Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-5897-2020
© 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-13-5897-2020
© 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
| 
30 Nov 2020
Model evaluation paper |
| 30 Nov 2020
| 30 Nov 2020
Sensitivity of aerosol optical properties to the aerosol size distribution over central Europe and the Mediterranean Basin using the WRF-Chem v.3.9.1.1 coupled model
Laura Palacios-Peña
CORRESPONDING AUTHOR
Physics of the Earth, Regional Campus of International Excellence (CEIT) “Campus Mare Nostrum”, University of Murcia,
Murcia , Spain
Jerome D. Fast
Pacific Northwest National Laboratory, Richland, WA, USA
Enrique Pravia-Sarabia
Physics of the Earth, Regional Campus of International Excellence (CEIT) “Campus Mare Nostrum”, University of Murcia,
Murcia , Spain
Pedro Jiménez-Guerrero
Physics of the Earth, Regional Campus of International Excellence (CEIT) “Campus Mare Nostrum”, University of Murcia,
Murcia , Spain
Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
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Matthew W. Christensen, Po-Lun Ma, Peng Wu, Adam C. Varble, Johannes Mülmenstädt, and Jerome D. Fast
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Siegfried Schobesberger, Emma L. D'Ambro, Lejish Vettikkat, Ben H. Lee, Qiaoyun Peng, David M. Bell, John E. Shilling, Manish Shrivastava, Mikhail Pekour, Jerome Fast, and Joel A. Thornton
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Jerome D. Fast, David M. Bell, Gourihar Kulkarni, Jiumeng Liu, Fan Mei, Georges Saliba, John E. Shilling, Kaitlyn Suski, Jason Tomlinson, Jian Wang, Rahul Zaveri, and Alla Zelenyuk
Atmos. Chem. Phys., 22, 11217–11238, https://doi.org/10.5194/acp-22-11217-2022, https://doi.org/10.5194/acp-22-11217-2022, 2022
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Amar Halifa-Marín, Miguel A. Torres-Vázquez, Enrique Pravia-Sarabia, Marc Lemus-Canovas, Pedro Jiménez-Guerrero, and Juan Pedro Montávez
Hydrol. Earth Syst. Sci., 26, 4251–4263, https://doi.org/10.5194/hess-26-4251-2022, https://doi.org/10.5194/hess-26-4251-2022, 2022
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Near-natural Iberian water resources have suddenly decreased since the 1980s. These declines have been promoted by the weakening (enhancement) of wintertime precipitation (the NAOi) in the most humid areas, whereas afforestation and drought intensification have played a crucial role in semi-arid areas. Future water management would benefit from greater knowledge of North Atlantic climate variability and reforestation/afforestation processes in semi-arid catchments.
Fan Mei, Mikhail S. Pekour, Darielle Dexheimer, Gijs de Boer, RaeAnn Cook, Jason Tomlinson, Beat Schmid, Lexie A. Goldberger, Rob Newsom, and Jerome D. Fast
Earth Syst. Sci. Data, 14, 3423–3438, https://doi.org/10.5194/essd-14-3423-2022, https://doi.org/10.5194/essd-14-3423-2022, 2022
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Shuaiqi Tang, Jerome D. Fast, Kai Zhang, Joseph C. Hardin, Adam C. Varble, John E. Shilling, Fan Mei, Maria A. Zawadowicz, and Po-Lun Ma
Geosci. Model Dev., 15, 4055–4076, https://doi.org/10.5194/gmd-15-4055-2022, https://doi.org/10.5194/gmd-15-4055-2022, 2022
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Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Patricia Tarín-Carrasco, Ulas Im, Camilla Geels, Laura Palacios-Peña, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 22, 3945–3965, https://doi.org/10.5194/acp-22-3945-2022, https://doi.org/10.5194/acp-22-3945-2022, 2022
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The evidence of the effects of atmospheric pollution (and particularly fine particulate matter, PM2.5) on human mortality is now unquestionable. Here, 895 000 annual premature deaths (PD) are estimated for the present (1991–2010), which increases to 1 540 000 in the year 2050 due to the ageing of the European population. The implementation of a mitigation scenario (80 % of the energy production in Europe from renewable sources) could lead to a decrease of over 60 000 annual PD for the year 2050.
Patricia Tarín-Carrasco, Sofia Augusto, Laura Palacios-Peña, Nuno Ratola, and Pedro Jiménez-Guerrero
Nat. Hazards Earth Syst. Sci., 21, 2867–2880, https://doi.org/10.5194/nhess-21-2867-2021, https://doi.org/10.5194/nhess-21-2867-2021, 2021
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Uncontrolled wildfires have a substantial impact on the environment and local populations. Although most southern European countries have been impacted by wildfires in the last decades, Portugal has the highest percentage of burned area compared to its whole territory. Under this umbrella, associations between large fires, PM10, and all-cause and cause-specific mortality (circulatory and respiratory) have been explored using Poisson regression models for 2001–2016.
Enrique Pravia-Sarabia, Juan José Gómez-Navarro, Pedro Jiménez-Guerrero, and Juan Pedro Montávez
Atmos. Chem. Phys., 21, 13353–13368, https://doi.org/10.5194/acp-21-13353-2021, https://doi.org/10.5194/acp-21-13353-2021, 2021
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Given the hazardous nature of medicanes, studies focused on understanding and quantifying the processes governing their formation have become paramount for present and future disaster risk reduction. Therefore, enhancing the modeling and forecasting capabilities of such events is of crucial importance. In this sense, the authors find that the microphysical processes, and specifically the wind--sea salt aerosol feedback, play a key role in their development and thus should not be neglected.
Maria A. Zawadowicz, Kaitlyn Suski, Jiumeng Liu, Mikhail Pekour, Jerome Fast, Fan Mei, Arthur J. Sedlacek, Stephen Springston, Yang Wang, Rahul A. Zaveri, Robert Wood, Jian Wang, and John E. Shilling
Atmos. Chem. Phys., 21, 7983–8002, https://doi.org/10.5194/acp-21-7983-2021, https://doi.org/10.5194/acp-21-7983-2021, 2021
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This paper describes the results of a recent field campaign in the eastern North Atlantic, where two mass spectrometers were deployed aboard a research aircraft to measure the chemistry of aerosols and trace gases. Very clean conditions were found, dominated by local sulfate-rich acidic aerosol and very aged organics. Evidence of
long-range transport of aerosols from the continents was also identified.
Jiumeng Liu, Liz Alexander, Jerome D. Fast, Rodica Lindenmaier, and John E. Shilling
Atmos. Chem. Phys., 21, 5101–5116, https://doi.org/10.5194/acp-21-5101-2021, https://doi.org/10.5194/acp-21-5101-2021, 2021
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To bridge the gaps in modeling and observational results due to insufficient understanding of aerosol properties, co-located measurements of aerosols and trace gases were conducted at SGP during the HI-SCALE campaign. Organic aerosols at the SGP site exhibited to be highly oxidized, and biogenic emissions appear to largely control the formation of organic aerosols. Seasonal variations of sources and meteorological impacts likely resulted in the highly oxygenated feature of aerosols.
Sonia Jerez, Laura Palacios-Peña, Claudia Gutiérrez, Pedro Jiménez-Guerrero, Jose María López-Romero, Enrique Pravia-Sarabia, and Juan Pedro Montávez
Geosci. Model Dev., 14, 1533–1551, https://doi.org/10.5194/gmd-14-1533-2021, https://doi.org/10.5194/gmd-14-1533-2021, 2021
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This research explores the role of aerosols when modeling surface solar radiation at regional scales (over Europe). A set of model experiments was performed with and without dynamical modeling of atmospheric aerosols and their direct and indirect effects on radiation. Results showed significant differences in the simulated solar radiation, mainly driven by the aerosol impact on cloudiness, which calls for caution when interpreting model experiments that do not include aerosols.
José María López-Romero, Juan Pedro Montávez, Sonia Jerez, Raquel Lorente-Plazas, Laura Palacios-Peña, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 21, 415–430, https://doi.org/10.5194/acp-21-415-2021, https://doi.org/10.5194/acp-21-415-2021, 2021
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The effect of aerosols on regional climate simulations presents large uncertainties due to their complex and non-linear interactions with a wide variety of factors, including aerosol–radiation and aerosol–cloud interactions. We show how these interactions are strongly conditioned by the meteorological situation and the type of aerosol. While natural aerosols tend to increase precipitation in some areas, anthropogenic aerosols decrease the number of rainy days in some pollutant regions.
Enrique Pravia-Sarabia, Juan José Gómez-Navarro, Pedro Jiménez-Guerrero, and Juan Pedro Montávez
Geosci. Model Dev., 13, 6051–6075, https://doi.org/10.5194/gmd-13-6051-2020, https://doi.org/10.5194/gmd-13-6051-2020, 2020
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This work shows TITAM, a time-independent tracking algorithm specifically suited for Mediterranean tropical-like cyclones, often referred to as medicanes. The methodology developed has the capacity to track multiple simultaneous cyclones, the ability to track a medicane in the presence of intense extratropical lows, and the potential to separate the medicane from other similar structures by handling the intermittent loss of structure and managing the tilting of the axis.
Laura Palacios-Peña, Philip Stier, Raquel Lorente-Plazas, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 20, 9679–9700, https://doi.org/10.5194/acp-20-9679-2020, https://doi.org/10.5194/acp-20-9679-2020, 2020
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It is widely known that the impact of aerosol–radiation and aerosol–cloud interactions on the radiative forcing is subject to large uncertainties. This is mainly due to the lack of understanding of aerosol optical properties and vertical distribution, whose uncertainties come from different processes. This work attempts to quantify the sensitivity of aerosol optical properties and their vertical distribution to key physico-chemical processes.
Patricia Tarín-Carrasco, María Morales-Suárez-Varela, Ulas Im, Jørgen Brandt, Laura Palacios-Peña, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 19, 9385–9398, https://doi.org/10.5194/acp-19-9385-2019, https://doi.org/10.5194/acp-19-9385-2019, 2019
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Air pollution has important implications for human health and external societal costs and is closely related to climate change. This work assesses the impacts of present and future air pollution on several cardiovascular and respiratory pathologies and estimates the costs associated with these health impacts on the European population. Premature deaths are the most important problem in terms of cases and costs (418 700 cases and EUR 158 billion per year, increasing by 17 % in the future).
Laura Palacios-Peña, Pedro Jiménez-Guerrero, Rocío Baró, Alessandra Balzarini, Roberto Bianconi, Gabriele Curci, Tony Christian Landi, Guido Pirovano, Marje Prank, Angelo Riccio, Paolo Tuccella, and Stefano Galmarini
Atmos. Chem. Phys., 19, 2965–2990, https://doi.org/10.5194/acp-19-2965-2019, https://doi.org/10.5194/acp-19-2965-2019, 2019
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The main uncertainties regarding the estimation of changes in the Earth’s energy budget are related to the role of atmospheric aerosols. Our study evaluates the representation of aerosol optical properties by different atmospheric chemistry models against remote-sensing observations in order to reduce this uncertainty. Results show that the representation of aerosol optical properties is strongly dependent on the used model.
Gabriele Curci, Ummugulsum Alyuz, Rocio Barò, Roberto Bianconi, Johannes Bieser, Jesper H. Christensen, Augustin Colette, Aidan Farrow, Xavier Francis, Pedro Jiménez-Guerrero, Ulas Im, Peng Liu, Astrid Manders, Laura Palacios-Peña, Marje Prank, Luca Pozzoli, Ranjeet Sokhi, Efisio Solazzo, Paolo Tuccella, Alper Unal, Marta G. Vivanco, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 19, 181–204, https://doi.org/10.5194/acp-19-181-2019, https://doi.org/10.5194/acp-19-181-2019, 2019
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Atmospheric carbonaceous aerosols are able to absorb solar radiation and they continue to contribute some of the largest uncertainties in projected climate change. One important detail is how the chemical species are arranged inside each particle, i.e. the knowledge of their mixing state. We use an ensemble of regional model simulations to test different mixing state assumptions and found that a combination of internal and external mixing may better reproduce sunphotometer observations.
Rocío Baró, Pedro Jiménez-Guerrero, Martin Stengel, Dominik Brunner, Gabriele Curci, Renate Forkel, Lucy Neal, Laura Palacios-Peña, Nicholas Savage, Martijn Schaap, Paolo Tuccella, Hugo Denier van der Gon, and Stefano Galmarini
Atmos. Chem. Phys., 18, 15183–15199, https://doi.org/10.5194/acp-18-15183-2018, https://doi.org/10.5194/acp-18-15183-2018, 2018
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Particles in the atmosphere, such as pollution, desert dust, and volcanic ash, have an impact on meteorology. They interact with incoming radiation resulting in a cooling effect of the atmosphere. Today, the use of meteorology and chemistry models help us to understand these processes, but there are a lot of uncertainties. The goal of this work is to evaluate how these interactions are represented in the models by comparing them to satellite data to see how close they are to reality.
Ulas Im, Jesper Heile Christensen, Camilla Geels, Kaj Mantzius Hansen, Jørgen Brandt, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Peng Liu, Uarporn Nopmongcol, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta G. Vivanco, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 8929–8952, https://doi.org/10.5194/acp-18-8929-2018, https://doi.org/10.5194/acp-18-8929-2018, 2018
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We evaluate the impact of global and regional anthropogenic emission reductions on major air pollutant levels over Europe and North America, using a multi-model ensemble of regional chemistry and transport models. Results show that ozone levels are largely driven by long-range transport over both continents while other pollutants such as carbon monoxide or aerosols are mainly controlled by domestic sources. Use of multi-model ensembles can help to reduce the uncertainties in individual models.
Stefano Galmarini, Ioannis Kioutsioukis, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Roberto Bellasio, Anna M. K. Benedictow, Roberto Bianconi, Johannes Bieser, Joergen Brandt, Jesper H. Christensen, Augustin Colette, Gabriele Curci, Yanko Davila, Xinyi Dong, Johannes Flemming, Xavier Francis, Andrea Fraser, Joshua Fu, Daven K. Henze, Christian Hogrefe, Ulas Im, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Jan Eiof Jonson, Nutthida Kitwiroon, Astrid Manders, Rohit Mathur, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marie Prank, Martin Schultz, Rajeet S. Sokhi, Kengo Sudo, Paolo Tuccella, Toshihiko Takemura, Takashi Sekiya, and Alper Unal
Atmos. Chem. Phys., 18, 8727–8744, https://doi.org/10.5194/acp-18-8727-2018, https://doi.org/10.5194/acp-18-8727-2018, 2018
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An ensemble of model results relating to ozone concentrations in Europe in 2010 has been produced and studied. The novelty consists in the fact that the ensemble is made of results of models working at two different scales (regional and global), therefore contributing in detail two different parts of the atmospheric spectrum. The ensemble defined as a hybrid has been studied in detail and shown to bring additional value to the assessment of air quality.
Ulas Im, Jørgen Brandt, Camilla Geels, Kaj Mantzius Hansen, Jesper Heile Christensen, Mikael Skou Andersen, Efisio Solazzo, Ioannis Kioutsioukis, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Ciao-Kai Liang, Uarporn Nopmongcol, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta Garcia Vivanco, Jason West, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 5967–5989, https://doi.org/10.5194/acp-18-5967-2018, https://doi.org/10.5194/acp-18-5967-2018, 2018
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The impacts of air pollution on human health and their costs in Europe and the United States for the year 2010 ared modeled by a multi-model ensemble. In Europe, the number of premature deaths is calculated to be 414 000, while in the US it is estimated to be 160 000. Health impacts estimated by individual models can vary up to a factor of 3. Results show that the domestic emissions have the largest impact on premature deaths, compared to foreign sources.
Laura Palacios-Peña, Rocío Baró, Alexander Baklanov, Alessandra Balzarini, Dominik Brunner, Renate Forkel, Marcus Hirtl, Luka Honzak, José María López-Romero, Juan Pedro Montávez, Juan Luis Pérez, Guido Pirovano, Roberto San José, Wolfram Schröder, Johannes Werhahn, Ralf Wolke, Rahela Žabkar, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 18, 5021–5043, https://doi.org/10.5194/acp-18-5021-2018, https://doi.org/10.5194/acp-18-5021-2018, 2018
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Atmospheric aerosols modify the radiative budget of the Earth, and it is therefore mandatory to have an accurate representation of their optical properties for understanding their climatic role. This work therefore evaluates the skill in the representation of optical properties by different remote-sensing sensors and regional online coupled chemistry–climate models over Europe.
Louis Marelle, Jean-Christophe Raut, Kathy S. Law, Larry K. Berg, Jerome D. Fast, Richard C. Easter, Manish Shrivastava, and Jennie L. Thomas
Geosci. Model Dev., 10, 3661–3677, https://doi.org/10.5194/gmd-10-3661-2017, https://doi.org/10.5194/gmd-10-3661-2017, 2017
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We develop the WRF-Chem 3.5.1 model to improve simulations of aerosols and ozone in the Arctic. Both species are important air pollutants and climate forcers, but models often struggle to reproduce observations in the Arctic. Our developments concern pollutant emissions, mixing, chemistry, and removal, including processes related to snow and sea ice. The effect of these changes are quantitatively validated against observations, showing significant improvements compared to the original model.
Jean-Christophe Raut, Louis Marelle, Jerome D. Fast, Jennie L. Thomas, Bernadett Weinzierl, Katharine S. Law, Larry K. Berg, Anke Roiger, Richard C. Easter, Katharina Heimerl, Tatsuo Onishi, Julien Delanoë, and Hans Schlager
Atmos. Chem. Phys., 17, 10969–10995, https://doi.org/10.5194/acp-17-10969-2017, https://doi.org/10.5194/acp-17-10969-2017, 2017
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We study the cross-polar transport of plumes from Siberian fires to the Arctic in summer, both in terms of transport pathways and efficiency of deposition processes. Those plumes containing soot may originate from anthropogenic and biomass burning sources in mid-latitude regions and may impact the Arctic climate by depositing on snow and ice surfaces. We evaluate the role of the respective source contributions, investigate the transport of plumes and treat pathway-dependent removal of particles.
Rocío Baró, Laura Palacios-Peña, Alexander Baklanov, Alessandra Balzarini, Dominik Brunner, Renate Forkel, Marcus Hirtl, Luka Honzak, Juan Luis Pérez, Guido Pirovano, Roberto San José, Wolfram Schröder, Johannes Werhahn, Ralf Wolke, Rahela Žabkar, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 17, 9677–9696, https://doi.org/10.5194/acp-17-9677-2017, https://doi.org/10.5194/acp-17-9677-2017, 2017
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The influence on modeled max., mean and min. temperature over Europe of including aerosol–radiation–cloud interactions has been assessed for two case studies in 2010. Data were taken from an ensemble of online regional chemistry–climate models from EuMetChem COST Action. The results indicate that including these interactions clearly improves the spatiotemporal variability in the temperature signal simulated by the models, with implications for reducing the uncertainty in climate projections.
Joseph Ching, Jerome Fast, Matthew West, and Nicole Riemer
Atmos. Chem. Phys., 17, 7445–7458, https://doi.org/10.5194/acp-17-7445-2017, https://doi.org/10.5194/acp-17-7445-2017, 2017
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The composition of individual aerosols affects their cloud condensation nuclei (CCN) properties, but is challenging to represent in models. This study quantifies the error in CCN calculations when per-particle information is neglected by using a metric for the composition diversity within a population. With more particle-level measurements from field campaigns, the approach is useful for quantifying uncertainties in composition-dependent quantities regarding aerosol–cloud–climate interactions.
Efisio Solazzo, Roberto Bianconi, Christian Hogrefe, Gabriele Curci, Paolo Tuccella, Ummugulsum Alyuz, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Johannes Bieser, Jørgen Brandt, Jesper H. Christensen, Augistin Colette, Xavier Francis, Andrea Fraser, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Ulas Im, Astrid Manders, Uarporn Nopmongcol, Nutthida Kitwiroon, Guido Pirovano, Luca Pozzoli, Marje Prank, Ranjeet S. Sokhi, Alper Unal, Greg Yarwood, and Stefano Galmarini
Atmos. Chem. Phys., 17, 3001–3054, https://doi.org/10.5194/acp-17-3001-2017, https://doi.org/10.5194/acp-17-3001-2017, 2017
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As part of the third phase of AQMEII, this study uses timescale analysis to apportion error to the responsible processes, detect causes of model error, and identify the processes and scales that require dedicated investigations. The analysis tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of model biases for ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature over Europe and North America.
Laura Palacios-Peña, Rocío Baró, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Dominik Brunner, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 17, 277–296, https://doi.org/10.5194/acp-17-277-2017, https://doi.org/10.5194/acp-17-277-2017, 2017
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The effects of atmospheric aerosols over the Earth’s climate mainly depend on their optical, microphysical and chemical properties, which modify the Earth's radiative budget, the main source of uncertainty in climate change. In this work we have studied the representation of aerosol optical properties using an online coupled model (WRF-Chem) when aerosol–radiation interactions (ARIs) and aerosol–clouds interactions (ACIs) are taken into account over the Iberian Peninsula.
Ioannis Kioutsioukis, Ulas Im, Efisio Solazzo, Roberto Bianconi, Alba Badia, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Dominik Brunner, Charles Chemel, Gabriele Curci, Hugo Denier van der Gon, Johannes Flemming, Renate Forkel, Lea Giordano, Pedro Jiménez-Guerrero, Marcus Hirtl, Oriol Jorba, Astrid Manders-Groot, Lucy Neal, Juan L. Pérez, Guidio Pirovano, Roberto San Jose, Nicholas Savage, Wolfram Schroder, Ranjeet S. Sokhi, Dimiter Syrakov, Paolo Tuccella, Johannes Werhahn, Ralf Wolke, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 16, 15629–15652, https://doi.org/10.5194/acp-16-15629-2016, https://doi.org/10.5194/acp-16-15629-2016, 2016
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Four ensemble methods are applied to two annual AQMEII datasets and their performance is compared for O3, NO2 and PM10. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill at each station over the single models and the ensemble mean. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way.
Dan Chen, Zhiquan Liu, Jerome Fast, and Junmei Ban
Atmos. Chem. Phys., 16, 10707–10724, https://doi.org/10.5194/acp-16-10707-2016, https://doi.org/10.5194/acp-16-10707-2016, 2016
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Extreme haze events occurred frequently over China recently, and adequately predicting peak PM2.5 concentrations is still challenging. In this study, the sulfate–nitrate–ammonium relevant heterogeneous reactions were parameterized for the first time in the WRF-Chem model. We evaluated the performance of WRF-Chem and used the model to investigate the sensitivity of heterogeneous reactions on simulated peak sulfate, nitrate, and ammonium concentrations in the vicinity of Beijing during October 2014.
Nuno Ratola and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 16, 4271–4282, https://doi.org/10.5194/acp-16-4271-2016, https://doi.org/10.5194/acp-16-4271-2016, 2016
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This original interpretation and application of environmental databases combines biomonitoring and atmospheric field data and state-of-the-art chemistry transport models to study one of the most carcinogenic atmospheric pollutants, benzo[a]pyrene (BaP). A comparison of ways to estimate air concentrations of BaP from its levels in vegetation is also a strong asset of this study. The whole methodology proposed here is versatile and can easily be applied to other regions and chemicals of interest.
J. A. García-Valero, J. P. Montávez, J. J. Gómez-Navarro, and P. Jiménez-Guerrero
Nat. Hazards Earth Syst. Sci., 15, 2143–2159, https://doi.org/10.5194/nhess-15-2143-2015, https://doi.org/10.5194/nhess-15-2143-2015, 2015
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This paper presents a study of extremely hot days (EHDs) in Spain and their connection with atmospheric dynamics. In addition, this work proposes a method that allows the detection of trends in the frequency of extreme events and their attribution to changes in atmospheric dynamics characterized through circulation types (CTs). The main CT-driven EHDs are identified. The increase in the EHD appearance is linked to the increase of the extreme CTs; however this only partially explains the trends.
S. Jerez, P. Jimenez-Guerrero, J. P. Montávez, and R. M. Trigo
Atmos. Chem. Phys., 13, 11195–11207, https://doi.org/10.5194/acp-13-11195-2013, https://doi.org/10.5194/acp-13-11195-2013, 2013
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Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
Short summary
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
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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
Short summary
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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
Short summary
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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
Short summary
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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
Short summary
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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.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
Short summary
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This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
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
Short summary
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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
Short summary
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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.
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Short summary
The main objective of this work is to study the impact of the representation of aerosol size distribution on aerosol optical properties over central Europe and the Mediterranean Basin during a summertime aerosol episode using the WRF-Chem online model. Results reveal that the reduction in the standard deviation of the accumulation mode leads to the largest impacts on aerosol optical depth (AOD) representation due to a transfer of particles from the accumulation mode to the coarse mode.
The main objective of this work is to study the impact of the representation of aerosol size...
