Articles | Volume 15, issue 9
https://doi.org/10.5194/gmd-15-3663-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-15-3663-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
09 May 2022
Model description paper |
| 09 May 2022
| 09 May 2022
Chemistry Across Multiple Phases (CAMP) version 1.0: an integrated multiphase chemistry model
Matthew L. Dawson
Barcelona Supercomputing Center, Barcelona, Spain
Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Christian Guzman
Barcelona Supercomputing Center, Barcelona, Spain
Jeffrey H. Curtis
Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA
Department of Mechanical Science and Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA
Mario Acosta
Barcelona Supercomputing Center, Barcelona, Spain
Shupeng Zhu
Advanced Power and Energy Program, University of California, Irvine, California, USA
Donald Dabdub
Department of Mechanical and Aerospace Engineering, University of California, Irvine, California, USA
Andrew Conley
Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Matthew West
Department of Mechanical Science and Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA
Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA
Barcelona Supercomputing Center, Barcelona, Spain
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Hervé Petetin, Marc Guevara, Steven Compernolle, Dene Bowdalo, Pierre-Antoine Bretonnière, Santiago Enciso, Oriol Jorba, Franco Lopez, Albert Soret, and Carlos Pérez García-Pando
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Hervé Petetin, Dene Bowdalo, Pierre-Antoine Bretonnière, Marc Guevara, Oriol Jorba, Jan Mateu Armengol, Margarida Samso Cabre, Kim Serradell, Albert Soret, and Carlos Pérez Garcia-Pando
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Yu Yao, Jeffrey H. Curtis, Joseph Ching, Zhonghua Zheng, and Nicole Riemer
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Enza Di Tomaso, Jerónimo Escribano, Sara Basart, Paul Ginoux, Francesca Macchia, Francesca Barnaba, Francesco Benincasa, Pierre-Antoine Bretonnière, Arnau Buñuel, Miguel Castrillo, Emilio Cuevas, Paola Formenti, María Gonçalves, Oriol Jorba, Martina Klose, Lucia Mona, Gilbert Montané Pinto, Michail Mytilinaios, Vincenzo Obiso, Miriam Olid, Nick Schutgens, Athanasios Votsis, Ernest Werner, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2785–2816, https://doi.org/10.5194/essd-14-2785-2022, https://doi.org/10.5194/essd-14-2785-2022, 2022
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MONARCH reanalysis of desert dust aerosols extends the existing observation-based information for mineral dust monitoring by providing 3-hourly upper-air, surface and total column key geophysical variables of the dust cycle over Northern Africa, the Middle East and Europe, at a 0.1° horizontal resolution in a rotated grid, from 2007 to 2016. This work provides evidence of the high accuracy of this data set and its suitability for air quality and health and climate service applications.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Jukka-Pekka Jalkanen, Elisa Majamäki, Lasse Johansson, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2521–2552, https://doi.org/10.5194/essd-14-2521-2022, https://doi.org/10.5194/essd-14-2521-2022, 2022
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To control the spread of the COVID-19 disease, European governments implemented mobility restriction measures that resulted in an unprecedented drop in anthropogenic emissions. This work presents a dataset of emission adjustment factors that allows quantifying changes in 2020 European primary emissions per country and pollutant sector at the daily scale. The resulting dataset can be used as input in modelling studies aiming at quantifying the impact of COVID-19 on air quality levels.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Xavier Yepes-Arbós, Gijs van den Oord, Mario C. Acosta, and Glenn D. Carver
Geosci. Model Dev., 15, 379–394, https://doi.org/10.5194/gmd-15-379-2022, https://doi.org/10.5194/gmd-15-379-2022, 2022
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Climate prediction models produce a large volume of simulated data that sometimes might not be efficiently managed. In this paper we present an approach to address this issue by reducing the computing time and storage space. As a case study, we analyse the output writing process of the ECMWF atmospheric model called IFS, and we integrate into it a data writing tool called XIOS. The results suggest that the integration between the two components achieves an adequate computational performance.
Jerónimo Escribano, Enza Di Tomaso, Oriol Jorba, Martina Klose, Maria Gonçalves Ageitos, Francesca Macchia, Vassilis Amiridis, Holger Baars, Eleni Marinou, Emmanouil Proestakis, Claudia Urbanneck, Dietrich Althausen, Johannes Bühl, Rodanthi-Elisavet Mamouri, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 22, 535–560, https://doi.org/10.5194/acp-22-535-2022, https://doi.org/10.5194/acp-22-535-2022, 2022
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We explore the benefits and consistency in adding lidar dust observations in a dust optical depth assimilation. We show that adding lidar data to a dust optical depth assimilation has valuable benefits and the dust analysis improves. We discuss the impact of the narrow satellite footprint of the lidar dust observations on the assimilation.
Michaël Sicard, Oriol Jorba, Jiang Ji Ho, Rebeca Izquierdo, Concepción De Linares, Marta Alarcón, Adolfo Comerón, and Jordina Belmonte
Atmos. Chem. Phys., 21, 17807–17832, https://doi.org/10.5194/acp-21-17807-2021, https://doi.org/10.5194/acp-21-17807-2021, 2021
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This paper investigates the mechanisms involved in the dispersion, structure, and mixing in the vertical column of atmospheric pollen, using observations of pollen concentration obtained at the ground and its stratification in the atmosphere measured by a lidar (laser radar), as well as an atmospheric transport model and a simplified pollen module developed especially for this study. The largest pollen concentration difference between the ground and the layers above is observed during nighttime.
Zhonghua Zheng, Matthew West, Lei Zhao, Po-Lun Ma, Xiaohong Liu, and Nicole Riemer
Atmos. Chem. Phys., 21, 17727–17741, https://doi.org/10.5194/acp-21-17727-2021, https://doi.org/10.5194/acp-21-17727-2021, 2021
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Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
Martina Klose, Oriol Jorba, María Gonçalves Ageitos, Jeronimo Escribano, Matthew L. Dawson, Vincenzo Obiso, Enza Di Tomaso, Sara Basart, Gilbert Montané Pinto, Francesca Macchia, Paul Ginoux, Juan Guerschman, Catherine Prigent, Yue Huang, Jasper F. Kok, Ron L. Miller, and Carlos Pérez García-Pando
Geosci. Model Dev., 14, 6403–6444, https://doi.org/10.5194/gmd-14-6403-2021, https://doi.org/10.5194/gmd-14-6403-2021, 2021
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Mineral soil dust is a major atmospheric airborne particle type. We present and evaluate MONARCH, a model used for regional and global dust-weather prediction. An important feature of the model is that it allows different approximations to represent dust, ranging from more simplified to more complex treatments. Using these different treatments, MONARCH can help us better understand impacts of dust in the Earth system, such as its interactions with radiation.
Jérôme Barré, Hervé Petetin, Augustin Colette, Marc Guevara, Vincent-Henri Peuch, Laurence Rouil, Richard Engelen, Antje Inness, Johannes Flemming, Carlos Pérez García-Pando, Dene Bowdalo, Frederik Meleux, Camilla Geels, Jesper H. Christensen, Michael Gauss, Anna Benedictow, Svetlana Tsyro, Elmar Friese, Joanna Struzewska, Jacek W. Kaminski, John Douros, Renske Timmermans, Lennart Robertson, Mario Adani, Oriol Jorba, Mathieu Joly, and Rostislav Kouznetsov
Atmos. Chem. Phys., 21, 7373–7394, https://doi.org/10.5194/acp-21-7373-2021, https://doi.org/10.5194/acp-21-7373-2021, 2021
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This study provides a comprehensive assessment of air quality changes across the main European urban areas induced by the COVID-19 lockdown using satellite observations, surface site measurements, and the forecasting system from the Copernicus Atmospheric Monitoring Service (CAMS). We demonstrate the importance of accounting for weather and seasonal variability when calculating such estimates.
Marc Guevara, Oriol Jorba, Carles Tena, Hugo Denier van der Gon, Jeroen Kuenen, Nellie Elguindi, Sabine Darras, Claire Granier, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, https://doi.org/10.5194/essd-13-367-2021, 2021
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The temporal variability of atmospheric emissions is linked to changes in activity patterns, emission processes and meteorology. Accounting for the change in temporal emission characteristics is a key aspect for modelling the trends of air pollutants. This work presents a dataset of global and European emission temporal profiles to be used for air quality modelling purposes. The profiles were constructed considering the influences of local sociodemographic factors and climatological conditions.
Marc Guevara, Oriol Jorba, Albert Soret, Hervé Petetin, Dene Bowdalo, Kim Serradell, Carles Tena, Hugo Denier van der Gon, Jeroen Kuenen, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 21, 773–797, https://doi.org/10.5194/acp-21-773-2021, https://doi.org/10.5194/acp-21-773-2021, 2021
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Most European countries have imposed lockdowns to combat the spread of the COVID-19 pandemic. Such a socioeconomic disruption has resulted in a sudden drop of atmospheric emissions and air pollution levels. This study quantifies the daily reductions in national emissions and associated levels of nitrogen dioxide (NO2) due to the COVID-19 lockdowns in Europe, by making use of multiple open-access measured activity data as well as artificial intelligence and modelling techniques.
Hervé Petetin, Dene Bowdalo, Albert Soret, Marc Guevara, Oriol Jorba, Kim Serradell, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 20, 11119–11141, https://doi.org/10.5194/acp-20-11119-2020, https://doi.org/10.5194/acp-20-11119-2020, 2020
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To control the spread of the COVID-19 coronavirus, the Spanish Government recently implemented a strict lockdown of the population, which strongly reduced the levels of nitrogen dioxide (NO2), one of the most critical air pollutants in Spain. This study quantifies the contribution of the lockdown on these reduced NO2 levels in Spain, taking the confounding effect of meteorology on artificial intelligence techniques into account.
Rein Haarsma, Mario Acosta, Rena Bakhshi, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Susanna Corti, Paolo Davini, Eleftheria Exarchou, Federico Fabiano, Uwe Fladrich, Ramon Fuentes Franco, Javier García-Serrano, Jost von Hardenberg, Torben Koenigk, Xavier Levine, Virna Loana Meccia, Twan van Noije, Gijs van den Oord, Froila M. Palmeiro, Mario Rodrigo, Yohan Ruprich-Robert, Philippe Le Sager, Etienne Tourigny, Shiyu Wang, Michiel van Weele, and Klaus Wyser
Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, https://doi.org/10.5194/gmd-13-3507-2020, 2020
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HighResMIP is an international coordinated CMIP6 effort to investigate the improvement in climate modeling caused by an increase in horizontal resolution. This paper describes EC-Earth3P-(HR), which has been developed for HighResMIP. First analyses reveal that increasing resolution does improve certain aspects of the simulated climate but that many other biases still continue, possibly related to phenomena that are still not yet resolved and need to be parameterized.
Havala O. T. Pye, Athanasios Nenes, Becky Alexander, Andrew P. Ault, Mary C. Barth, Simon L. Clegg, Jeffrey L. Collett Jr., Kathleen M. Fahey, Christopher J. Hennigan, Hartmut Herrmann, Maria Kanakidou, James T. Kelly, I-Ting Ku, V. Faye McNeill, Nicole Riemer, Thomas Schaefer, Guoliang Shi, Andreas Tilgner, John T. Walker, Tao Wang, Rodney Weber, Jia Xing, Rahul A. Zaveri, and Andreas Zuend
Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, https://doi.org/10.5194/acp-20-4809-2020, 2020
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Acid rain is recognized for its impacts on human health and ecosystems, and programs to mitigate these effects have had implications for atmospheric acidity. Historical measurements indicate that cloud and fog droplet acidity has changed in recent decades in response to controls on emissions from human activity, while the limited trend data for suspended particles indicate acidity may be relatively constant. This review synthesizes knowledge on the acidity of atmospheric particles and clouds.
François Massonnet, Martin Ménégoz, Mario Acosta, Xavier Yepes-Arbós, Eleftheria Exarchou, and Francisco J. Doblas-Reyes
Geosci. Model Dev., 13, 1165–1178, https://doi.org/10.5194/gmd-13-1165-2020, https://doi.org/10.5194/gmd-13-1165-2020, 2020
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Earth system models (ESMs) are one of the cornerstones of modern climate science. They are usually run on high-performance computers (HPCs). Whether the choice of HPC can affect the model results is a question of importance for optimizing the design of scientific studies. Here, we introduce a protocol for testing the replicability of the EC-Earth3 ESM across different HPCs. We find the simulation results to be replicable only if specific precautions are taken at the compilation stage.
Daniel M. Westervelt, Nora R. Mascioli, Arlene M. Fiore, Andrew J. Conley, Jean-François Lamarque, Drew T. Shindell, Greg Faluvegi, Michael Previdi, Gustavo Correa, and Larry W. Horowitz
Atmos. Chem. Phys., 20, 3009–3027, https://doi.org/10.5194/acp-20-3009-2020, https://doi.org/10.5194/acp-20-3009-2020, 2020
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We use three Earth system models to estimate the impact of regional air pollutant emissions reductions on global and regional surface temperature. We find that removing human-caused air pollutant emissions from certain world regions (such as the USA) results in warming of up to 0.15 °C. We use our model output to calculate simple climate metrics that will allow for regional-scale climate impact estimates without the use of computationally demanding computer models.
Marc Guevara, Carles Tena, Manuel Porquet, Oriol Jorba, and Carlos Pérez García-Pando
Geosci. Model Dev., 13, 873–903, https://doi.org/10.5194/gmd-13-873-2020, https://doi.org/10.5194/gmd-13-873-2020, 2020
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Emission inventories are a key input to numerical systems that simulate air quality. In this paper, we present an open-source tool intended for the computation of high-resolution anthropogenic emissions for air quality modelling. Emissions are estimated using detailed methods that combine local activity and emission factors along with meteorological data. Specific results are presented for Spain. Nevertheless, the model is designed so that it can be applicable to any European country or region.
Le Kuai, Kevin W. Bowman, Kazuyuki Miyazaki, Makoto Deushi, Laura Revell, Eugene Rozanov, Fabien Paulot, Sarah Strode, Andrew Conley, Jean-François Lamarque, Patrick Jöckel, David A. Plummer, Luke D. Oman, Helen Worden, Susan Kulawik, David Paynter, Andrea Stenke, and Markus Kunze
Atmos. Chem. Phys., 20, 281–301, https://doi.org/10.5194/acp-20-281-2020, https://doi.org/10.5194/acp-20-281-2020, 2020
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The tropospheric ozone increase from pre-industrial to the present day leads to a radiative forcing. The top-of-atmosphere outgoing fluxes at the ozone band are controlled by ozone, water vapor, and temperature. We demonstrate a method to attribute the models’ flux biases to these key players using satellite-constrained instantaneous radiative kernels. The largest spread between models is found in the tropics, mainly driven by ozone and then water vapor.
Oriol Tintó Prims, Mario C. Acosta, Andrew M. Moore, Miguel Castrillo, Kim Serradell, Ana Cortés, and Francisco J. Doblas-Reyes
Geosci. Model Dev., 12, 3135–3148, https://doi.org/10.5194/gmd-12-3135-2019, https://doi.org/10.5194/gmd-12-3135-2019, 2019
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Mixed-precision approaches can provide substantial speed-ups for both computing- and memory-bound codes, requiring little effort. A novel method to enable modern and legacy codes to benefit from a reduction of precision without sacrificing accuracy is presented. Using a precision emulator and a divide-and-conquer algorithm it identifies the parts that cannot handle reduced precision and the ones that can. The method has been proved using two ocean models, NEMO and ROMS, with promising results.
Jaime Benavides, Michelle Snyder, Marc Guevara, Albert Soret, Carlos Pérez García-Pando, Fulvio Amato, Xavier Querol, and Oriol Jorba
Geosci. Model Dev., 12, 2811–2835, https://doi.org/10.5194/gmd-12-2811-2019, https://doi.org/10.5194/gmd-12-2811-2019, 2019
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The NO2 annual air quality limit value is systematically exceeded in many European cities. In this context, understanding human exposure, improving policy and planning, and providing forecasts requires the development of accurate air quality models at street level. We describe CALIOPE-Urban, a system coupling an operational mesoscale air quality forecast system with an urban roadway dispersion model over Barcelona city (Spain). The methodology may be replicated for other cities in the future.
Marc Guevara, Carles Tena, Manuel Porquet, Oriol Jorba, and Carlos Pérez García-Pando
Geosci. Model Dev., 12, 1885–1907, https://doi.org/10.5194/gmd-12-1885-2019, https://doi.org/10.5194/gmd-12-1885-2019, 2019
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Atmospheric emission inventories, which describe the amounts of pollutants released into the air by different sources and for specific regions, are an essential input to numerical models that estimate air quality. This work presents the High-Elective Resolution Modelling Emission System version 3 (HERMESv3), an open-source modelling framework that allows adapting existing global and regional emission inventories to the input requirements of air quality models in a flexible and transparent way.
María Teresa Pay, Gotzon Gangoiti, Marc Guevara, Sergey Napelenok, Xavier Querol, Oriol Jorba, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 19, 5467–5494, https://doi.org/10.5194/acp-19-5467-2019, https://doi.org/10.5194/acp-19-5467-2019, 2019
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The poor diagnostic of the O3 issue over southwestern Europe prevents authorities from implementing effective mitigation plans. This work is a pioneer in identifying that imported O3 is the largest input to the ground-level O3 concentration in the Iberian Peninsula, which is largely explained by vertical mixing. This study also proves that anthropogenic emissions control the severe O3 peaks during stagnant conditions. Ad hoc local actions should complement national/European strategies.
Daniel M. Westervelt, Andrew J. Conley, Arlene M. Fiore, Jean-François Lamarque, Drew T. Shindell, Michael Previdi, Nora R. Mascioli, Greg Faluvegi, Gustavo Correa, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 12461–12475, https://doi.org/10.5194/acp-18-12461-2018, https://doi.org/10.5194/acp-18-12461-2018, 2018
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Small particles in Earth's atmosphere (also referred to as atmospheric aerosols) emitted by human activities impact Earth's climate in complex ways and play an important role in Earth's water cycle. We use a climate modeling approach and find that aerosols from the United States and Europe can have substantial effects on rainfall in far-away regions such as Africa's Sahel or the Mediterranean. Air pollution controls in these regions may help reduce the likelihood and severity of Sahel drought.
Angela Benedetti, Jeffrey S. Reid, Peter Knippertz, John H. Marsham, Francesca Di Giuseppe, Samuel Rémy, Sara Basart, Olivier Boucher, Ian M. Brooks, Laurent Menut, Lucia Mona, Paolo Laj, Gelsomina Pappalardo, Alfred Wiedensohler, Alexander Baklanov, Malcolm Brooks, Peter R. Colarco, Emilio Cuevas, Arlindo da Silva, Jeronimo Escribano, Johannes Flemming, Nicolas Huneeus, Oriol Jorba, Stelios Kazadzis, Stefan Kinne, Thomas Popp, Patricia K. Quinn, Thomas T. Sekiyama, Taichu Tanaka, and Enric Terradellas
Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, https://doi.org/10.5194/acp-18-10615-2018, 2018
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Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation authorities, solar energy plant managers, climate service providers, and health professionals. This paper describes the advances in the field and sets out requirements for observations for the sustainability of these activities.
Marta G. Vivanco, Mark R. Theobald, Héctor García-Gómez, Juan Luis Garrido, Marje Prank, Wenche Aas, Mario Adani, Ummugulsum Alyuz, Camilla Andersson, Roberto Bellasio, Bertrand Bessagnet, Roberto Bianconi, Johannes Bieser, Jørgen Brandt, Gino Briganti, Andrea Cappelletti, Gabriele Curci, Jesper H. Christensen, Augustin Colette, Florian Couvidat, Cornelis Cuvelier, Massimo D'Isidoro, Johannes Flemming, Andrea Fraser, Camilla Geels, Kaj M. Hansen, Christian Hogrefe, Ulas Im, Oriol Jorba, Nutthida Kitwiroon, Astrid Manders, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Luca Pozzoli, Efisio Solazzo, Svetlana Tsyro, Alper Unal, Peter Wind, and Stefano Galmarini
Atmos. Chem. Phys., 18, 10199–10218, https://doi.org/10.5194/acp-18-10199-2018, https://doi.org/10.5194/acp-18-10199-2018, 2018
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European wet and dry atmospheric deposition of N and S estimated by 14 air quality models was found to vary substantially. An ensemble of models meeting acceptability criteria was used to estimate the exceedances of the critical loads for N in habitats within the Natura 2000 network, as well as their lower and upper limits. Scenarios with 20 % emission reductions in different regions of the world showed that European emissions are responsible for most of the N and S deposition in Europe.
Antonis Gkikas, Vincenzo Obiso, Carlos Pérez García-Pando, Oriol Jorba, Nikos Hatzianastassiou, Lluis Vendrell, Sara Basart, Stavros Solomos, Santiago Gassó, and José Maria Baldasano
Atmos. Chem. Phys., 18, 8757–8787, https://doi.org/10.5194/acp-18-8757-2018, https://doi.org/10.5194/acp-18-8757-2018, 2018
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The present study investigates the direct radiative effects (DREs), induced during 20 intense Mediterranean desert dust outbreaks, based on regional short-term numerical simulations of the NMMB-MONARCH model: more specifically, (i) the DREs and their associated impacts on temperature and surface sensible and latent heat fluxes, (ii) the feedbacks on dust AOD and dust emissions, and (iii) the possible improvements in short-term forecasts (up to 84 h) of temperature and radiation.
Shupeng Zhu, Jeremy R. Horne, Julia Montoya-Aguilera, Mallory L. Hinks, Sergey A. Nizkorodov, and Donald Dabdub
Atmos. Chem. Phys., 18, 3641–3657, https://doi.org/10.5194/acp-18-3641-2018, https://doi.org/10.5194/acp-18-3641-2018, 2018
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For the first time, the interaction between ammonia and secondary organic aerosol (SOA) is integrated in an air quality model and investigated on a national scale. Our original analysis from simulation results indicates that a significant reduction in gas-phase ammonia is possible due to its uptake onto SOA. Significant impact is also observed in the concentration of particulate matter, with a distinct spatial pattern over different seasons.
Angeline G. Pendergrass, Andrew Conley, and Francis M. Vitt
Earth Syst. Sci. Data, 10, 317–324, https://doi.org/10.5194/essd-10-317-2018, https://doi.org/10.5194/essd-10-317-2018, 2018
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We document and validate radiative kernels for the surface and top-of-atmosphere calculated with NCAR's CESM1 climate model. A radiative kernel is the change in radiation in response to a small change in a property of the atmosphere or surface, essentially a partial derivative. They are used to quantify temperature, water vapor, surface albedo, and cloud feedbacks. We made these kernels because few are available for the surface. We also validate the kernels against the expected model responses.
Mallory L. Hinks, Julia Montoya-Aguilera, Lucas Ellison, Peng Lin, Alexander Laskin, Julia Laskin, Manabu Shiraiwa, Donald Dabdub, and Sergey A. Nizkorodov
Atmos. Chem. Phys., 18, 1643–1652, https://doi.org/10.5194/acp-18-1643-2018, https://doi.org/10.5194/acp-18-1643-2018, 2018
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We have observed a strong effect of relative humidity on the composition of particulate matter produced from the oxidation of toluene in clean air. At higher relative humidity, there was a significant reduction in the fraction of high-molecular-weight compounds present in the particles. The amount of particulate matter also decreased at higher relative humidity. The main implication of this study is that water vapor participates in the photooxidation of toluene in a complicated way.
Albert Ansmann, Franziska Rittmeister, Ronny Engelmann, Sara Basart, Oriol Jorba, Christos Spyrou, Samuel Remy, Annett Skupin, Holger Baars, Patric Seifert, Fabian Senf, and Thomas Kanitz
Atmos. Chem. Phys., 17, 14987–15006, https://doi.org/10.5194/acp-17-14987-2017, https://doi.org/10.5194/acp-17-14987-2017, 2017
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 10, 4057–4079, https://doi.org/10.5194/gmd-10-4057-2017, https://doi.org/10.5194/gmd-10-4057-2017, 2017
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Traditional aerosol representations rely on simplifying assumptions about the aerosol composition in order to reduce computational cost. This introduces errors in estimates of aerosol impacts on climate. In contrast, the WRF-PartMC-MOSAIC-SCM model, presented here, uses a particle-resolved aerosol representation. It is made feasible by the development of efficient numerical methods, and allows for the capture of complex aerosol mixing states with altitude.
Julia Montoya-Aguilera, Jeremy R. Horne, Mallory L. Hinks, Lauren T. Fleming, Véronique Perraud, Peng Lin, Alexander Laskin, Julia Laskin, Donald Dabdub, and Sergey A. Nizkorodov
Atmos. Chem. Phys., 17, 11605–11621, https://doi.org/10.5194/acp-17-11605-2017, https://doi.org/10.5194/acp-17-11605-2017, 2017
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Various plant species emit a chemical compound called indole under stressed conditions or during flowering events. Our experiments show that indole can be oxidized in the atmosphere to produce a brownish haze containing well-known indole-derived dyes, such as indigo dye. An airshed model that includes indole chemistry shows that indole aerosol makes a significant contribution to the total aerosol burden and to visibility.
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.
Alejandro Marti, Arnau Folch, Oriol Jorba, and Zavisa Janjic
Atmos. Chem. Phys., 17, 4005–4030, https://doi.org/10.5194/acp-17-4005-2017, https://doi.org/10.5194/acp-17-4005-2017, 2017
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We describe and evaluate NMMB-MONARCH-ASH, a novel online multi-scale meteorological and transport model developed at the BSC-CNS capable of forecasting the dispersal and deposition of volcanic ash. The forecast skills of the model have been validated and they improve on those from traditional operational offline (decoupled) models. The results support the use of online coupled models to aid civil aviation and emergency management during a crisis such as the 2010 eruption of Eyjafjallajökull.
Enza Di Tomaso, Nick A. J. Schutgens, Oriol Jorba, and Carlos Pérez García-Pando
Geosci. Model Dev., 10, 1107–1129, https://doi.org/10.5194/gmd-10-1107-2017, https://doi.org/10.5194/gmd-10-1107-2017, 2017
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A data assimilation capability has been built for a chemical weather prediction system, with a focus on mineral dust. Before this work, dust was produced uniquely from model estimated emissions. As emissions are recognized as a major factor limiting the accuracy of dust modelling, satellite observations have been used to improve the description of the atmospheric dust load, with a significant impact on dust forecast from assimilating observations particularly relevant for dust applications.
Alba Badia, Oriol Jorba, Apostolos Voulgarakis, Donald Dabdub, Carlos Pérez García-Pando, Andreas Hilboll, María Gonçalves, and Zavisa Janjic
Geosci. Model Dev., 10, 609–638, https://doi.org/10.5194/gmd-10-609-2017, https://doi.org/10.5194/gmd-10-609-2017, 2017
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This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH), an online chemical weather prediction system conceived for both the regional and global scales. We provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations, ozonesondes, aircraft data and satellite observations.
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.
Ryan Reynolds Neely III, Andrew J. Conley, Francis Vitt, and Jean-François Lamarque
Geosci. Model Dev., 9, 2459–2470, https://doi.org/10.5194/gmd-9-2459-2016, https://doi.org/10.5194/gmd-9-2459-2016, 2016
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We describe an updated scheme for prescribing stratospheric aerosol in the Community Earth System Model (CESM1). The inadequate response of the CESM1 to large volcanic disturbances to the stratospheric aerosol layer (such as the 1991 Pinatubo eruption) in comparison to observations motivates the need for a new parameterization. Simulations utilizing the new scheme successfully reproduce the observed global mean and local stratospheric temperature response to the Pinatubo eruption.
Antonis Gkikas, Sara Basart, Nikos Hatzianastassiou, Eleni Marinou, Vassilis Amiridis, Stelios Kazadzis, Jorge Pey, Xavier Querol, Oriol Jorba, Santiago Gassó, and José Maria Baldasano
Atmos. Chem. Phys., 16, 8609–8642, https://doi.org/10.5194/acp-16-8609-2016, https://doi.org/10.5194/acp-16-8609-2016, 2016
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This study presents the 3-D structures of intense Mediterranean desert dust outbreaks, over the period Mar 2000–Feb 2013. The desert dust (DD) episodes are identified through an objective and dynamic algorithm, which utilizes satellite retrievals (MODIS, TOMS and OMI) as inputs. The performance of the satellite algorithm is evaluated vs. AERONET and PM10 data. The geometrical characteristics of the identified DD episodes are analyzed using the collocated CALIOP profiles as a complementary tool.
Matthew L. Dawson, Jialu Xu, Robert J. Griffin, and Donald Dabdub
Geosci. Model Dev., 9, 2143–2151, https://doi.org/10.5194/gmd-9-2143-2016, https://doi.org/10.5194/gmd-9-2143-2016, 2016
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The atmospheric oxidation of aromatic compounds is an important source of aerosol-forming species, and thus contributes to pollution in urban areas. However, details of the mechanisms by which oxidation occurs are only recently being elucidated. Here we report the incorporation of a newly developed mechanism for aromatic oxidation into the UCI-CIT regional air quality model. Results suggest an unexpected role for chemical pathways typically associated with cleaner environments.
Simone Tilmes, Jean-Francois Lamarque, Louisa K. Emmons, Doug E. Kinnison, Dan Marsh, Rolando R. Garcia, Anne K. Smith, Ryan R. Neely, Andrew Conley, Francis Vitt, Maria Val Martin, Hiroshi Tanimoto, Isobel Simpson, Don R. Blake, and Nicola Blake
Geosci. Model Dev., 9, 1853–1890, https://doi.org/10.5194/gmd-9-1853-2016, https://doi.org/10.5194/gmd-9-1853-2016, 2016
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The state of the art Community Earth System Model, CESM1 CAM4-chem has been used to perform reference and sensitivity simulations as part of the Chemistry Climate Model Initiative (CCMI). Specifics of the model and details regarding the setup of the simulations are described. In additions, the main behavior of the model, including selected chemical species have been evaluated with climatological datasets. This paper is therefore a references for studies that use the provided model results.
Megan D. Willis, Robert M. Healy, Nicole Riemer, Matthew West, Jon M. Wang, Cheol-Heon Jeong, John C. Wenger, Greg J. Evans, Jonathan P. D. Abbatt, and Alex K. Y. Lee
Atmos. Chem. Phys., 16, 4693–4706, https://doi.org/10.5194/acp-16-4693-2016, https://doi.org/10.5194/acp-16-4693-2016, 2016
P. H. Lauritzen, A. J. Conley, J.-F. Lamarque, F. Vitt, and M. A. Taylor
Geosci. Model Dev., 8, 1299–1313, https://doi.org/10.5194/gmd-8-1299-2015, https://doi.org/10.5194/gmd-8-1299-2015, 2015
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This test extends the evaluation of transport schemes from prescribed advection of inert scalars to reactive species. It consists of transporting two reacting chlorine-like species in an idealized flow field. The sources/sinks are given by a simple but non-linear toy chemistry that mimics photolysis-driven processes near the solar terminator. As a result, strong gradients in the spatial distribution of the species develop near the edge of the terminator.
L. Fierce, N. Riemer, and T. C. Bond
Atmos. Chem. Phys., 15, 3173–3191, https://doi.org/10.5194/acp-15-3173-2015, https://doi.org/10.5194/acp-15-3173-2015, 2015
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The timescale for particles containing black carbon to age from hydrophobic to hygroscopic strongly influences black carbon's atmospheric lifetime and climate impact. This paper identifies the minimal set of independent variables needed to explain variance in this aging timescale. This work distills the complex interactions captured by a particle-resolved aerosol model to a few input variables and is a first step toward developing physically based parameterizations of aerosol aging.
W. R. Sessions, J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama, T. Y. Tanaka, J. M. Baldasano, S. Basart, M. E. Brooks, T. F. Eck, M. Iredell, J. A. Hansen, O. C. Jorba, H.-M. H. Juang, P. Lynch, J.-J. Morcrette, S. Moorthi, J. Mulcahy, Y. Pradhan, M. Razinger, C. B. Sampson, J. Wang, and D. L. Westphal
Atmos. Chem. Phys., 15, 335–362, https://doi.org/10.5194/acp-15-335-2015, https://doi.org/10.5194/acp-15-335-2015, 2015
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R. M. Healy, N. Riemer, J. C. Wenger, M. Murphy, M. West, L. Poulain, A. Wiedensohler, I. P. O'Connor, E. McGillicuddy, J. R. Sodeau, and G. J. Evans
Atmos. Chem. Phys., 14, 6289–6299, https://doi.org/10.5194/acp-14-6289-2014, https://doi.org/10.5194/acp-14-6289-2014, 2014
J. C. Kaiser, J. Hendricks, M. Righi, N. Riemer, R. A. Zaveri, S. Metzger, and V. Aquila
Geosci. Model Dev., 7, 1137–1157, https://doi.org/10.5194/gmd-7-1137-2014, https://doi.org/10.5194/gmd-7-1137-2014, 2014
J. Tian, N. Riemer, M. West, L. Pfaffenberger, H. Schlager, and A. Petzold
Atmos. Chem. Phys., 14, 5327–5347, https://doi.org/10.5194/acp-14-5327-2014, https://doi.org/10.5194/acp-14-5327-2014, 2014
P. H. Lauritzen, P. A. Ullrich, C. Jablonowski, P. A. Bosler, D. Calhoun, A. J. Conley, T. Enomoto, L. Dong, S. Dubey, O. Guba, A. B. Hansen, E. Kaas, J. Kent, J.-F. Lamarque, M. J. Prather, D. Reinert, V. V. Shashkin, W. C. Skamarock, B. Sørensen, M. A. Taylor, and M. A. Tolstykh
Geosci. Model Dev., 7, 105–145, https://doi.org/10.5194/gmd-7-105-2014, https://doi.org/10.5194/gmd-7-105-2014, 2014
A. Baklanov, K. Schlünzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. S. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang
Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, https://doi.org/10.5194/acp-14-317-2014, 2014
M. Spada, O. Jorba, C. Pérez García-Pando, Z. Janjic, and J. M. Baldasano
Atmos. Chem. Phys., 13, 11735–11755, https://doi.org/10.5194/acp-13-11735-2013, https://doi.org/10.5194/acp-13-11735-2013, 2013
N. Riemer and M. West
Atmos. Chem. Phys., 13, 11423–11439, https://doi.org/10.5194/acp-13-11423-2013, https://doi.org/10.5194/acp-13-11423-2013, 2013
A. J. Conley, J.-F. Lamarque, F. Vitt, W. D. Collins, and J. Kiehl
Geosci. Model Dev., 6, 469–476, https://doi.org/10.5194/gmd-6-469-2013, https://doi.org/10.5194/gmd-6-469-2013, 2013
D. T. Shindell, J.-F. Lamarque, M. Schulz, M. Flanner, C. Jiao, M. Chin, P. J. Young, Y. H. Lee, L. Rotstayn, N. Mahowald, G. Milly, G. Faluvegi, Y. Balkanski, W. J. Collins, A. J. Conley, S. Dalsoren, R. Easter, S. Ghan, L. Horowitz, X. Liu, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. Skeie, K. Sudo, S. Szopa, T. Takemura, A. Voulgarakis, J.-H. Yoon, and F. Lo
Atmos. Chem. Phys., 13, 2939–2974, https://doi.org/10.5194/acp-13-2939-2013, https://doi.org/10.5194/acp-13-2939-2013, 2013
D. S. Stevenson, P. J. Young, V. Naik, J.-F. Lamarque, D. T. Shindell, A. Voulgarakis, R. B. Skeie, S. B. Dalsoren, G. Myhre, T. K. Berntsen, G. A. Folberth, S. T. Rumbold, W. J. Collins, I. A. MacKenzie, R. M. Doherty, G. Zeng, T. P. C. van Noije, A. Strunk, D. Bergmann, P. Cameron-Smith, D. A. Plummer, S. A. Strode, L. Horowitz, Y. H. Lee, S. Szopa, K. Sudo, T. Nagashima, B. Josse, I. Cionni, M. Righi, V. Eyring, A. Conley, K. W. Bowman, O. Wild, and A. Archibald
Atmos. Chem. Phys., 13, 3063–3085, https://doi.org/10.5194/acp-13-3063-2013, https://doi.org/10.5194/acp-13-3063-2013, 2013
Related subject area
Atmospheric sciences
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Estimation of aerosol and cloud radiative heating rate in tropical stratosphere using radiative kernel method
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
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
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.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at 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 of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
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.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2815, https://doi.org/10.5194/egusphere-2024-2815, 2024
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate that 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 and consists well with radiative model calculations and can be applied to atmospheric models with speed requirements.
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.
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Short summary
Progress in identifying complex, mixed-phase physicochemical processes has resulted in an advanced understanding of the evolution of atmospheric systems but has also introduced a level of complexity that few atmospheric models were designed to handle. We present a flexible treatment for multiphase chemical processes for models of diverse scale, from box up to global models. This enables users to build a customized multiphase mechanism that is accessible to a much wider community.
Progress in identifying complex, mixed-phase physicochemical processes has resulted in an...
