194/acp-23-6897-2023, 2023
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Large cities emit greenhouse gases which contribute to global warming. In this study, we measured the release of one important green house gas, methane, in Hamburg. Multiple sources that contribute to methane emissions were located and quantified. Methane sources were found to be mainly caused by human activity (e.g., by release from oil and gas refineries). Moreover, potential natural sources have been located, such as the Elbe River and lakes.
Tamino Wetz and Norman Wildmann
Wind Energ. Sci., 8, 515–534, https://doi.org/10.5194/wes-8-515-2023, https://doi.org/10.5194/wes-8-515-2023, 2023
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In the present study, for the first time, the SWUF-3D fleet of multirotors is deployed for field measurements on an operating 2 MW wind turbine (WT) in complex terrain. The fleet of multirotors has the potential to fill the meteorological gap of observations in the near wake of WTs with high-temporal and high-spatial-resolution wind vector measurements plus temperature, humidity and pressure. The flow up- and downstream of the WT is measured simultaneously at multiple spatial positions.
Noviana Dewani, Mirjana Sakradzija, Linda Schlemmer, Ronny Leinweber, and Juerg Schmidli
Atmos. Chem. Phys., 23, 4045–4058, https://doi.org/10.5194/acp-23-4045-2023, https://doi.org/10.5194/acp-23-4045-2023, 2023
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A high daily variability of the normalized vertical velocity variance profiles in the convective boundary layer is observed using Doppler lidar data during the FESSTVaL campaign 2020–2021. The dependency of the normalized vertical velocity variance on several meteorological parameters explains that the moisture processes in the boundary layer contribute to the remaining variability. The finding suggests that a new vertical velocity scale that takes moist processes into account has to be defined.
Norman Wildmann and Tamino Wetz
Atmos. Meas. Tech., 15, 5465–5477, https://doi.org/10.5194/amt-15-5465-2022, https://doi.org/10.5194/amt-15-5465-2022, 2022
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Multicopter uncrewed aerial systems (UAS, also known as drones) are very easy to use systems for collecting data in the lowest part of the atmosphere. Wind and turbulence are parameters that are particularly important for understanding the dynamics in the atmosphere. Only with three-dimensional measurements of the wind can a full understanding can be achieved. In this study, we show how even the vertical wind through the UAS can be measured with good accuracy.
Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz
Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, https://doi.org/10.5194/acp-22-5859-2022, 2022
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Coal mining is an extensive source of anthropogenic methane emissions. In order to reduce and mitigate methane emissions, it is important to know how much and where the methane is emitted. We estimated coal mining methane emissions in Poland based on atmospheric methane measurements and particle dispersion modeling. In general, our emission estimates suggest higher emissions than expected by previous annual emission reports.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Sven Krautwurst, Konstantin Gerilowski, Jakob Borchardt, Norman Wildmann, Michał Gałkowski, Justyna Swolkień, Julia Marshall, Alina Fiehn, Anke Roiger, Thomas Ruhtz, Christoph Gerbig, Jaroslaw Necki, John P. Burrows, Andreas Fix, and Heinrich Bovensmann
Atmos. Chem. Phys., 21, 17345–17371, https://doi.org/10.5194/acp-21-17345-2021, https://doi.org/10.5194/acp-21-17345-2021, 2021
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Quantification of anthropogenic CH4 emissions remains challenging, but it is essential for near-term climate mitigation strategies. We use airborne remote sensing observations to assess bottom-up estimates of coal mining emissions from one of Europe's largest CH4 emission hot spots located in Poland. The analysis reveals that emissions from small groups of shafts can be disentangled, but caution is advised when comparing observations to commonly reported annual emissions.
Etienne Cheynet, Martin Flügge, Joachim Reuder, Jasna B. Jakobsen, Yngve Heggelund, Benny Svardal, Pablo Saavedra Garfias, Charlotte Obhrai, Nicolò Daniotti, Jarle Berge, Christiane Duscha, Norman Wildmann, Ingrid H. Onarheim, and Marte Godvik
Atmos. Meas. Tech., 14, 6137–6157, https://doi.org/10.5194/amt-14-6137-2021, https://doi.org/10.5194/amt-14-6137-2021, 2021
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The COTUR campaign explored the structure of wind turbulence above the ocean to improve the design of future multi-megawatt offshore wind turbines. Deploying scientific instruments offshore is both a financial and technological challenge. Therefore, lidar technology was used to remotely measure the wind above the ocean from instruments located on the seaside. The experimental setup is tailored to the study of the spatial correlation of wind gusts, which governs the wind loading on structures.
Julian Kostinek, Anke Roiger, Maximilian Eckl, Alina Fiehn, Andreas Luther, Norman Wildmann, Theresa Klausner, Andreas Fix, Christoph Knote, Andreas Stohl, and André Butz
Atmos. Chem. Phys., 21, 8791–8807, https://doi.org/10.5194/acp-21-8791-2021, https://doi.org/10.5194/acp-21-8791-2021, 2021
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Abundant mining and industrial activities in the Upper Silesian Coal Basin lead to large emissions of the potent greenhouse gas methane. This study quantifies these emissions with continuous, high-precision airborne measurements and dispersion modeling. Our emission estimates are in line with values reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) but significantly lower than values reported in the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2).
Tamino Wetz, Norman Wildmann, and Frank Beyrich
Atmos. Meas. Tech., 14, 3795–3814, https://doi.org/10.5194/amt-14-3795-2021, https://doi.org/10.5194/amt-14-3795-2021, 2021
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A fleet of quadrotors is presented as a system to measure the spatial distribution of atmospheric boundary layer flow. The big advantage of this approach is that multiple and flexible measurement points in space can be sampled synchronously. The algorithm to calculate the horizontal wind is based on the principle of aerodynamic drag and the related quadrotor dynamics. The validation reveals that an average accuracy of < 0.3 m s−1 for the wind speed and < 8° for the wind direction was achieved.
Alina Fiehn, Julian Kostinek, Maximilian Eckl, Theresa Klausner, Michał Gałkowski, Jinxuan Chen, Christoph Gerbig, Thomas Röckmann, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Pawel Jagoda, Norman Wildmann, Christian Mallaun, Rostyslav Bun, Anna-Leah Nickl, Patrick Jöckel, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 20, 12675–12695, https://doi.org/10.5194/acp-20-12675-2020, https://doi.org/10.5194/acp-20-12675-2020, 2020
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A severe reduction of greenhouse gas emissions is necessary to fulfill the Paris Agreement. We use aircraft- and ground-based in situ observations of trace gases and wind speed from two flights over the Upper Silesian Coal Basin, Poland, for independent emission estimation. The derived methane emission estimates are within the range of emission inventories, carbon dioxide estimates are in the lower range and carbon monoxide emission estimates are slightly higher than emission inventory values.
Sonja Gisinger, Johannes Wagner, and Benjamin Witschas
Atmos. Chem. Phys., 20, 10091–10109, https://doi.org/10.5194/acp-20-10091-2020, https://doi.org/10.5194/acp-20-10091-2020, 2020
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Gravity waves are an important coupling mechanism in the atmosphere. Measurements by two research aircraft during a mountain wave event over Scandinavia in 2016 revealed changes of the horizontal scales in the vertical velocity field and of momentum fluxes in the vicinity of the tropopause inversion. Idealized simulations revealed the presence of interfacial waves. They are found downstream of the mountain peaks, meaning that they horizontally transport momentum/energy away from their source.
Robert Menke, Nikola Vasiljević, Johannes Wagner, Steven P. Oncley, and Jakob Mann
Wind Energ. Sci., 5, 1059–1073, https://doi.org/10.5194/wes-5-1059-2020, https://doi.org/10.5194/wes-5-1059-2020, 2020
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The estimation of wind resources in complex terrain is challenging as the wind conditions change significantly over short distances, different to flat terrain, where spatial changes are small. We demonstrate in this work that wind lidars can remotely map wind resources over large areas. This will have implications for the planning of wind energy projects and ultimately reduce uncertainties in wind resource estimations in complex terrain, making such areas more interesting for future development.
Norman Wildmann, Eileen Päschke, Anke Roiger, and Christian Mallaun
Atmos. Meas. Tech., 13, 4141–4158, https://doi.org/10.5194/amt-13-4141-2020, https://doi.org/10.5194/amt-13-4141-2020, 2020
Tyler M. Bell, Petra Klein, Norman Wildmann, and Robert Menke
Atmos. Meas. Tech., 13, 1357–1371, https://doi.org/10.5194/amt-13-1357-2020, https://doi.org/10.5194/amt-13-1357-2020, 2020
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This study investigates the utility of using multi-Doppler retrievals during the Perdigão 2017 campaign. By combining scans from the multitude of Doppler lidars, it was possible to derive virtual towers that greatly extend the range of traditional in situ meteorological towers. Uncertainties from the measurements are analyzed and discussed. Despite multiple sources of error, it was found that the virtual towers are useful for analyzing the complex flows observed during the campaign.
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.
Johannes Wagner, Norman Wildmann, and Thomas Gerz
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-77, https://doi.org/10.5194/wes-2019-77, 2019
Preprint retracted
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The impact of a forest parameterization on the simulation of boundary layer flows over complex terrain is investigated. Short- and long-term simulations are run for 12 hours and 1.5 months, respectively, with and without forest parameterization and the results are compared to lidar and meteorological tower observations. The test cases are based on the Perdigao 2017 campaign.
Andreas Luther, Ralph Kleinschek, Leon Scheidweiler, Sara Defratyka, Mila Stanisavljevic, Andreas Forstmaier, Alexandru Dandocsi, Sebastian Wolff, Darko Dubravica, Norman Wildmann, Julian Kostinek, Patrick Jöckel, Anna-Leah Nickl, Theresa Klausner, Frank Hase, Matthias Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Andreas Fix, Anke Roiger, and André Butz
Atmos. Meas. Tech., 12, 5217–5230, https://doi.org/10.5194/amt-12-5217-2019, https://doi.org/10.5194/amt-12-5217-2019, 2019
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Methane ventilated from hard coal mines in the Upper Silesian
Coal Basin in Poland is measured with a mobile Fourier transform spectrometer EM27/SUN. The instrument was mounted on a truck driving in stop-and-go patterns downwind of the methane sources. The emissions are estimated with the cross-sectional flux method. Calculated emissions are in broad agreement with the E-PRTR database. Wind-related errors on the methane estimates dominate the error budget and typically amount to 20 %.
Jens Faber, Michael Gerding, Andreas Schneider, Andreas Dörnbrack, Henrike Wilms, Johannes Wagner, and Franz-Josef Lübken
Atmos. Meas. Tech., 12, 4191–4210, https://doi.org/10.5194/amt-12-4191-2019, https://doi.org/10.5194/amt-12-4191-2019, 2019
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Atmospheric measurements on rising balloons can be compromised by the balloon's wake. The aim of this study is to provide a tool for assessing the likelihood of encountering the balloon's wake at the position of the gondola. This includes an uncertainty analysis of the calculation and a retrieval of vertical winds. We find an average wake encounter probability of 28 % for a standard radiosonde. Additionally, we evaluate the influence of wake from smaller objects on turbulence measurements.
Johannes Wagner, Thomas Gerz, Norman Wildmann, and Kira Gramitzky
Atmos. Chem. Phys., 19, 1129–1146, https://doi.org/10.5194/acp-19-1129-2019, https://doi.org/10.5194/acp-19-1129-2019, 2019
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Long-term WRF-LES simulations were performed with a horizontal resolution of 200 m for a period of 49 days during the Perdigão campaign. Simulation results were used to characterize the meteorological conditions and to analyse characteristic flow patterns. It could be shown that thermally driven flows including low-level jets frequently occurred during the observation period. Model results were in very good agreement with observations in spite of the long simulation time.
Norman Wildmann, Nikola Vasiljevic, and Thomas Gerz
Atmos. Meas. Tech., 11, 3801–3814, https://doi.org/10.5194/amt-11-3801-2018, https://doi.org/10.5194/amt-11-3801-2018, 2018
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Wind turbines extract energy from the flow which manifests in a region of lower wind speeds and increased turbulence downstream of the rotor, the so-called wake. Understanding the characteristics of the wake is a key challenge for wind-energy research. A new strategy for measuring the wind in the wake with three synchronized lidar instruments is presented. The measurement points are automatically adapted to the prevailing wind direction to achieve continuous monitoring of wake properties.
Michael Keller, Nico Kröner, Oliver Fuhrer, Daniel Lüthi, Juerg Schmidli, Martin Stengel, Reto Stöckli, and Christoph Schär
Atmos. Chem. Phys., 18, 5253–5264, https://doi.org/10.5194/acp-18-5253-2018, https://doi.org/10.5194/acp-18-5253-2018, 2018
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Deep convection is often associated with thunderstorms and heavy rain events. In this study, the sensitivity of Alpine deep convective events to environmental parameters and climate warming is investigated. To this end, simulations are conducted at resolutions of 12 and 2 km. The results show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences are found in terms of the radiative feedbacks.
Romy Heller, Christiane Voigt, Stuart Beaton, Andreas Dörnbrack, Andreas Giez, Stefan Kaufmann, Christian Mallaun, Hans Schlager, Johannes Wagner, Kate Young, and Markus Rapp
Atmos. Chem. Phys., 17, 14853–14869, https://doi.org/10.5194/acp-17-14853-2017, https://doi.org/10.5194/acp-17-14853-2017, 2017
Andreas Schneider, Johannes Wagner, Jens Faber, Michael Gerding, and Franz-Josef Lübken
Atmos. Chem. Phys., 17, 7941–7954, https://doi.org/10.5194/acp-17-7941-2017, https://doi.org/10.5194/acp-17-7941-2017, 2017
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Wave breaking is studied with a combination of high-resolution turbulence observations with the balloon-borne instrument LITOS and mesoscale simulations with the WRF model. A relation between observed turbulent energy dissipation rates and the occurrence of wave patterns in modelled vertical winds is found, which is interpreted as the effect of wave saturation. The change of stability plays less of a role for mean dissipation for the flights examined.
Johannes Wagner, Andreas Dörnbrack, Markus Rapp, Sonja Gisinger, Benedikt Ehard, Martina Bramberger, Benjamin Witschas, Fernando Chouza, Stephan Rahm, Christian Mallaun, Gerd Baumgarten, and Peter Hoor
Atmos. Chem. Phys., 17, 4031–4052, https://doi.org/10.5194/acp-17-4031-2017, https://doi.org/10.5194/acp-17-4031-2017, 2017
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.
M. Lothon, F. Lohou, D. Pino, F. Couvreux, E. R. Pardyjak, J. Reuder, J. Vilà-Guerau de Arellano, P Durand, O. Hartogensis, D. Legain, P. Augustin, B. Gioli, D. H. Lenschow, I. Faloona, C. Yagüe, D. C. Alexander, W. M. Angevine, E Bargain, J. Barrié, E. Bazile, Y. Bezombes, E. Blay-Carreras, A. van de Boer, J. L. Boichard, A. Bourdon, A. Butet, B. Campistron, O. de Coster, J. Cuxart, A. Dabas, C. Darbieu, K. Deboudt, H. Delbarre, S. Derrien, P. Flament, M. Fourmentin, A. Garai, F. Gibert, A. Graf, J. Groebner, F. Guichard, M. A. Jiménez, M. Jonassen, A. van den Kroonenberg, V. Magliulo, S. Martin, D. Martinez, L. Mastrorillo, A. F. Moene, F. Molinos, E. Moulin, H. P. Pietersen, B. Piguet, E. Pique, C. Román-Cascón, C. Rufin-Soler, F. Saïd, M. Sastre-Marugán, Y. Seity, G. J. Steeneveld, P. Toscano, O. Traullé, D. Tzanos, S. Wacker, N. Wildmann, and A. Zaldei
Atmos. Chem. Phys., 14, 10931–10960, https://doi.org/10.5194/acp-14-10931-2014, https://doi.org/10.5194/acp-14-10931-2014, 2014
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
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
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Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
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
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
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
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
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.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
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.
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Short summary
The ultimate objective of this model evaluation is to improve boundary layer flow representation over complex terrain. The numerical model is tested against observations retrieved during the Perdigão 2017 field campaign (moderate complex terrain). We observed that the inclusion of a forest parameterization in the numerical model significantly improves the representation of the wind field in the atmospheric boundary layer.
The ultimate objective of this model evaluation is to improve boundary layer flow representation...
