Articles | Volume 12, issue 5
https://doi.org/10.5194/gmd-12-1885-2019
© Author(s) 2019. 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-12-1885-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 1: global and regional module
Earth Sciences Department, Barcelona Supercomputing Center, Barcelona,
08034, Spain
Carles Tena
Earth Sciences Department, Barcelona Supercomputing Center, Barcelona,
08034, Spain
Manuel Porquet
Earth Sciences Department, Barcelona Supercomputing Center, Barcelona,
08034, Spain
Oriol Jorba
Earth Sciences Department, Barcelona Supercomputing Center, Barcelona,
08034, Spain
Carlos Pérez García-Pando
Earth Sciences Department, Barcelona Supercomputing Center, Barcelona,
08034, Spain
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Atmos. Chem. Phys., 24, 7137–7177, https://doi.org/10.5194/acp-24-7137-2024, https://doi.org/10.5194/acp-24-7137-2024, 2024
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An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
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Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
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Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Jieying Ding, Ronald van der A, Henk Eskes, Enrico Dammers, Mark Shephard, Roy Wichink Kruit, Marc Guevara, and Leonor Tarrason
EGUsphere, https://doi.org/10.5194/egusphere-2024-1073, https://doi.org/10.5194/egusphere-2024-1073, 2024
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Here we applied the existing DECSO inversion algorithm to NH3 observations from the CrIS satellite instrument to estimate NH3 emissions. Because NH3 in the atmosphere is influenced by NOx, we implemented DECSO to estimate NOx and NH3 emissions simultaneously. The emissions are derived over Europe for 2020 on a spatial resolution of 0.2° degree using daily observations from both CrIS and TROPOMI. The results are compared to bottom-up emission inventories.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-397, https://doi.org/10.5194/essd-2023-397, 2024
Revised manuscript accepted for ESSD
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GHOST: Globally Harmonised Observations in Space and Time, represents one of the biggest collection of harmonised measurements of atmospheric composition at the surface. In total, 7,275,148,646 measurements from 1970–2023, of 227 different components, from 38 reporting networks, are compiled, parsed, and standardised. Components processed include gaseous species, total and speciated particulate matter, and aerosol optical properties.
Ruben Urraca, Greet Janssens-Maenhout, Nicolás Álamos, Lucas Berna-Peña, Monica Crippa, Sabine Darras, Stijn Dellaert, Hugo Denier van der Gon, Mark Dowell, Nadine Gobron, Claire Granier, Giacomo Grassi, Marc Guevara, Diego Guizzardi, Kevin Gurney, Nicolás Huneeus, Sekou Keita, Jeroen Kuenen, Ana Lopez-Noreña, Enrique Puliafito, Geoffrey Roest, Simone Rossi, Antonin Soulie, and Antoon Visschedijk
Earth Syst. Sci. Data, 16, 501–523, https://doi.org/10.5194/essd-16-501-2024, https://doi.org/10.5194/essd-16-501-2024, 2024
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CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories providing gridded (0.1×0.1) monthly emissions of anthropogenic CO2. Regional inventories include country-specific information and finer spatial resolution than global inventories. CoCO2-MOSAIC provides harmonized access to these datasets and can be considered as a regionally accepted reference to assess the quality of global inventories, as done in the current paper.
Marc Guevara, Santiago Enciso, Carles Tena, Oriol Jorba, Stijn Dellaert, Hugo Denier van der Gon, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 16, 337–373, https://doi.org/10.5194/essd-16-337-2024, https://doi.org/10.5194/essd-16-337-2024, 2024
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A global dataset of emissions from thermal power plants was created for the year 2018. The resulting catalogue reports annual emissions of CO2 and co-emitted species (NOx, CO, SO2 and CH4) for more than 16000 individual facilities at their exact geographical locations. Information on the temporal and vertical distributions of the emissions is also provided at the facility level. The dataset is intended to support current and future satellite emission monitoring and inverse modelling efforts.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Claire Granier, Thierno Doumbia, Philippe Ciais, Zhu Liu, Robin D. Lamboll, Sabine Schindlbacher, Bradley Matthews, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8081–8101, https://doi.org/10.5194/acp-23-8081-2023, https://doi.org/10.5194/acp-23-8081-2023, 2023
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Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodriguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
Geosci. Model Dev., 16, 2193–2213, https://doi.org/10.5194/gmd-16-2193-2023, https://doi.org/10.5194/gmd-16-2193-2023, 2023
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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
Atmos. Chem. Phys., 23, 3905–3935, https://doi.org/10.5194/acp-23-3905-2023, https://doi.org/10.5194/acp-23-3905-2023, 2023
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This study analyses the potential of the TROPOMI space sensor for monitoring the variability of NO2 pollution over the Iberian Peninsula. A reduction of NO2 levels is observed during the weekend and in summer, especially over most urbanized areas, in agreement with surface observations. An enhancement of NO2 is found during summer with TROPOMI over croplands, potentially related to natural soil NO emissions, which illustrates the outstanding value of TROPOMI for complementing surface networks.
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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.
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.
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.
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.
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.
Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Melani Hernández-Chiriboga, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert Green, Paul Ginoux, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 9155–9176, https://doi.org/10.5194/acp-24-9155-2024, https://doi.org/10.5194/acp-24-9155-2024, 2024
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In this research, we studied the dust-emitting properties of crusts and aeolian ripples from the Mojave Desert. These properties are key to understanding the effect of dust upon climate. We found two different playa lakes according to the groundwater regime, which implies differences in crusts' cohesion state and mineralogy, which can affect the dust emission potential and properties. We also compare them with Moroccan Sahara crusts and Icelandic top sediments.
Hector Navarro-Barboza, Jordi Rovira, Vincenzo Obiso, Andrea Pozzer, Marta Via, Andres Alastuey, Xavier Querol, Noemi Perez, Marjan Savadkoohi, Gang Chen, Jesus Yus-Díez, Matic Ivancic, Martin Rigler, Konstantinos Eleftheriadis, Stergios Vratolis, Olga Zografou, Maria Gini, Benjamin Chazeau, Nicolas Marchand, Andre Prevot, Kaspar Dallenbach, Mikael Ehn, Krista Luoma, Tuukka Petäjä, Anna Tobler, Jaroslaw Necki, Minna Aurela, Hilkka Timonen, Jarkko Niemi, Olivier Favez, Jean-Eudes Petit, Jean-Philippe Putaud, Christoph Hueglin, Nicolas Pascal, Aurelien Chauvigné, Sebastien Conil, Marco Pandolfi, and Oriol Jorba
EGUsphere, https://doi.org/10.5194/egusphere-2024-2086, https://doi.org/10.5194/egusphere-2024-2086, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Brown carbon (BrC) absorbs UV and visible light, affecting climate. Our study investigates BrC's imaginary refractive index (k ) using data from 12 European sites. Residential emissions are a major OA source in winter, while secondary organic aerosols (SOA) dominate in summer. We derived source-specific k values, enhancing model accuracy. This research improves understanding of BrC's climate role, emphasizing the need for source-specific constraints in atmospheric models.
Qianqian Song, Paul Ginoux, María Gonçalves Ageitos, Ron L. Miller, Vincenzo Obiso, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7421–7446, https://doi.org/10.5194/acp-24-7421-2024, https://doi.org/10.5194/acp-24-7421-2024, 2024
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We implement and simulate the distribution of eight dust minerals in the GFDL AM4.0 model. We found that resolving the eight minerals reduces dust absorption compared to the homogeneous dust used in the standard GFDL AM4.0 model that assumes a globally uniform hematite content of 2.7 % by volume. Resolving dust mineralogy results in significant impacts on radiation, land surface temperature, surface winds, and precipitation over North Africa in summer.
Kevin Oliveira, Marc Guevara, Oriol Jorba, Hervé Petetin, Dene Bowdalo, Carles Tena, Gilbert Montané Pinto, Franco López, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7137–7177, https://doi.org/10.5194/acp-24-7137-2024, https://doi.org/10.5194/acp-24-7137-2024, 2024
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In this work, we assess and evaluate benzene, toluene, and xylene primary emissions and air quality levels in Spain by combining observations, emission inventories, and air quality modelling techniques. The comparison between modelled and observed levels allows identifying uncertainty sources within the emission input. This contributes to improving air quality models' performance when simulating these compounds, leading to better support for the design of effective pollution control strategies.
Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert O. Green, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 6883–6910, https://doi.org/10.5194/acp-24-6883-2024, https://doi.org/10.5194/acp-24-6883-2024, 2024
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The knowledge of properties from dust emitted in high latitudes such as in Iceland is scarce. This study focuses on the particle size, mineralogy, cohesion, and iron mode of occurrence and reflectance spectra of dust-emitting sediments. Icelandic top sediments have lower cohesion state, coarser particle size, distinctive mineralogy, and 3-fold bulk Fe content, with a large presence of magnetite compared to Saharan crusts.
Vincenzo Obiso, María Gonçalves Ageitos, Carlos Pérez García-Pando, Jan P. Perlwitz, Gregory L. Schuster, Susanne E. Bauer, Claudia Di Biagio, Paola Formenti, Kostas Tsigaridis, and Ron L. Miller
Atmos. Chem. Phys., 24, 5337–5367, https://doi.org/10.5194/acp-24-5337-2024, https://doi.org/10.5194/acp-24-5337-2024, 2024
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We calculate the dust direct radiative effect (DRE) in an Earth system model accounting for regionally varying soil mineralogy through a new observationally constrained method. Linking dust absorption at solar wavelengths to the varying amount of specific minerals (i.e., iron oxides) improves the modeled range of dust single scattering albedo compared to observations and increases the global cooling by dust. Our results may contribute to improved estimates of the dust DRE and its climate impact.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
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An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
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Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Marios Chatziparaschos, Stelios Myriokefalitakis, Nikos Kalivitis, Nikos Daskalakis, Athanasios Nenes, María Gonçalves Ageitos, Montserrat Costa-Surós, Carlos Pérez García-Pando, Mihalis Vrekoussis, and Maria Kanakidou
EGUsphere, https://doi.org/10.5194/egusphere-2024-952, https://doi.org/10.5194/egusphere-2024-952, 2024
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We show distinct seasonal and geographical patterns in the contributions of mineral dust, marine and terrestrial biological particles to ice-nucleating particles (INP) concentrations that lead to atmospheric ice formation, a major source of uncertainty in climate predictions. Bioaerosols are the major source of INP at high temperatures, while mineral dust influences the global INP population at lower temperatures. These particles can satisfactorily reproduce INP in a climate model.
Jieying Ding, Ronald van der A, Henk Eskes, Enrico Dammers, Mark Shephard, Roy Wichink Kruit, Marc Guevara, and Leonor Tarrason
EGUsphere, https://doi.org/10.5194/egusphere-2024-1073, https://doi.org/10.5194/egusphere-2024-1073, 2024
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Here we applied the existing DECSO inversion algorithm to NH3 observations from the CrIS satellite instrument to estimate NH3 emissions. Because NH3 in the atmosphere is influenced by NOx, we implemented DECSO to estimate NOx and NH3 emissions simultaneously. The emissions are derived over Europe for 2020 on a spatial resolution of 0.2° degree using daily observations from both CrIS and TROPOMI. The results are compared to bottom-up emission inventories.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-248, https://doi.org/10.5194/egusphere-2024-248, 2024
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Aerosol-cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem model, this study aims to understand the extent to which Twomey effect manifests itself at larger scales. We report a reduction in the warm bias over the Southern Ocean due to model improvements. While we do see footprints of Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Dene Bowdalo, Sara Basart, Marc Guevara, Oriol Jorba, Carlos Pérez García-Pando, Monica Jaimes Palomera, Olivia Rivera Hernandez, Melissa Puchalski, David Gay, Jörg Klausen, Sergio Moreno, Stoyka Netcheva, and Oksana Tarasova
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-397, https://doi.org/10.5194/essd-2023-397, 2024
Revised manuscript accepted for ESSD
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GHOST: Globally Harmonised Observations in Space and Time, represents one of the biggest collection of harmonised measurements of atmospheric composition at the surface. In total, 7,275,148,646 measurements from 1970–2023, of 227 different components, from 38 reporting networks, are compiled, parsed, and standardised. Components processed include gaseous species, total and speciated particulate matter, and aerosol optical properties.
Danny M. Leung, Jasper F. Kok, Longlei Li, Natalie M. Mahowald, David M. Lawrence, Simone Tilmes, Erik Kluzek, Martina Klose, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 2287–2318, https://doi.org/10.5194/acp-24-2287-2024, https://doi.org/10.5194/acp-24-2287-2024, 2024
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This study uses a premier Earth system model to evaluate a new desert dust emission scheme proposed in our companion paper. We show that our scheme accounts for more dust emission physics, hence matching better against observations than other existing dust emission schemes do. Our scheme's dust emissions also couple tightly with meteorology, hence likely improving the modeled dust sensitivity to climate change. We believe this work is vital for improving dust representation in climate models.
Ruben Urraca, Greet Janssens-Maenhout, Nicolás Álamos, Lucas Berna-Peña, Monica Crippa, Sabine Darras, Stijn Dellaert, Hugo Denier van der Gon, Mark Dowell, Nadine Gobron, Claire Granier, Giacomo Grassi, Marc Guevara, Diego Guizzardi, Kevin Gurney, Nicolás Huneeus, Sekou Keita, Jeroen Kuenen, Ana Lopez-Noreña, Enrique Puliafito, Geoffrey Roest, Simone Rossi, Antonin Soulie, and Antoon Visschedijk
Earth Syst. Sci. Data, 16, 501–523, https://doi.org/10.5194/essd-16-501-2024, https://doi.org/10.5194/essd-16-501-2024, 2024
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CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories providing gridded (0.1×0.1) monthly emissions of anthropogenic CO2. Regional inventories include country-specific information and finer spatial resolution than global inventories. CoCO2-MOSAIC provides harmonized access to these datasets and can be considered as a regionally accepted reference to assess the quality of global inventories, as done in the current paper.
Marc Guevara, Santiago Enciso, Carles Tena, Oriol Jorba, Stijn Dellaert, Hugo Denier van der Gon, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 16, 337–373, https://doi.org/10.5194/essd-16-337-2024, https://doi.org/10.5194/essd-16-337-2024, 2024
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A global dataset of emissions from thermal power plants was created for the year 2018. The resulting catalogue reports annual emissions of CO2 and co-emitted species (NOx, CO, SO2 and CH4) for more than 16000 individual facilities at their exact geographical locations. Information on the temporal and vertical distributions of the emissions is also provided at the facility level. The dataset is intended to support current and future satellite emission monitoring and inverse modelling efforts.
Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Cristina Reche, Patricia Córdoba, Natalia Moreno, Andres Alastuey, Konrad Kandler, Martina Klose, Clarissa Baldo, Roger N. Clark, Zongbo Shi, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 15815–15834, https://doi.org/10.5194/acp-23-15815-2023, https://doi.org/10.5194/acp-23-15815-2023, 2023
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The effect of dust emitted from desertic surfaces upon climate and ecosystems depends on size and mineralogy, but data from soil mineral atlases of desert soils are scarce. We performed particle-size distribution, mineralogy, and Fe speciation in southern Morocco. Results show coarser particles with high quartz proportion are near the elevated areas, while in depressed areas, sizes are finer, and proportions of clays and nano-Fe oxides are higher. This difference is important for dust modelling.
María Gonçalves Ageitos, Vincenzo Obiso, Ron L. Miller, Oriol Jorba, Martina Klose, Matt Dawson, Yves Balkanski, Jan Perlwitz, Sara Basart, Enza Di Tomaso, Jerónimo Escribano, Francesca Macchia, Gilbert Montané, Natalie M. Mahowald, Robert O. Green, David R. Thompson, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8623–8657, https://doi.org/10.5194/acp-23-8623-2023, https://doi.org/10.5194/acp-23-8623-2023, 2023
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Dust aerosols affect our climate differently depending on their mineral composition. We include dust mineralogy in an atmospheric model considering two existing soil maps, which still have large associated uncertainties. The soil data and the distribution of the minerals in different aerosol sizes are key to our model performance. We find significant regional variations in climate-relevant variables, which supports including mineralogy in our current models and the need for improved soil maps.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Claire Granier, Thierno Doumbia, Philippe Ciais, Zhu Liu, Robin D. Lamboll, Sabine Schindlbacher, Bradley Matthews, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8081–8101, https://doi.org/10.5194/acp-23-8081-2023, https://doi.org/10.5194/acp-23-8081-2023, 2023
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This study provides an intercomparison of European 2020 emission changes derived from official inventories, which are reported by countries under the framework of several international conventions and directives, and non-official near-real-time estimates, the use of which has significantly grown since the COVID-19 outbreak. The results of the work are used to produce recommendations on how best to approach and make use of near-real-time emissions for modelling and monitoring applications.
Cristina González-Flórez, Martina Klose, Andrés Alastuey, Sylvain Dupont, Jerónimo Escribano, Vicken Etyemezian, Adolfo Gonzalez-Romero, Yue Huang, Konrad Kandler, George Nikolich, Agnesh Panta, Xavier Querol, Cristina Reche, Jesús Yus-Díez, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 7177–7212, https://doi.org/10.5194/acp-23-7177-2023, https://doi.org/10.5194/acp-23-7177-2023, 2023
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Atmospheric mineral dust consists of tiny mineral particles that are emitted by wind erosion from arid regions. Its particle size distribution (PSD) affects its impact on the Earth's system. Nowadays, there is an incomplete understanding of the emitted dust PSD and a lot of debate about its variability. Here, we try to address these issues based on the measurements performed during a wind erosion and dust emission field campaign in the Moroccan Sahara within the framework of FRAGMENT project.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
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Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Aleksander Lacima, Hervé Petetin, Albert Soret, Dene Bowdalo, Oriol Jorba, Zhaoyue Chen, Raúl F. Méndez Turrubiates, Hicham Achebak, Joan Ballester, and Carlos Pérez García-Pando
Geosci. Model Dev., 16, 2689–2718, https://doi.org/10.5194/gmd-16-2689-2023, https://doi.org/10.5194/gmd-16-2689-2023, 2023
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Understanding how air pollution varies across space and time is of key importance for the safeguarding of human health. This work arose in the context of the project EARLY-ADAPT, for which the Barcelona Supercomputing Center developed an air pollution database covering all of Europe. Through different statistical methods, we compared two global pollution models against measurements from ground stations and found significant discrepancies between the observed and the modeled surface pollution.
Michail Mytilinaios, Sara Basart, Sergio Ciamprone, Juan Cuesta, Claudio Dema, Enza Di Tomaso, Paola Formenti, Antonis Gkikas, Oriol Jorba, Ralph Kahn, Carlos Pérez García-Pando, Serena Trippetta, and Lucia Mona
Atmos. Chem. Phys., 23, 5487–5516, https://doi.org/10.5194/acp-23-5487-2023, https://doi.org/10.5194/acp-23-5487-2023, 2023
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Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) dust reanalysis provides a high-resolution 3D reconstruction of past dust conditions, allowing better quantification of climate and socioeconomic dust impacts. We assess the performance of the reanalysis needed to reproduce dust optical depth using dust-related products retrieved from satellite and ground-based observations and show that it reproduces the spatial distribution and seasonal variability of atmospheric dust well.
Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodriguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
Geosci. Model Dev., 16, 2193–2213, https://doi.org/10.5194/gmd-16-2193-2023, https://doi.org/10.5194/gmd-16-2193-2023, 2023
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This work aims to derive and evaluate a general statistical post-processing tool specifically designed for the street scale that can be applied to any urban air quality system. Our data fusion methodology corrects NO2 fields based on continuous hourly observations and experimental campaigns. This study enables us to obtain exceedance probability maps of air quality standards. In 2019, 13 % of the Barcelona area had a 70 % or higher probability of exceeding the annual legal NO2 limit of 40 µg/m3.
Hervé Petetin, Marc Guevara, Steven Compernolle, Dene Bowdalo, Pierre-Antoine Bretonnière, Santiago Enciso, Oriol Jorba, Franco Lopez, Albert Soret, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 3905–3935, https://doi.org/10.5194/acp-23-3905-2023, https://doi.org/10.5194/acp-23-3905-2023, 2023
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This study analyses the potential of the TROPOMI space sensor for monitoring the variability of NO2 pollution over the Iberian Peninsula. A reduction of NO2 levels is observed during the weekend and in summer, especially over most urbanized areas, in agreement with surface observations. An enhancement of NO2 is found during summer with TROPOMI over croplands, potentially related to natural soil NO emissions, which illustrates the outstanding value of TROPOMI for complementing surface networks.
Agnesh Panta, Konrad Kandler, Andres Alastuey, Cristina González-Flórez, Adolfo González-Romero, Martina Klose, Xavier Querol, Cristina Reche, Jesús Yus-Díez, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 3861–3885, https://doi.org/10.5194/acp-23-3861-2023, https://doi.org/10.5194/acp-23-3861-2023, 2023
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Desert dust is a major aerosol component of the Earth system and affects the climate. Dust properties are influenced by particle size, mineralogy, shape, and mixing state. This work characterizes freshly emitted individual mineral dust particles from a major source region using electron microscopy. Our new insights into critical particle-specific information will contribute to better constraining climate models that consider mineralogical variations in their representation of the dust cycle.
Zhao-Yue Chen, Raul Méndez, Hervé Petetin, Aleksander Lacima, Carlos Pérez García-Pando, and Joan Ballester
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-104, https://doi.org/10.5194/essd-2023-104, 2023
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Given in the limitations of existing AOD and its size fraction information, a new 18-year daily Aerosol Optical Depth (AOD) dataset over Europe has been developed based on quantile machine learning (QML) models. This dataset improves the ability to monitor and analyse fine-mode and coarse-mode aerosols. They provide better tools to investigate negatively affect human health and have impacts on climate, visibility, and biogeochemical cycling.
Marios Chatziparaschos, Nikos Daskalakis, Stelios Myriokefalitakis, Nikos Kalivitis, Athanasios Nenes, María Gonçalves Ageitos, Montserrat Costa-Surós, Carlos Pérez García-Pando, Medea Zanoli, Mihalis Vrekoussis, and Maria Kanakidou
Atmos. Chem. Phys., 23, 1785–1801, https://doi.org/10.5194/acp-23-1785-2023, https://doi.org/10.5194/acp-23-1785-2023, 2023
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Ice formation is enabled by ice-nucleating particles (INP) at higher temperatures than homogeneous formation and can profoundly affect the properties of clouds. Our global model results show that K-feldspar is the most important contributor to INP concentrations globally, affecting mid-level mixed-phase clouds. However, quartz can significantly contribute and dominates the lowest and the highest altitudes of dust-derived INP, affecting mainly low-level and high-level mixed-phase clouds.
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
Atmos. Chem. Phys., 22, 11603–11630, https://doi.org/10.5194/acp-22-11603-2022, https://doi.org/10.5194/acp-22-11603-2022, 2022
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This study investigates the extent to which ozone forecasts provided by the Copernicus Atmospheric Monitoring Service (CAMS) can be improved using surface observations and state-of-the-art statistical methods. Through a case study over the Iberian Peninsula in 2018–2019, it unambiguously demonstrates the value of these methods for improving the raw CAMS O3 forecasts while at the same time highlighting the complexity of improving the detection of the highest O3 concentrations.
Philippe Thunis, Alain Clappier, Enrico Pisoni, Bertrand Bessagnet, Jeroen Kuenen, Marc Guevara, and Susana Lopez-Aparicio
Geosci. Model Dev., 15, 5271–5286, https://doi.org/10.5194/gmd-15-5271-2022, https://doi.org/10.5194/gmd-15-5271-2022, 2022
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In this work, we propose a screening method to improve the quality of emission inventories, which are responsible for large uncertainties in air-quality modeling. The first step of screening consists of keeping only emission contributions that are relevant enough. In a second step, the method identifies large differences that provide evidence of methodological divergence or errors. We used the approach to compare two versions of the CAMS-REG European-scale inventory over 150 European cities.
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.
Matthew L. Dawson, Christian Guzman, Jeffrey H. Curtis, Mario Acosta, Shupeng Zhu, Donald Dabdub, Andrew Conley, Matthew West, Nicole Riemer, and Oriol Jorba
Geosci. Model Dev., 15, 3663–3689, https://doi.org/10.5194/gmd-15-3663-2022, https://doi.org/10.5194/gmd-15-3663-2022, 2022
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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.
Stelios Myriokefalitakis, Elisa Bergas-Massó, María Gonçalves-Ageitos, Carlos Pérez García-Pando, Twan van Noije, Philippe Le Sager, Akinori Ito, Eleni Athanasopoulou, Athanasios Nenes, Maria Kanakidou, Maarten C. Krol, and Evangelos Gerasopoulos
Geosci. Model Dev., 15, 3079–3120, https://doi.org/10.5194/gmd-15-3079-2022, https://doi.org/10.5194/gmd-15-3079-2022, 2022
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We here describe the implementation of atmospheric multiphase processes in the EC-Earth Earth system model. We provide global budgets of oxalate, sulfate, and iron-containing aerosols, along with an analysis of the links among atmospheric composition, aqueous-phase processes, and aerosol dissolution, supported by comparison to observations. This work is a first step towards an interactive calculation of the deposition of bioavailable atmospheric iron coupled to the model’s ocean component.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Eleni Marinou, Nikos Hatzianastassiou, Jasper F. Kok, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 22, 3553–3578, https://doi.org/10.5194/acp-22-3553-2022, https://doi.org/10.5194/acp-22-3553-2022, 2022
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We present a comprehensive climatological analysis of dust optical depth (DOD) relying on the MIDAS dataset. MIDAS provides columnar mid-visible (550 nm) DOD at fine spatial resolution (0.1° × 0.1°) over a 15-year period (2003–2017). In the current study, the analysis is performed at various spatial (from regional to global) and temporal (from months to years) scales. More specifically, focus is given to specific regions hosting the major dust sources as well as downwind areas of the planet.
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.
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.
Twan van Noije, Tommi Bergman, Philippe Le Sager, Declan O'Donnell, Risto Makkonen, María Gonçalves-Ageitos, Ralf Döscher, Uwe Fladrich, Jost von Hardenberg, Jukka-Pekka Keskinen, Hannele Korhonen, Anton Laakso, Stelios Myriokefalitakis, Pirkka Ollinaho, Carlos Pérez García-Pando, Thomas Reerink, Roland Schrödner, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 5637–5668, https://doi.org/10.5194/gmd-14-5637-2021, https://doi.org/10.5194/gmd-14-5637-2021, 2021
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This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in CMIP6. We give an overview of the model and describe in detail how it differs from its predecessor and the other EC-Earth3 configurations. The model's performance is characterized using coupled simulations conducted for CMIP6. The model has an effective equilibrium climate sensitivity of 3.9 °C and a transient climate response of 2.1 °C.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Danny M. Leung, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, Jessica S. Wan, and Chloe A. Whicker
Atmos. Chem. Phys., 21, 8127–8167, https://doi.org/10.5194/acp-21-8127-2021, https://doi.org/10.5194/acp-21-8127-2021, 2021
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Desert dust interacts with virtually every component of the Earth system, including the climate system. We develop a new methodology to represent the global dust cycle that integrates observational constraints on the properties and abundance of desert dust with global atmospheric model simulations. We show that the resulting representation of the global dust cycle is more accurate than what can be obtained from a large number of current climate global atmospheric models.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, and Jessica S. Wan
Atmos. Chem. Phys., 21, 8169–8193, https://doi.org/10.5194/acp-21-8169-2021, https://doi.org/10.5194/acp-21-8169-2021, 2021
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The many impacts of dust on the Earth system depend on dust mineralogy, which varies between dust source regions. We constrain the contribution of the world’s main dust source regions by integrating dust observations with global model simulations. We find that Asian dust contributes more and that North African dust contributes less than models account for. We obtain a dataset of each source region’s contribution to the dust cycle that can be used to constrain dust impacts on the Earth system.
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.
Longlei Li, Natalie M. Mahowald, Ron L. Miller, Carlos Pérez García-Pando, Martina Klose, Douglas S. Hamilton, Maria Gonçalves Ageitos, Paul Ginoux, Yves Balkanski, Robert O. Green, Olga Kalashnikova, Jasper F. Kok, Vincenzo Obiso, David Paynter, and David R. Thompson
Atmos. Chem. Phys., 21, 3973–4005, https://doi.org/10.5194/acp-21-3973-2021, https://doi.org/10.5194/acp-21-3973-2021, 2021
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For the first time, this study quantifies the range of the dust direct radiative effect due to uncertainty in the soil mineral abundance using all currently available information. We show that the majority of the estimated direct radiative effect range is due to uncertainty in the simulated mass fractions of iron oxides and thus their soil abundance, which is independent of the model employed. We therefore prove the necessity of considering mineralogy for understanding dust–climate interactions.
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.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Alexandra Tsekeri, Eleni Marinou, Nikos Hatzianastassiou, and Carlos Pérez García-Pando
Atmos. Meas. Tech., 14, 309–334, https://doi.org/10.5194/amt-14-309-2021, https://doi.org/10.5194/amt-14-309-2021, 2021
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We present the development of the MIDAS (ModIs Dust AeroSol) data set, providing daily dust optical depth (DOD; 550 nm) at a global scale and fine spatial resolution (0.1° x 0.1°) over a 15-year period (2003–2017). It has been developed via the synergy of MODIS-Aqua and MERRA-2 data, while CALIOP and AERONET retrievals are used for its assessment. MIDAS upgrades existing dust observational capabilities, and it is suitable for dust climatological studies, model evaluation, and data assimilation.
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.
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.
Bing Pu, Paul Ginoux, Huan Guo, N. Christina Hsu, John Kimball, Beatrice Marticorena, Sergey Malyshev, Vaishali Naik, Norman T. O'Neill, Carlos Pérez García-Pando, Juliette Paireau, Joseph M. Prospero, Elena Shevliakova, and Ming Zhao
Atmos. Chem. Phys., 20, 55–81, https://doi.org/10.5194/acp-20-55-2020, https://doi.org/10.5194/acp-20-55-2020, 2020
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Dust emission initiates when surface wind velocities exceed a threshold depending on soil and surface characteristics and varying spatially and temporally. Climate models widely use wind erosion thresholds. The climatological monthly global distribution of the wind erosion threshold, Vthreshold, is retrieved using satellite and reanalysis products and improves the simulation of dust frequency, magnitude, and the seasonal cycle in the Geophysical Fluid Dynamics Laboratory land–atmosphere model.
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.
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.
Rachel A. Scanza, Douglas S. Hamilton, Carlos Perez Garcia-Pando, Clifton Buck, Alex Baker, and Natalie M. Mahowald
Atmos. Chem. Phys., 18, 14175–14196, https://doi.org/10.5194/acp-18-14175-2018, https://doi.org/10.5194/acp-18-14175-2018, 2018
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Soluble iron input to remote oceans from dust and combustion aerosols may significantly impact the ability of the ocean to remove carbon dioxide from the atmosphere. In this paper, the processing of insoluble iron during atmospheric transport is simulated using parameterizations that can be implemented in most Earth system models. Our mechanism reasonably matches observations and is computationally efficient, enabling the study of trends and climate impacts due to the Fe–C cycle.
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.
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
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.
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.
N. Huneeus, S. Basart, S. Fiedler, J.-J. Morcrette, A. Benedetti, J. Mulcahy, E. Terradellas, C. Pérez García-Pando, G. Pejanovic, S. Nickovic, P. Arsenovic, M. Schulz, E. Cuevas, J. M. Baldasano, J. Pey, S. Remy, and B. Cvetkovic
Atmos. Chem. Phys., 16, 4967–4986, https://doi.org/10.5194/acp-16-4967-2016, https://doi.org/10.5194/acp-16-4967-2016, 2016
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Five dust models are evaluated regarding their performance in predicting an intense Saharan dust outbreak affecting western and northern Europe (NE). Models predict the onset and evolution of the event for all analysed lead times. On average, differences among the models are larger than differences in lead times for each model. The models tend to underestimate the long-range transport towards NE. This is partly due to difficulties in simulating the vertical dust distribution and horizontal wind.
J. P. Perlwitz, C. Pérez García-Pando, and R. L. Miller
Atmos. Chem. Phys., 15, 11593–11627, https://doi.org/10.5194/acp-15-11593-2015, https://doi.org/10.5194/acp-15-11593-2015, 2015
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The mineral composition of dust aerosols is modeled. The mineral composition is derived by extending a method that provides the composition of wet-sieved soil to account for differences between the mineral fractions of the wet-sieved soil and the resulting aerosol concentration. An empirical constraint upon the relative emission of clay and silt is applied that further differentiates soil and aerosol mineral composition. A method is proposed for mixing minerals with iron oxide impurities.
J. P. Perlwitz, C. Pérez García-Pando, and R. L. Miller
Atmos. Chem. Phys., 15, 11629–11652, https://doi.org/10.5194/acp-15-11629-2015, https://doi.org/10.5194/acp-15-11629-2015, 2015
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A global compilation from nearly sixty measurement studies is used to evaluate two methods of simulating the mineral composition of dust aerosols. Dust emission based on wet-sieved soil is assumed for the first method. The second method reconstructs the aggregates and size distribution of the emitted dust aerosols. Only the second method is able to reproduce observed phyllosilicate fractions in the silt size range and reduces quartz overestimation. Substantial uncertainties remain.
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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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
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AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
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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.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
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Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
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The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
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The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
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We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
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This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
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The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
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The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
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This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
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We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
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This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
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In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
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Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Álvaro González-Cervera and Luis Durán
EGUsphere, https://doi.org/10.5194/egusphere-2024-958, https://doi.org/10.5194/egusphere-2024-958, 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 of broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-84, https://doi.org/10.5194/gmd-2024-84, 2024
Revised manuscript accepted for GMD
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We apply a comprehensive approach to select a subset of CMIP6 that is suitable for dynamical downscaling over Southeast Asia by considering model performance, model independence, data availability, and future climate change spread. The standardised benchmarking framework is applied to identify a subset of models through two stages of assessment: statistical-based and process-based metrics. We finalize a sub-set of two independent models for dynamical downscaling over Southeast Asia.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
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HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
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Short summary
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.
Atmospheric emission inventories, which describe the amounts of pollutants released into the air...