Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1721-2021
© Author(s) 2021. 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-14-1721-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
29 Mar 2021
Model evaluation paper |
| 29 Mar 2021
| 29 Mar 2021
Evaluation of ECMWF IFS-AER (CAMS) operational forecasts during cycle 41r1–46r1 with calibrated ceilometer profiles over Germany
Harald Flentje
CORRESPONDING AUTHOR
Deutscher Wetterdienst, Met. Obs. Hohenpeißenberg, Albin-Schwaiger-Weg 10, Hohenpeißenberg, Germany
Ina Mattis
Deutscher Wetterdienst, Met. Obs. Hohenpeißenberg, Albin-Schwaiger-Weg 10, Hohenpeißenberg, Germany
Zak Kipling
European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Samuel Rémy
HYGEOS, 165 Avenue de Bretagne, Lille, France
Werner Thomas
Deutscher Wetterdienst, Met. Obs. Hohenpeißenberg, Albin-Schwaiger-Weg 10, Hohenpeißenberg, Germany
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Atmos. Chem. Phys., 21, 2675–2692, https://doi.org/10.5194/acp-21-2675-2021, https://doi.org/10.5194/acp-21-2675-2021, 2021
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Following the transmission of SARS-CoV-2 to Europe, social distancing rules were introduced to prevent further spread. We investigate the impacts of the European lockdowns on black carbon (BC) emissions by means of in situ observations and inverse modelling. BC emissions declined by 23 kt in Europe during the lockdowns as compared with previous years and by 11 % as compared to the period prior to lockdowns. Residential combustion prevailed in Eastern Europe, as confirmed by remote sensing data.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
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Atmos. Chem. Phys., 20, 7049–7068, https://doi.org/10.5194/acp-20-7049-2020, https://doi.org/10.5194/acp-20-7049-2020, 2020
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Ka Lok Chan, Matthias Wiegner, Harald Flentje, Ina Mattis, Frank Wagner, Josef Gasteiger, and Alexander Geiß
Geosci. Model Dev., 11, 3807–3831, https://doi.org/10.5194/gmd-11-3807-2018, https://doi.org/10.5194/gmd-11-3807-2018, 2018
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The paper presents the comparison of ECMWF-IFS model simulation of aerosol backscatter profiles to long-term measurements of an extended ceilometer network. A significant influence of the numerical description of the hygroscopic growth of sea salt aerosols on the agreement between model and observations was found. Consideration of the nonsphericity of dust particles in the model reduced the attenuated backscatter of dust by ~&thinp;30 % and improved the agreement between model and observations.
Martine Collaud Coen, Elisabeth Andrews, Diego Aliaga, Marcos Andrade, Hristo Angelov, Nicolas Bukowiecki, Marina Ealo, Paulo Fialho, Harald Flentje, A. Gannet Hallar, Rakesh Hooda, Ivo Kalapov, Radovan Krejci, Neng-Huei Lin, Angela Marinoni, Jing Ming, Nhat Anh Nguyen, Marco Pandolfi, Véronique Pont, Ludwig Ries, Sergio Rodríguez, Gerhard Schauer, Karine Sellegri, Sangeeta Sharma, Junying Sun, Peter Tunved, Patricio Velasquez, and Dominique Ruffieux
Atmos. Chem. Phys., 18, 12289–12313, https://doi.org/10.5194/acp-18-12289-2018, https://doi.org/10.5194/acp-18-12289-2018, 2018
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High altitude stations are often emphasized as free tropospheric measuring sites but they remain influenced by atmospheric boundary layer. An ABL-TopoIndex is defined from a topography analysis around the stations. This new index allows ranking stations as a function of the ABL influence due to topography or help to choose a new site to sample FT. The ABL-TopoIndex is validated by aerosol optical properties and number concentration measured at 29 high altitude stations of five continents.
Marco Pandolfi, Lucas Alados-Arboledas, Andrés Alastuey, Marcos Andrade, Christo Angelov, Begoña Artiñano, John Backman, Urs Baltensperger, Paolo Bonasoni, Nicolas Bukowiecki, Martine Collaud Coen, Sébastien Conil, Esther Coz, Vincent Crenn, Vadimas Dudoitis, Marina Ealo, Kostas Eleftheriadis, Olivier Favez, Prodromos Fetfatzis, Markus Fiebig, Harald Flentje, Patrick Ginot, Martin Gysel, Bas Henzing, Andras Hoffer, Adela Holubova Smejkalova, Ivo Kalapov, Nikos Kalivitis, Giorgos Kouvarakis, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Chris Lunder, Krista Luoma, Hassan Lyamani, Angela Marinoni, Nikos Mihalopoulos, Marcel Moerman, José Nicolas, Colin O'Dowd, Tuukka Petäjä, Jean-Eudes Petit, Jean Marc Pichon, Nina Prokopciuk, Jean-Philippe Putaud, Sergio Rodríguez, Jean Sciare, Karine Sellegri, Erik Swietlicki, Gloria Titos, Thomas Tuch, Peter Tunved, Vidmantas Ulevicius, Aditya Vaishya, Milan Vana, Aki Virkkula, Stergios Vratolis, Ernest Weingartner, Alfred Wiedensohler, and Paolo Laj
Atmos. Chem. Phys., 18, 7877–7911, https://doi.org/10.5194/acp-18-7877-2018, https://doi.org/10.5194/acp-18-7877-2018, 2018
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This investigation presents the variability in near-surface in situ aerosol particle light-scattering measurements obtained over the past decade at 28 measuring atmospheric observatories which are part of the ACTRIS Research Infrastructure, and most of them belong to the GAW network. This paper provides a comprehensive picture of the spatial and temporal variability of aerosol particles optical properties in Europe.
Wolfram Birmili, Kay Weinhold, Fabian Rasch, André Sonntag, Jia Sun, Maik Merkel, Alfred Wiedensohler, Susanne Bastian, Alexander Schladitz, Gunter Löschau, Josef Cyrys, Mike Pitz, Jianwei Gu, Thomas Kusch, Harald Flentje, Ulrich Quass, Heinz Kaminski, Thomas A. J. Kuhlbusch, Frank Meinhardt, Andreas Schwerin, Olaf Bath, Ludwig Ries, Holger Gerwig, Klaus Wirtz, and Markus Fiebig
Earth Syst. Sci. Data, 8, 355–382, https://doi.org/10.5194/essd-8-355-2016, https://doi.org/10.5194/essd-8-355-2016, 2016
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The German Ultrafine Aerosol Network (GUAN) provides new continuous data on tropospheric aerosol particles including number size distributions and black carbon. The data are equally relevant for atmospheric studies related to both climate-related and health-related issues. The published data underwent uniform measures of quality assurance and control. The data are available free of charge at the World Data Center for Aerosols EBAS data repository.
A. Wagner, A.-M. Blechschmidt, I. Bouarar, E.-G. Brunke, C. Clerbaux, M. Cupeiro, P. Cristofanelli, H. Eskes, J. Flemming, H. Flentje, M. George, S. Gilge, A. Hilboll, A. Inness, J. Kapsomenakis, A. Richter, L. Ries, W. Spangl, O. Stein, R. Weller, and C. Zerefos
Atmos. Chem. Phys., 15, 14005–14030, https://doi.org/10.5194/acp-15-14005-2015, https://doi.org/10.5194/acp-15-14005-2015, 2015
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The Monitoring Atmospheric Composition and Climate project (MACC) operationally produces global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the model to simulate concentrations of reactive gases (carbon monoxide, nitrogen dioxide and ozone) between 2009 and 2012. The model reproduced reactive gas concentrations with consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations.
H. Eskes, V. Huijnen, A. Arola, A. Benedictow, A.-M. Blechschmidt, E. Botek, O. Boucher, I. Bouarar, S. Chabrillat, E. Cuevas, R. Engelen, H. Flentje, A. Gaudel, J. Griesfeller, L. Jones, J. Kapsomenakis, E. Katragkou, S. Kinne, B. Langerock, M. Razinger, A. Richter, M. Schultz, M. Schulz, N. Sudarchikova, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Geosci. Model Dev., 8, 3523–3543, https://doi.org/10.5194/gmd-8-3523-2015, https://doi.org/10.5194/gmd-8-3523-2015, 2015
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The MACC project is preparing the operational atmosphere service of the European Copernicus Programme, and uses data assimilation to combine atmospheric models with available observations. Our paper provides an overview of the aerosol and trace gas validation activity of MACC. Topics are the validation requirements, the measurement data, the assimilation systems, the upgrade procedure, operational aspects and the scoring methods. A summary is provided of recent results, including special events.
T. Trickl, H. Vogelmann, H. Flentje, and L. Ries
Atmos. Chem. Phys., 15, 9631–9649, https://doi.org/10.5194/acp-15-9631-2015, https://doi.org/10.5194/acp-15-9631-2015, 2015
D. C. S. Beddows, M. Dall'Osto, R. M. Harrison, M. Kulmala, A. Asmi, A. Wiedensohler, P. Laj, A.M. Fjaeraa, K. Sellegri, W. Birmili, N. Bukowiecki, E. Weingartner, U. Baltensperger, V. Zdimal, N. Zikova, J.-P. Putaud, A. Marinoni, P. Tunved, H.-C. Hansson, M. Fiebig, N. Kivekäs, E. Swietlicki, H. Lihavainen, E. Asmi, V. Ulevicius, P. P. Aalto, N. Mihalopoulos, N. Kalivitis, I. Kalapov, G. Kiss, G. de Leeuw, B. Henzing, C. O'Dowd, S. G. Jennings, H. Flentje, F. Meinhardt, L. Ries, H. A. C. Denier van der Gon, and A. J. H. Visschedijk
Atmos. Chem. Phys., 14, 4327–4348, https://doi.org/10.5194/acp-14-4327-2014, https://doi.org/10.5194/acp-14-4327-2014, 2014
U. Schumann, R. Hempel, H. Flentje, M. Garhammer, K. Graf, S. Kox, H. Lösslein, and B. Mayer
Atmos. Meas. Tech., 6, 3597–3612, https://doi.org/10.5194/amt-6-3597-2013, https://doi.org/10.5194/amt-6-3597-2013, 2013
A. Asmi, M. Collaud Coen, J. A. Ogren, E. Andrews, P. Sheridan, A. Jefferson, E. Weingartner, U. Baltensperger, N. Bukowiecki, H. Lihavainen, N. Kivekäs, E. Asmi, P. P. Aalto, M. Kulmala, A. Wiedensohler, W. Birmili, A. Hamed, C. O'Dowd, S. G Jennings, R. Weller, H. Flentje, A. M. Fjaeraa, M. Fiebig, C. L. Myhre, A. G. Hallar, E. Swietlicki, A. Kristensson, and P. Laj
Atmos. Chem. Phys., 13, 895–916, https://doi.org/10.5194/acp-13-895-2013, https://doi.org/10.5194/acp-13-895-2013, 2013
M. Collaud Coen, E. Andrews, A. Asmi, U. Baltensperger, N. Bukowiecki, D. Day, M. Fiebig, A. M. Fjaeraa, H. Flentje, A. Hyvärinen, A. Jefferson, S. G. Jennings, G. Kouvarakis, H. Lihavainen, C. Lund Myhre, W. C. Malm, N. Mihapopoulos, J. V. Molenar, C. O'Dowd, J. A. Ogren, B. A. Schichtel, P. Sheridan, A. Virkkula, E. Weingartner, R. Weller, and P. Laj
Atmos. Chem. Phys., 13, 869–894, https://doi.org/10.5194/acp-13-869-2013, https://doi.org/10.5194/acp-13-869-2013, 2013
Henk Eskes, Athanasios Tsikerdekis, Melanie Ades, Mihai Alexe, Anna Carlin Benedictow, Yasmine Bennouna, Lewis Blake, Idir Bouarar, Simon Chabrillat, Richard Engelen, Quentin Errera, Johannes Flemming, Sebastien Garrigues, Jan Griesfeller, Vincent Huijnen, Luka Ilic, Antje Inness, John Kapsomenakis, Zak Kipling, Bavo Langerock, Augustin Mortier, Mark Parrington, Isabelle Pison, Mikko Pitkanen, Samuel Remy, Andreas Richter, Anja Schoenhardt, Michael Schulz, Valerie Thouret, Thorsten Warneke, Christos Zerefos, and Vincent-Henri Peuch
EGUsphere, https://doi.org/10.5194/egusphere-2023-3129, https://doi.org/10.5194/egusphere-2023-3129, 2024
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of aerosols and trace gases in the atmosphere. On 27/06/2023 a major upgrade, Cy48R1, became operational. Comparisons with in situ, surface remote sensing, aircraft, balloon and satellite observations, show that the new CAMS system is a significant improvement. The results quantify the skill of CAMS to forecast impactful events, such as wildfires, dust storms and air pollution peaks.
Jia Sun, Markus Hermann, Kay Weinhold, Maik Merkel, Wolfram Birmili, Yifan Yang, Thomas Tuch, Harald Flentje, Björn Briel, Ludwig Ries, Cedric Couret, Michael Elsasser, Ralf Sohmer, Klaus Wirtz, Frank Meinhardt, Maik Schütze, Olaf Bath, Bryan Hellack, Veli-Matti Kerminen, Markku Kulmala, Nan Ma, and Alfred Wiedensohler
EGUsphere, https://doi.org/10.5194/egusphere-2023-2359, https://doi.org/10.5194/egusphere-2023-2359, 2024
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We investigated the characteristics of new particle formation (NPF) for various environments from urban background to high Alpine, and the impacts of NPF on cloud condensation nuclei and aerosol radiative forcing. The NPF features differ between site categories, implying the crucial role of local environments such as degree of emissions and meteorological conditions. The results also underscore the importance of the local environments when assessing the impact of NPF on climate in models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
EGUsphere, https://doi.org/10.5194/egusphere-2023-3072, https://doi.org/10.5194/egusphere-2023-3072, 2024
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In this paper we describe the development of the future operational cycle of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
EGUsphere, https://doi.org/10.5194/egusphere-2023-2930, https://doi.org/10.5194/egusphere-2023-2930, 2023
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EQSAM4Clim has recently been revised to provide an accurate and efficient method for calculating the acidity of atmospheric particles. It is based on an analytical concept that is sufficiently fast and free of numerical noise, which makes it attractive for air quality forecasting. Version 12 allows the calculation of aerosol composition based on the gas-liquid-solid and the reduced gas-liquid partitioning with the associated water uptake for both cases, including the acidity of the aerosols.
Peng Xian, Jeffrey S. Reid, Melanie Ades, Angela Benedettie, Peter R. Colarco, Arlindo da Silva, Tom F. Eck, Johannes Flemming, Edward J. Hyer, Zak Kipling, Samuel Rémy, Tsuyoshi Thomas Sekiyama, Taichu Tanaka, Keiya Yumimoto, and Jianglong Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2023-2354, https://doi.org/10.5194/egusphere-2023-2354, 2023
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The study compares and evaluates the monthly aerosol optical depth of four reanalyses (RA) and their consensus. The basic verification characteristics of these RA versus both AERONET and MODIS retrievals are presented. The study discusses the strength of each RA and identifies regions where diversity and challenges are prominent. The RA consensus usually performs very well on a global scale in terms of how well it matches the observational data, making it a good choice for various applications.
Sebastien Garrigues, Melanie Ades, Samuel Remy, Johannes Flemming, Zak Kipling, Istvan Laszlo, Mark Parrington, Antje Inness, Roberto Ribas, Luke Jones, Richard Engelen, and Vincent-Henri Peuch
Atmos. Chem. Phys., 23, 10473–10487, https://doi.org/10.5194/acp-23-10473-2023, https://doi.org/10.5194/acp-23-10473-2023, 2023
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global monitoring of aerosols using the ECMWF forecast model constrained by the assimilation of satellite aerosol optical depth (AOD). This work aims at evaluating the assimilation of the NOAA VIIRS AOD product in the ECMWF model. It shows that the introduction of VIIRS in the CAMS data assimilation system enhances the accuracy of the aerosol analysis, particularly over Europe and desert and maritime sites.
Claire L. Ryder, Clèment Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
EGUsphere, https://doi.org/10.5194/egusphere-2023-662, https://doi.org/10.5194/egusphere-2023-662, 2023
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Desert dust poses a hazard to aircraft because flying through it can cause engine components to degrade faster than they would otherwise. Here we quantify how much dust gets ingested into aircraft engines at worldwide airports. We find that Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. We show that dust ingestion can be reduced by changing the time of day of flights and the altitude of holding patterns.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Sebastien Garrigues, Samuel Remy, Julien Chimot, Melanie Ades, Antje Inness, Johannes Flemming, Zak Kipling, Istvan Laszlo, Angela Benedetti, Roberto Ribas, Soheila Jafariserajehlou, Bertrand Fougnie, Shobha Kondragunta, Richard Engelen, Vincent-Henri Peuch, Mark Parrington, Nicolas Bousserez, Margarita Vazquez Navarro, and Anna Agusti-Panareda
Atmos. Chem. Phys., 22, 14657–14692, https://doi.org/10.5194/acp-22-14657-2022, https://doi.org/10.5194/acp-22-14657-2022, 2022
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global monitoring of aerosols using the ECMWF forecast model constrained by the assimilation of satellite aerosol optical depth (AOD). This work aims at evaluating two new satellite AODs to enhance the CAMS aerosol global forecast. It highlights the spatial and temporal differences between the satellite AOD products at the model spatial resolution, which is essential information to design multi-satellite AOD data assimilation schemes.
Thomas Drugé, Pierre Nabat, Marc Mallet, Martine Michou, Samuel Rémy, and Oleg Dubovik
Atmos. Chem. Phys., 22, 12167–12205, https://doi.org/10.5194/acp-22-12167-2022, https://doi.org/10.5194/acp-22-12167-2022, 2022
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This study presents the implementation of brown carbon in the atmospheric component of the CNRM global climate model and particularly in its aerosol scheme TACTIC. Several simulations were carried out with this climate model, over the period 2000–2014, to evaluate the model by comparison with different reference datasets (PARASOL-GRASP, OMI-OMAERUVd, MACv2, FMI_SAT, AERONET) and to analyze the brown carbon radiative and climatic effects.
Sini Isokääntä, Paul Kim, Santtu Mikkonen, Thomas Kühn, Harri Kokkola, Taina Yli-Juuti, Liine Heikkinen, Krista Luoma, Tuukka Petäjä, Zak Kipling, Daniel Partridge, and Annele Virtanen
Atmos. Chem. Phys., 22, 11823–11843, https://doi.org/10.5194/acp-22-11823-2022, https://doi.org/10.5194/acp-22-11823-2022, 2022
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This research employs air mass history analysis and observations to study how clouds and precipitation affect atmospheric aerosols during transport to a boreal forest site. The mass concentrations of studied chemical species showed exponential decrease as a function of accumulated rain along the air mass route. Our analysis revealed in-cloud sulfate formation, while no major changes in organic mass were seen. Most of the in-cloud-formed sulfate could be assigned to particle sizes above 200 nm.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Vincent Huijnen, Philippe Le Sager, Marcus O. Köhler, Glenn Carver, Samuel Rémy, Johannes Flemming, Simon Chabrillat, Quentin Errera, and Twan van Noije
Geosci. Model Dev., 15, 6221–6241, https://doi.org/10.5194/gmd-15-6221-2022, https://doi.org/10.5194/gmd-15-6221-2022, 2022
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We report on the first implementation of atmospheric chemistry and aerosol as part of the OpenIFS model, based on the CAMS global model. We give an overview of the model and evaluate two reference model configurations, with and without the stratospheric chemistry extension, against a variety of observational datasets. This OpenIFS version with atmospheric composition components is open to the scientific user community under a standard OpenIFS license.
Peng Xian, Jianglong Zhang, Norm T. O'Neill, Travis D. Toth, Blake Sorenson, Peter R. Colarco, Zak Kipling, Edward J. Hyer, James R. Campbell, Jeffrey S. Reid, and Keyvan Ranjbar
Atmos. Chem. Phys., 22, 9915–9947, https://doi.org/10.5194/acp-22-9915-2022, https://doi.org/10.5194/acp-22-9915-2022, 2022
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The study provides baseline Arctic spring and summertime aerosol optical depth climatology, trend, and extreme event statistics from 2003 to 2019 using a combination of aerosol reanalyses, remote sensing, and ground observations. Biomass burning smoke has an overwhelming contribution to black carbon (an efficient climate forcer) compared to anthropogenic sources. Burning's large interannual variability and increasing summer trend have important implications for the Arctic climate.
Samuel Rémy, Zak Kipling, Vincent Huijnen, Johannes Flemming, Pierre Nabat, Martine Michou, Melanie Ades, Richard Engelen, and Vincent-Henri Peuch
Geosci. Model Dev., 15, 4881–4912, https://doi.org/10.5194/gmd-15-4881-2022, https://doi.org/10.5194/gmd-15-4881-2022, 2022
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This article describes a new version of IFS-AER, the tropospheric aerosol scheme used to provide global aerosol products within the Copernicus Atmosphere Monitoring Service (CAMS) cycle. Several components of the model have been updated, such as the dynamical dust and sea salt aerosol emission schemes. New deposition schemes have also been incorporated but are not yet used operationally. This new version of IFS-AER has been evaluated and shown to have a greater skill than previous versions.
Joe McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Luca Cantarello, Richard Engelen, Vincent Huijnen, Antje Inness, Zak Kipling, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 5961–5981, https://doi.org/10.5194/acp-22-5961-2022, https://doi.org/10.5194/acp-22-5961-2022, 2022
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Concentrations of atmospheric methane continue to grow, in recent years at an increasing rate, for unknown reasons. Using newly available satellite observations and a state-of-the-art weather prediction model we perform global estimates of emissions from hotspots at high resolution. Results show that the system can accurately report on biases in national inventories and is used to conclude that the early COVID-19 slowdown period (March–June 2020) had little impact on global methane emissions.
Xiaoxia Shang, Holger Baars, Iwona S. Stachlewska, Ina Mattis, and Mika Komppula
Atmos. Chem. Phys., 22, 3931–3944, https://doi.org/10.5194/acp-22-3931-2022, https://doi.org/10.5194/acp-22-3931-2022, 2022
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This study reports pollen observations at four lidar stations (Hohenpeißenberg, Germany; Kuopio, Finland; Leipzig, Germany; and Warsaw, Poland) during the intensive observation campaign organized in May 2020. A novel simple method for the characterization of the pure pollen is proposed, based on lidar measurements. It was applied to evaluate the pollen depolarization ratio and for the aerosol classifications.
Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
Atmos. Chem. Phys., 21, 17185–17223, https://doi.org/10.5194/acp-21-17185-2021, https://doi.org/10.5194/acp-21-17185-2021, 2021
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Aerosol particles are a complex component of the atmospheric system the effects of which are among the most uncertain in climate change projections. Using data collected at 62 stations, this study provides the most up-to-date picture of the spatial distribution of particle number concentration and size distribution worldwide, with the aim of contributing to better representation of aerosols and their interactions with clouds in models and, therefore, better evaluation of their impact on climate.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
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Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Anthony C. Jones, Adrian Hill, Samuel Remy, N. Luke Abraham, Mohit Dalvi, Catherine Hardacre, Alan J. Hewitt, Ben Johnson, Jane P. Mulcahy, and Steven T. Turnock
Atmos. Chem. Phys., 21, 15901–15927, https://doi.org/10.5194/acp-21-15901-2021, https://doi.org/10.5194/acp-21-15901-2021, 2021
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Ammonium nitrate is hard to model because it forms and evaporates rapidly. One approach is to relate its equilibrium concentration to temperature, humidity, and the amount of nitric acid and ammonia gases. Using this approach, we limit the rate at which equilibrium is reached using various condensation rates in a climate model. We show that ammonium nitrate concentrations are highly sensitive to the condensation rate. Our results will help improve the representation of nitrate in climate models.
Mariana Adam, Iwona S. Stachlewska, Lucia Mona, Nikolaos Papagiannopoulos, Juan Antonio Bravo-Aranda, Michaël Sicard, Doina N. Nicolae, Livio Belegante, Lucja Janicka, Dominika Szczepanik, Maria Mylonaki, Christina-Anna Papanikolaou, Nikolaos Siomos, Kalliopi Artemis Voudouri, Luca Alados-Arboledas, Arnoud Apituley, Ina Mattis, Anatoli Chaikovsky, Constantino Muñoz-Porcar, Aleksander Pietruczuk, Daniele Bortoli, Holger Baars, Ivan Grigorov, and Zahary Peshev
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-759, https://doi.org/10.5194/acp-2021-759, 2021
Revised manuscript not accepted
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Results over 10 years of biomass burning events measured by EARLINET are analysed by means of the intensive parameters, based on the methodology described in Part I. Smoke type is characterized for each of the four geographical regions based on continental smoke origin. Relationships between intensive parameters or colour ratios are shown. The smoke is labelled in average as aged smoke.
Andrea Cuesta-Mosquera, Griša Močnik, Luka Drinovec, Thomas Müller, Sascha Pfeifer, María Cruz Minguillón, Björn Briel, Paul Buckley, Vadimas Dudoitis, Javier Fernández-García, María Fernández-Amado, Joel Ferreira De Brito, Veronique Riffault, Harald Flentje, Eimear Heffernan, Nikolaos Kalivitis, Athina-Cerise Kalogridis, Hannes Keernik, Luminita Marmureanu, Krista Luoma, Angela Marinoni, Michael Pikridas, Gerhard Schauer, Norbert Serfozo, Henri Servomaa, Gloria Titos, Jesús Yus-Díez, Natalia Zioła, and Alfred Wiedensohler
Atmos. Meas. Tech., 14, 3195–3216, https://doi.org/10.5194/amt-14-3195-2021, https://doi.org/10.5194/amt-14-3195-2021, 2021
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Measurements of black carbon must be conducted with instruments operating in quality-checked and assured conditions to generate reliable and comparable data. Here, 23 Aethalometers monitoring black carbon mass concentrations in European networks were characterized and intercompared. The influence of different aerosol sources, maintenance activities, and the filter material on the instrumental variabilities were investigated. Good agreement and in general low deviations were seen.
Nikolaos Evangeliou, Stephen M. Platt, Sabine Eckhardt, Cathrine Lund Myhre, Paolo Laj, Lucas Alados-Arboledas, John Backman, Benjamin T. Brem, Markus Fiebig, Harald Flentje, Angela Marinoni, Marco Pandolfi, Jesus Yus-Dìez, Natalia Prats, Jean P. Putaud, Karine Sellegri, Mar Sorribas, Konstantinos Eleftheriadis, Stergios Vratolis, Alfred Wiedensohler, and Andreas Stohl
Atmos. Chem. Phys., 21, 2675–2692, https://doi.org/10.5194/acp-21-2675-2021, https://doi.org/10.5194/acp-21-2675-2021, 2021
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Following the transmission of SARS-CoV-2 to Europe, social distancing rules were introduced to prevent further spread. We investigate the impacts of the European lockdowns on black carbon (BC) emissions by means of in situ observations and inverse modelling. BC emissions declined by 23 kt in Europe during the lockdowns as compared with previous years and by 11 % as compared to the period prior to lockdowns. Residential combustion prevailed in Eastern Europe, as confirmed by remote sensing data.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
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Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Peng Xian, Philip J. Klotzbach, Jason P. Dunion, Matthew A. Janiga, Jeffrey S. Reid, Peter R. Colarco, and Zak Kipling
Atmos. Chem. Phys., 20, 15357–15378, https://doi.org/10.5194/acp-20-15357-2020, https://doi.org/10.5194/acp-20-15357-2020, 2020
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Using dust AOD (DAOD) data from three aerosol reanalyses, we explored the correlative relationships between DAOD and multiple indices representing seasonal Atlantic TC activities. A robust negative correlation with Caribbean DAOD and Atlantic TC activity was found. We documented for the first time the regional differences of this relationship for over the Caribbean and the tropical North Atlantic. We also evaluated the impacts of potential confounding climate factors in this relationship.
Augustin Mortier, Jonas Gliß, Michael Schulz, Wenche Aas, Elisabeth Andrews, Huisheng Bian, Mian Chin, Paul Ginoux, Jenny Hand, Brent Holben, Hua Zhang, Zak Kipling, Alf Kirkevåg, Paolo Laj, Thibault Lurton, Gunnar Myhre, David Neubauer, Dirk Olivié, Knut von Salzen, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 20, 13355–13378, https://doi.org/10.5194/acp-20-13355-2020, https://doi.org/10.5194/acp-20-13355-2020, 2020
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We present a multiparameter analysis of the aerosol trends over the last 2 decades in the different regions of the world. In most of the regions, ground-based observations show a decrease in aerosol content in both the total atmospheric column and at the surface. The use of climate models, assessed against these observations, reveals however an increase in the total aerosol load, which is not seen with the sole use of observation due to partial coverage in space and time.
Debbie O'Sullivan, Franco Marenco, Claire L. Ryder, Yaswant Pradhan, Zak Kipling, Ben Johnson, Angela Benedetti, Melissa Brooks, Matthew McGill, John Yorks, and Patrick Selmer
Atmos. Chem. Phys., 20, 12955–12982, https://doi.org/10.5194/acp-20-12955-2020, https://doi.org/10.5194/acp-20-12955-2020, 2020
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Mineral dust is an important component of the climate system, and we assess how well it is predicted by two operational models. We flew an aircraft in the dust layers in the eastern Atlantic, and we also make use of satellites. We show that models predict the dust layer too low and that it predicts the particles to be too small. We believe that these discrepancies may be overcome if models can be constrained with operational observations of dust vertical and size-resolved distribution.
Nikolaos Papagiannopoulos, Giuseppe D'Amico, Anna Gialitaki, Nicolae Ajtai, Lucas Alados-Arboledas, Aldo Amodeo, Vassilis Amiridis, Holger Baars, Dimitris Balis, Ioannis Binietoglou, Adolfo Comerón, Davide Dionisi, Alfredo Falconieri, Patrick Fréville, Anna Kampouri, Ina Mattis, Zoran Mijić, Francisco Molero, Alex Papayannis, Gelsomina Pappalardo, Alejandro Rodríguez-Gómez, Stavros Solomos, and Lucia Mona
Atmos. Chem. Phys., 20, 10775–10789, https://doi.org/10.5194/acp-20-10775-2020, https://doi.org/10.5194/acp-20-10775-2020, 2020
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Volcanic and desert dust particles affect human activities in manifold ways; consequently, mitigation tools are important. Their early detection and the issuance of early warnings are key elements in the initiation of operational response procedures. A methodology for the early warning of these hazards using European Aerosol Research Lidar Network (EARLINET) data is presented. The tailored product is investigated during a volcanic eruption and mineral dust advected in the eastern Mediterranean.
María A. Burgos, Elisabeth Andrews, Gloria Titos, Angela Benedetti, Huisheng Bian, Virginie Buchard, Gabriele Curci, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Anton Laakso, Julie Letertre-Danczak, Marianne T. Lund, Hitoshi Matsui, Gunnar Myhre, Cynthia Randles, Michael Schulz, Twan van Noije, Kai Zhang, Lucas Alados-Arboledas, Urs Baltensperger, Anne Jefferson, James Sherman, Junying Sun, Ernest Weingartner, and Paul Zieger
Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, https://doi.org/10.5194/acp-20-10231-2020, 2020
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We investigate how well models represent the enhancement in scattering coefficients due to particle water uptake, and perform an evaluation of several implementation schemes used in ten Earth system models. Our results show the importance of the parameterization of hygroscopicity and model chemistry as drivers of some of the observed diversity amongst model estimates. The definition of dry conditions and the phenomena taking place in this relative humidity range also impact the model evaluation.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
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The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Martine Collaud Coen, Elisabeth Andrews, Andrés Alastuey, Todor Petkov Arsov, John Backman, Benjamin T. Brem, Nicolas Bukowiecki, Cédric Couret, Konstantinos Eleftheriadis, Harald Flentje, Markus Fiebig, Martin Gysel-Beer, Jenny L. Hand, András Hoffer, Rakesh Hooda, Christoph Hueglin, Warren Joubert, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Casper Labuschagne, Neng-Huei Lin, Yong Lin, Cathrine Lund Myhre, Krista Luoma, Hassan Lyamani, Angela Marinoni, Olga L. Mayol-Bracero, Nikos Mihalopoulos, Marco Pandolfi, Natalia Prats, Anthony J. Prenni, Jean-Philippe Putaud, Ludwig Ries, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Patrick Sheridan, James Patrick Sherman, Junying Sun, Gloria Titos, Elvis Torres, Thomas Tuch, Rolf Weller, Alfred Wiedensohler, Paul Zieger, and Paolo Laj
Atmos. Chem. Phys., 20, 8867–8908, https://doi.org/10.5194/acp-20-8867-2020, https://doi.org/10.5194/acp-20-8867-2020, 2020
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Long-term trends of aerosol radiative properties (52 stations) prove that aerosol load has significantly decreased over the last 20 years. Scattering trends are negative in Europe (EU) and North America (NA), not ss in Asia, and show a mix of positive and negative trends at polar stations. Absorption has mainly negative trends. The single scattering albedo has positive trends in Asia and eastern EU and negative in western EU and NA, leading to a global positive median trend of 0.02 % per year.
Mariana Adam, Doina Nicolae, Livio Belegante, Iwona S. Stachlewska, Lucja Janicka, Dominika Szczepanik, Maria Mylonaki, Christiana Anna Papanikolaou, Nikos Siomos, Kalliopi Artemis Voudouri, Luca Alados-Arboledas, Juan Antonio Bravo-Aranda, Arnoud Apituley, Nikolaos Papagiannopoulos, Lucia Mona, Ina Mattis, Anatoli Chaikovsky, Michaël Sicard, Constantino Muñoz-Porcar, Aleksander Pietruczuk, Daniele Bortoli, Holger Baars, Ivan Grigorov, and Zahary Peshev
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-647, https://doi.org/10.5194/acp-2020-647, 2020
Revised manuscript not accepted
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Results over 10 years of biomass burning events measured by EARLINET are analysed by means of the intensive parameters based on the methodology described in Part I. Smoke type is characterized for each of the four geographical regions based on continental smoke origin. Relationships between intensive parameters or colour ratios are shown. The smoke is labelled in average as aged smoke. The local smoke has a smaller lidar ratio while the depolarization is smaller for long range transported smoke.
Jia Sun, Wolfram Birmili, Markus Hermann, Thomas Tuch, Kay Weinhold, Maik Merkel, Fabian Rasch, Thomas Müller, Alexander Schladitz, Susanne Bastian, Gunter Löschau, Josef Cyrys, Jianwei Gu, Harald Flentje, Björn Briel, Christoph Asbach, Heinz Kaminski, Ludwig Ries, Ralf Sohmer, Holger Gerwig, Klaus Wirtz, Frank Meinhardt, Andreas Schwerin, Olaf Bath, Nan Ma, and Alfred Wiedensohler
Atmos. Chem. Phys., 20, 7049–7068, https://doi.org/10.5194/acp-20-7049-2020, https://doi.org/10.5194/acp-20-7049-2020, 2020
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To evaluate the effectiveness of emission mitigation policies, we evaluated the trends of the size-resolved particle number concentrations and equivalent black carbon mass concentration at 16 observational sites for various environments in Germany (2009–2018). Overall, significant decrease trends are found for most of the parameters and sites. This study suggests that a combination of emission mitigation policies can effectively improve the air quality on large spatial scales such as in Germany.
Joe R. McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Margarita Choulga, Andrew Dawson, Richard Engelen, Zak Kipling, and Simon Lang
Geosci. Model Dev., 13, 2297–2313, https://doi.org/10.5194/gmd-13-2297-2020, https://doi.org/10.5194/gmd-13-2297-2020, 2020
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To infer carbon emissions from observations using atmospheric models, detailed knowledge of uncertainty is required. The uncertainties associated with models are often estimated because they are difficult to attribute. Here we use a state-of-the-art weather model to assess the impact of uncertainty in the wind fields on atmospheric concentrations of carbon dioxide. These results can be used to help quantify the uncertainty in estimated carbon emissions from atmospheric observations.
Matthias Wiegner, Alexander Geiß, Ina Mattis, Fred Meier, and Thomas Ruhtz
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-332, https://doi.org/10.5194/acp-2020-332, 2020
Publication in ACP not foreseen
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We investigated ceilometer signals from 2 testbeds in Munich and Berlin, Germany, with respect to their representativeness. For each testbed data of 24 months from 6 ceilometers were available. Two parameters were discussed: the mixing layer height (MLH) as an indicator for the vertical distribution and the integrated backscatter as a proxy for the amount of aerosols in the mixing layer. We found that only the MLH determined from a single ceilometer is applicable for a whole metropolitan area.
Zak Kipling, Laurent Labbouz, and Philip Stier
Atmos. Chem. Phys., 20, 4445–4460, https://doi.org/10.5194/acp-20-4445-2020, https://doi.org/10.5194/acp-20-4445-2020, 2020
Alessio Bozzo, Angela Benedetti, Johannes Flemming, Zak Kipling, and Samuel Rémy
Geosci. Model Dev., 13, 1007–1034, https://doi.org/10.5194/gmd-13-1007-2020, https://doi.org/10.5194/gmd-13-1007-2020, 2020
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Aerosols are tiny particles of natural and anthropogenic origin transported by the winds in the Earth's atmosphere. These particles play a key role in the energy budget of our planet. In numerical models of the Earth's atmosphere, aerosols spatial distribution are often represented by conditions averaged over several years. We prepared a new aerosol climatology and used it in a numerical weather model. We show that in certain regions aerosols can affect the quality of numerical weather forecast.
Holger Baars, Albert Ansmann, Kevin Ohneiser, Moritz Haarig, Ronny Engelmann, Dietrich Althausen, Ingrid Hanssen, Michael Gausa, Aleksander Pietruczuk, Artur Szkop, Iwona S. Stachlewska, Dongxiang Wang, Jens Reichardt, Annett Skupin, Ina Mattis, Thomas Trickl, Hannes Vogelmann, Francisco Navas-Guzmán, Alexander Haefele, Karen Acheson, Albert A. Ruth, Boyan Tatarov, Detlef Müller, Qiaoyun Hu, Thierry Podvin, Philippe Goloub, Igor Veselovskii, Christophe Pietras, Martial Haeffelin, Patrick Fréville, Michaël Sicard, Adolfo Comerón, Alfonso Javier Fernández García, Francisco Molero Menéndez, Carmen Córdoba-Jabonero, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Daniele Bortoli, Maria João Costa, Davide Dionisi, Gian Luigi Liberti, Xuan Wang, Alessia Sannino, Nikolaos Papagiannopoulos, Antonella Boselli, Lucia Mona, Giuseppe D'Amico, Salvatore Romano, Maria Rita Perrone, Livio Belegante, Doina Nicolae, Ivan Grigorov, Anna Gialitaki, Vassilis Amiridis, Ourania Soupiona, Alexandros Papayannis, Rodanthi-Elisaveth Mamouri, Argyro Nisantzi, Birgit Heese, Julian Hofer, Yoav Y. Schechner, Ulla Wandinger, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 15183–15198, https://doi.org/10.5194/acp-19-15183-2019, https://doi.org/10.5194/acp-19-15183-2019, 2019
Samuel Rémy, Zak Kipling, Johannes Flemming, Olivier Boucher, Pierre Nabat, Martine Michou, Alessio Bozzo, Melanie Ades, Vincent Huijnen, Angela Benedetti, Richard Engelen, Vincent-Henri Peuch, and Jean-Jacques Morcrette
Geosci. Model Dev., 12, 4627–4659, https://doi.org/10.5194/gmd-12-4627-2019, https://doi.org/10.5194/gmd-12-4627-2019, 2019
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This article describes the IFS-AER aerosol module used operationally in the Integrated Forecasting System (IFS) cycle 45R1, operated by the ECMWF in the framework of the Copernicus Atmospheric Monitoring Services (CAMS). We describe the different parameterizations for aerosol sources, sinks, and how the aerosols are integrated in the larger atmospheric composition forecasting system. The skill of PM and AOD simulations against observations is improved compared to the older cycle 40R2.
Emmanouil Proestakis, Vassilis Amiridis, Eleni Marinou, Ioannis Binietoglou, Albert Ansmann, Ulla Wandinger, Julian Hofer, John Yorks, Edward Nowottnick, Abduvosit Makhmudov, Alexandros Papayannis, Aleksander Pietruczuk, Anna Gialitaki, Arnoud Apituley, Artur Szkop, Constantino Muñoz Porcar, Daniele Bortoli, Davide Dionisi, Dietrich Althausen, Dimitra Mamali, Dimitris Balis, Doina Nicolae, Eleni Tetoni, Gian Luigi Liberti, Holger Baars, Ina Mattis, Iwona Sylwia Stachlewska, Kalliopi Artemis Voudouri, Lucia Mona, Maria Mylonaki, Maria Rita Perrone, Maria João Costa, Michael Sicard, Nikolaos Papagiannopoulos, Nikolaos Siomos, Pasquale Burlizzi, Rebecca Pauly, Ronny Engelmann, Sabur Abdullaev, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 11743–11764, https://doi.org/10.5194/acp-19-11743-2019, https://doi.org/10.5194/acp-19-11743-2019, 2019
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To increase accuracy and validate satellite-based products, comparison with ground-based reference observations is required. To do this, we present evaluation activity of EARLINET for the qualitative and quantitative assessment of NASA's CATS lidar operating aboard the International Space Station (ISS) while identified discrepancies are discussed. Better understanding CATS performance and limitations provides a valuable basis for scientific studies implementing the satellite-based lidar system.
Antje Inness, Melanie Ades, Anna Agustí-Panareda, Jérôme Barré, Anna Benedictow, Anne-Marlene Blechschmidt, Juan Jose Dominguez, Richard Engelen, Henk Eskes, Johannes Flemming, Vincent Huijnen, Luke Jones, Zak Kipling, Sebastien Massart, Mark Parrington, Vincent-Henri Peuch, Miha Razinger, Samuel Remy, Michael Schulz, and Martin Suttie
Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, https://doi.org/10.5194/acp-19-3515-2019, 2019
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This paper describes a new global dataset of atmospheric composition data for the years 2003-2016 that has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). It is called the CAMS reanalysis and provides information on aerosols and reactive gases. The CAMS reanalysis shows an improved performance compared to our previous atmospheric composition reanalyses; has smaller biases compared to independent O3, CO, NO2 and aerosol observations; and is more consistent in time.
Tobias Anhäuser, Birgit Sehls, Werner Thomas, Claudia Hartl, Markus Greule, Denis Scholz, Jan Esper, and Frank Keppler
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-8, https://doi.org/10.5194/cp-2019-8, 2019
Revised manuscript not accepted
Matthias Wiegner, Ina Mattis, Margit Pattantyús-Ábrahám, Juan Antonio Bravo-Aranda, Yann Poltera, Alexander Haefele, Maxime Hervo, Ulrich Görsdorf, Ronny Leinweber, Josef Gasteiger, Martial Haeffelin, Frank Wagner, Jan Cermak, Katerina Komínková, Mike Brettle, Christoph Münkel, and Kornelia Pönitz
Atmos. Meas. Tech., 12, 471–490, https://doi.org/10.5194/amt-12-471-2019, https://doi.org/10.5194/amt-12-471-2019, 2019
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Many ceilometers are influenced by water vapor absorption in the spectral range around 910 nm. Thus, a correction is required to retrieve aerosol optical properties. Validation of this correction scheme was performed in the framework of CeiLinEx2015 for several ceilometers with good agreement for Vaisala's CL51 ceilometer. For future applications we recommend monitoring the emitted wavelength and providing
darkmeasurements on a regular basis to be able to correct for signal artifacts.
Angela Benedetti, Francesca Di Giuseppe, Luke Jones, Vincent-Henri Peuch, Samuel Rémy, and Xiaoye Zhang
Atmos. Chem. Phys., 19, 987–998, https://doi.org/10.5194/acp-19-987-2019, https://doi.org/10.5194/acp-19-987-2019, 2019
Ka Lok Chan, Matthias Wiegner, Harald Flentje, Ina Mattis, Frank Wagner, Josef Gasteiger, and Alexander Geiß
Geosci. Model Dev., 11, 3807–3831, https://doi.org/10.5194/gmd-11-3807-2018, https://doi.org/10.5194/gmd-11-3807-2018, 2018
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The paper presents the comparison of ECMWF-IFS model simulation of aerosol backscatter profiles to long-term measurements of an extended ceilometer network. A significant influence of the numerical description of the hygroscopic growth of sea salt aerosols on the agreement between model and observations was found. Consideration of the nonsphericity of dust particles in the model reduced the attenuated backscatter of dust by ~&thinp;30 % and improved the agreement between model and observations.
Martine Collaud Coen, Elisabeth Andrews, Diego Aliaga, Marcos Andrade, Hristo Angelov, Nicolas Bukowiecki, Marina Ealo, Paulo Fialho, Harald Flentje, A. Gannet Hallar, Rakesh Hooda, Ivo Kalapov, Radovan Krejci, Neng-Huei Lin, Angela Marinoni, Jing Ming, Nhat Anh Nguyen, Marco Pandolfi, Véronique Pont, Ludwig Ries, Sergio Rodríguez, Gerhard Schauer, Karine Sellegri, Sangeeta Sharma, Junying Sun, Peter Tunved, Patricio Velasquez, and Dominique Ruffieux
Atmos. Chem. Phys., 18, 12289–12313, https://doi.org/10.5194/acp-18-12289-2018, https://doi.org/10.5194/acp-18-12289-2018, 2018
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High altitude stations are often emphasized as free tropospheric measuring sites but they remain influenced by atmospheric boundary layer. An ABL-TopoIndex is defined from a topography analysis around the stations. This new index allows ranking stations as a function of the ABL influence due to topography or help to choose a new site to sample FT. The ABL-TopoIndex is validated by aerosol optical properties and number concentration measured at 29 high altitude stations of five continents.
Albert Ansmann, Holger Baars, Alexandra Chudnovsky, Ina Mattis, Igor Veselovskii, Moritz Haarig, Patric Seifert, Ronny Engelmann, and Ulla Wandinger
Atmos. Chem. Phys., 18, 11831–11845, https://doi.org/10.5194/acp-18-11831-2018, https://doi.org/10.5194/acp-18-11831-2018, 2018
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Extremely large light extinction coefficients of 500 Mm-1, about 20 times higher than after the Pinatubo volcanic eruptions in 1991, were observed by EARLINET lidars in the stratosphere over central Europe from 21 to 22 August, 2017. This paper provides an overview based on ground-based (lidar, AERONET) and satellite (MODIS, OMI) remote sensing.
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.
Marco Pandolfi, Lucas Alados-Arboledas, Andrés Alastuey, Marcos Andrade, Christo Angelov, Begoña Artiñano, John Backman, Urs Baltensperger, Paolo Bonasoni, Nicolas Bukowiecki, Martine Collaud Coen, Sébastien Conil, Esther Coz, Vincent Crenn, Vadimas Dudoitis, Marina Ealo, Kostas Eleftheriadis, Olivier Favez, Prodromos Fetfatzis, Markus Fiebig, Harald Flentje, Patrick Ginot, Martin Gysel, Bas Henzing, Andras Hoffer, Adela Holubova Smejkalova, Ivo Kalapov, Nikos Kalivitis, Giorgos Kouvarakis, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Chris Lunder, Krista Luoma, Hassan Lyamani, Angela Marinoni, Nikos Mihalopoulos, Marcel Moerman, José Nicolas, Colin O'Dowd, Tuukka Petäjä, Jean-Eudes Petit, Jean Marc Pichon, Nina Prokopciuk, Jean-Philippe Putaud, Sergio Rodríguez, Jean Sciare, Karine Sellegri, Erik Swietlicki, Gloria Titos, Thomas Tuch, Peter Tunved, Vidmantas Ulevicius, Aditya Vaishya, Milan Vana, Aki Virkkula, Stergios Vratolis, Ernest Weingartner, Alfred Wiedensohler, and Paolo Laj
Atmos. Chem. Phys., 18, 7877–7911, https://doi.org/10.5194/acp-18-7877-2018, https://doi.org/10.5194/acp-18-7877-2018, 2018
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This investigation presents the variability in near-surface in situ aerosol particle light-scattering measurements obtained over the past decade at 28 measuring atmospheric observatories which are part of the ACTRIS Research Infrastructure, and most of them belong to the GAW network. This paper provides a comprehensive picture of the spatial and temporal variability of aerosol particles optical properties in Europe.
Francesca Di Giuseppe, Samuel Rémy, Florian Pappenberger, and Fredrik Wetterhall
Atmos. Chem. Phys., 18, 5359–5370, https://doi.org/10.5194/acp-18-5359-2018, https://doi.org/10.5194/acp-18-5359-2018, 2018
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Fire emissions injected into the atmosphere are crucial input for air quality models. This information is available globally using fire radiative power (FRP) observations, converted into smoke constituents. In case of a missing observation after ignition, a practical choice is to assume persistence. As an improvement we propose the use of the Canadian Fire Weather Index (FWI) to predict the FRP evolution. We show that the FWI is able to capture weather-related changes in fire activity well.
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
Bethan White, Edward Gryspeerdt, Philip Stier, Hugh Morrison, Gregory Thompson, and Zak Kipling
Atmos. Chem. Phys., 17, 12145–12175, https://doi.org/10.5194/acp-17-12145-2017, https://doi.org/10.5194/acp-17-12145-2017, 2017
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Aerosols influence cloud and precipitation by modifying cloud droplet number concentrations (CDNCs). We simulate three different types of convective cloud using two different cloud microphysics parameterisations. The simulated cloud and precipitation depends much more strongly on the choice of microphysics scheme than on CDNC. The uncertainty differs between types of convection. Our results highlight a large uncertainty in cloud and precipitation responses to aerosol in current models.
Samuel Rémy, Andreas Veira, Ronan Paugam, Mikhail Sofiev, Johannes W. Kaiser, Franco Marenco, Sharon P. Burton, Angela Benedetti, Richard J. Engelen, Richard Ferrare, and Jonathan W. Hair
Atmos. Chem. Phys., 17, 2921–2942, https://doi.org/10.5194/acp-17-2921-2017, https://doi.org/10.5194/acp-17-2921-2017, 2017
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Biomass burning emission injection heights are an important source of uncertainty in global climate and atmospheric composition modelling. This work provides a global daily data set of injection heights computed by two very different algorithms, which coherently complete a global biomass burning emissions database. The two data sets were compared and validated against observations, and their use was found to improve forecasts of carbonaceous aerosols in two case studies.
Johannes Flemming, Angela Benedetti, Antje Inness, Richard J. Engelen, Luke Jones, Vincent Huijnen, Samuel Remy, Mark Parrington, Martin Suttie, Alessio Bozzo, Vincent-Henri Peuch, Dimitris Akritidis, and Eleni Katragkou
Atmos. Chem. Phys., 17, 1945–1983, https://doi.org/10.5194/acp-17-1945-2017, https://doi.org/10.5194/acp-17-1945-2017, 2017
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We combine satellite observations of carbon monoxide, ozone and aerosols with the results from a model using a technique called data assimilation. The generated global data set (CAMS interim reanalysis) covers the period 2003–2015 at a resolution of about 110 km. The CAMS interim reanalysis can be used to study global air pollution and climate forcing of aerosol and stratospheric ozone. It has been produced by the Copernicus Atmosphere Monitoring Service (http://atmosphere. copernicus.eu).
Zak Kipling, Philip Stier, Laurent Labbouz, and Till Wagner
Atmos. Chem. Phys., 17, 327–342, https://doi.org/10.5194/acp-17-327-2017, https://doi.org/10.5194/acp-17-327-2017, 2017
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We present the first evaluation of the convective cloud field model (CCFM) in the context of a global climate model. CCFM attempts to address some of the shortcomings of commonly used representations of convection, in particular allowing for physically based aerosol effects on different types of convective cloud. We show that the model performs well overall in the context of the climate model and is thus well placed to study aerosol–convection–climate interactions at the global scale.
Duncan Watson-Parris, Nick Schutgens, Nicholas Cook, Zak Kipling, Philip Kershaw, Edward Gryspeerdt, Bryan Lawrence, and Philip Stier
Geosci. Model Dev., 9, 3093–3110, https://doi.org/10.5194/gmd-9-3093-2016, https://doi.org/10.5194/gmd-9-3093-2016, 2016
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In this paper we describe CIS, a new command line tool for the easy visualization, analysis and comparison of a wide variety of gridded and ungridded data sets used in Earth sciences. Users can now use a single tool to not only view plots of satellite, aircraft, station or model data, but also bring them onto the same spatio-temporal sampling. This allows robust, quantitative comparisons to be made easily. CIS is an open-source project and welcomes input from the community.
Wolfram Birmili, Kay Weinhold, Fabian Rasch, André Sonntag, Jia Sun, Maik Merkel, Alfred Wiedensohler, Susanne Bastian, Alexander Schladitz, Gunter Löschau, Josef Cyrys, Mike Pitz, Jianwei Gu, Thomas Kusch, Harald Flentje, Ulrich Quass, Heinz Kaminski, Thomas A. J. Kuhlbusch, Frank Meinhardt, Andreas Schwerin, Olaf Bath, Ludwig Ries, Holger Gerwig, Klaus Wirtz, and Markus Fiebig
Earth Syst. Sci. Data, 8, 355–382, https://doi.org/10.5194/essd-8-355-2016, https://doi.org/10.5194/essd-8-355-2016, 2016
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The German Ultrafine Aerosol Network (GUAN) provides new continuous data on tropospheric aerosol particles including number size distributions and black carbon. The data are equally relevant for atmospheric studies related to both climate-related and health-related issues. The published data underwent uniform measures of quality assurance and control. The data are available free of charge at the World Data Center for Aerosols EBAS data repository.
Ina Mattis, Giuseppe D'Amico, Holger Baars, Aldo Amodeo, Fabio Madonna, and Marco Iarlori
Atmos. Meas. Tech., 9, 3009–3029, https://doi.org/10.5194/amt-9-3009-2016, https://doi.org/10.5194/amt-9-3009-2016, 2016
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We present an automated software tool for the retrieval of profiles of optical particle properties from lidar signals. This tool is one of the modules of the Single Calculus Chain of the European Aerosol Research Lidar Network (EARLINET). It allows for the analysis of the data of many different lidar systems of EARLINET in an automated, unsupervised way.
Armin Geisinger, Andreas Behrendt, Volker Wulfmeyer, Jens Strohbach, Jochen Förstner, Roland Potthast, and Ina Mattis
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-609, https://doi.org/10.5194/acp-2016-609, 2016
Revised manuscript not accepted
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Hereby, we present a new backscatter lidar forward operator which allows for a quantitative comparison of atmospheric chemistry models and backscatter lidar measurements. We applied the operator on model predictions of the 2010 Eyjafjallajökull eruption where the model obviously overestimated the ash concentration. Uncertainties of the operator were minimized by applying averaging algorithms and performing sensitivity studies. Further steps towards quantitative model validation were identified.
Ronny Engelmann, Thomas Kanitz, Holger Baars, Birgit Heese, Dietrich Althausen, Annett Skupin, Ulla Wandinger, Mika Komppula, Iwona S. Stachlewska, Vassilis Amiridis, Eleni Marinou, Ina Mattis, Holger Linné, and Albert Ansmann
Atmos. Meas. Tech., 9, 1767–1784, https://doi.org/10.5194/amt-9-1767-2016, https://doi.org/10.5194/amt-9-1767-2016, 2016
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The atmospheric science community demands for autonomous and quality-assured vertically resolved measurements of aerosol and cloud properties. For this purpose, a portable lidar called Polly
was developed at TROPOS in 2003. This lidar type was continuously improved with gained experience from EARLINET, worldwide field campaigns, and institute collaborations within the last 10 years. We present recent changes to the setup of our portable multiwavelength Raman and polarization lidar PollyXT.
Holger Baars, Thomas Kanitz, Ronny Engelmann, Dietrich Althausen, Birgit Heese, Mika Komppula, Jana Preißler, Matthias Tesche, Albert Ansmann, Ulla Wandinger, Jae-Hyun Lim, Joon Young Ahn, Iwona S. Stachlewska, Vassilis Amiridis, Eleni Marinou, Patric Seifert, Julian Hofer, Annett Skupin, Florian Schneider, Stephanie Bohlmann, Andreas Foth, Sebastian Bley, Anne Pfüller, Eleni Giannakaki, Heikki Lihavainen, Yrjö Viisanen, Rakesh Kumar Hooda, Sérgio Nepomuceno Pereira, Daniele Bortoli, Frank Wagner, Ina Mattis, Lucja Janicka, Krzysztof M. Markowicz, Peggy Achtert, Paulo Artaxo, Theotonio Pauliquevis, Rodrigo A. F. Souza, Ved Prakesh Sharma, Pieter Gideon van Zyl, Johan Paul Beukes, Junying Sun, Erich G. Rohwer, Ruru Deng, Rodanthi-Elisavet Mamouri, and Felix Zamorano
Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, https://doi.org/10.5194/acp-16-5111-2016, 2016
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The findings from more than 10 years of global aerosol lidar measurements with Polly systems are summarized, and a data set of optical properties for specific aerosol types is given. An automated data retrieval algorithm for continuous Polly lidar observations is presented and discussed by means of a Saharan dust advection event in Leipzig, Germany. Finally, a statistic on the vertical aerosol distribution including the seasonal variability at PollyNET locations around the globe is presented.
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.
Ulla Wandinger, Volker Freudenthaler, Holger Baars, Aldo Amodeo, Ronny Engelmann, Ina Mattis, Silke Groß, Gelsomina Pappalardo, Aldo Giunta, Giuseppe D'Amico, Anatoli Chaikovsky, Fiodor Osipenko, Alexander Slesar, Doina Nicolae, Livio Belegante, Camelia Talianu, Ilya Serikov, Holger Linné, Friedhelm Jansen, Arnoud Apituley, Keith M. Wilson, Martin de Graaf, Thomas Trickl, Helmut Giehl, Mariana Adam, Adolfo Comerón, Constantino Muñoz-Porcar, Francesc Rocadenbosch, Michaël Sicard, Sergio Tomás, Diego Lange, Dhiraj Kumar, Manuel Pujadas, Francisco Molero, Alfonso J. Fernández, Lucas Alados-Arboledas, Juan Antonio Bravo-Aranda, Francisco Navas-Guzmán, Juan Luis Guerrero-Rascado, María José Granados-Muñoz, Jana Preißler, Frank Wagner, Michael Gausa, Ivan Grigorov, Dimitar Stoyanov, Marco Iarlori, Vincenco Rizi, Nicola Spinelli, Antonella Boselli, Xuan Wang, Teresa Lo Feudo, Maria Rita Perrone, Ferdinando De Tomasi, and Pasquale Burlizzi
Atmos. Meas. Tech., 9, 1001–1023, https://doi.org/10.5194/amt-9-1001-2016, https://doi.org/10.5194/amt-9-1001-2016, 2016
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We introduce the quality-assurance efforts of the European Aerosol Research Lidar Network (EARLINET) at instrument level. Within several campaigns, 21 EARLINET systems from 18 EARLINET stations were intercompared. A comprehensive strategy for campaign setup and data evaluation was established. The intercomparisons have reinforced our confidence in the EARLINET data quality and allowed us to draw conclusions on necessary system improvements and to identify major challenges for our future work.
Shipeng Zhang, Minghuai Wang, Steven J. Ghan, Aijun Ding, Hailong Wang, Kai Zhang, David Neubauer, Ulrike Lohmann, Sylvaine Ferrachat, Toshihiko Takeamura, Andrew Gettelman, Hugh Morrison, Yunha Lee, Drew T. Shindell, Daniel G. Partridge, Philip Stier, Zak Kipling, and Congbin Fu
Atmos. Chem. Phys., 16, 2765–2783, https://doi.org/10.5194/acp-16-2765-2016, https://doi.org/10.5194/acp-16-2765-2016, 2016
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The variation of aerosol indirect effects (AIE) in several climate models is investigated across different dynamical regimes. Regimes with strong large-scale ascent are shown to be as important as stratocumulus regimes in studying AIE. AIE over regions with high monthly large-scale surface precipitation rate contributes the most to the total aerosol indirect forcing. These results point to the need to reduce the uncertainty in AIE in different dynamical regimes.
Zak Kipling, Philip Stier, Colin E. Johnson, Graham W. Mann, Nicolas Bellouin, Susanne E. Bauer, Tommi Bergman, Mian Chin, Thomas Diehl, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Harri Kokkola, Xiaohong Liu, Gan Luo, Twan van Noije, Kirsty J. Pringle, Knut von Salzen, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Toshihiko Takemura, Kostas Tsigaridis, and Kai Zhang
Atmos. Chem. Phys., 16, 2221–2241, https://doi.org/10.5194/acp-16-2221-2016, https://doi.org/10.5194/acp-16-2221-2016, 2016
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The vertical distribution of atmospheric aerosol is an important factor in its effects on climate. In this study we use a sophisticated model of the many interacting processes affecting aerosol in the atmosphere to show that the vertical distribution is typically dominated by only a few of these processes. Constraining these physical processes may help to reduce the large differences between models. However, the important processes are not always the same for different types of aerosol.
Franco Marenco, Ben Johnson, Justin M. Langridge, Jane Mulcahy, Angela Benedetti, Samuel Remy, Luke Jones, Kate Szpek, Jim Haywood, Karla Longo, and Paulo Artaxo
Atmos. Chem. Phys., 16, 2155–2174, https://doi.org/10.5194/acp-16-2155-2016, https://doi.org/10.5194/acp-16-2155-2016, 2016
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A widespread and persistent smoke layer was observed in the Amazon
region during the biomass burning season, spanning a distance of 2200 km
and a period of 14 days. The larger smoke content was typically found
in elevated layers, from 1–1.5 km to 4–6 km.
Measurements have been compared to model predictions, and the latter
were able to reproduce the general features of the smoke layer, but
with some differences which are analysed and described in the paper.
Giuseppe D'Amico, Aldo Amodeo, Ina Mattis, Volker Freudenthaler, and Gelsomina Pappalardo
Atmos. Meas. Tech., 9, 491–507, https://doi.org/10.5194/amt-9-491-2016, https://doi.org/10.5194/amt-9-491-2016, 2016
A. Wagner, A.-M. Blechschmidt, I. Bouarar, E.-G. Brunke, C. Clerbaux, M. Cupeiro, P. Cristofanelli, H. Eskes, J. Flemming, H. Flentje, M. George, S. Gilge, A. Hilboll, A. Inness, J. Kapsomenakis, A. Richter, L. Ries, W. Spangl, O. Stein, R. Weller, and C. Zerefos
Atmos. Chem. Phys., 15, 14005–14030, https://doi.org/10.5194/acp-15-14005-2015, https://doi.org/10.5194/acp-15-14005-2015, 2015
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The Monitoring Atmospheric Composition and Climate project (MACC) operationally produces global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the model to simulate concentrations of reactive gases (carbon monoxide, nitrogen dioxide and ozone) between 2009 and 2012. The model reproduced reactive gas concentrations with consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations.
S. Rémy, A. Benedetti, A. Bozzo, T. Haiden, L. Jones, M. Razinger, J. Flemming, R. J. Engelen, V. H. Peuch, and J. N. Thepaut
Atmos. Chem. Phys., 15, 12909–12933, https://doi.org/10.5194/acp-15-12909-2015, https://doi.org/10.5194/acp-15-12909-2015, 2015
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In this paper we report on the feedbacks between dust and boundary layer meteorology during a dust storm over Egypt and Libya in April 2012, using an atmospheric composition forecasting system. Dust was found to act on atmospheric stability, leading to an increase (night) or a decrease (day) in dust production. Horizontal gradients of temperature were modified by the radiative impact of the dust layer, leading to changes in wind patterns at the edge of the storm due to the thermal wind effect.
G. D'Amico, A. Amodeo, H. Baars, I. Binietoglou, V. Freudenthaler, I. Mattis, U. Wandinger, and G. Pappalardo
Atmos. Meas. Tech., 8, 4891–4916, https://doi.org/10.5194/amt-8-4891-2015, https://doi.org/10.5194/amt-8-4891-2015, 2015
H. Eskes, V. Huijnen, A. Arola, A. Benedictow, A.-M. Blechschmidt, E. Botek, O. Boucher, I. Bouarar, S. Chabrillat, E. Cuevas, R. Engelen, H. Flentje, A. Gaudel, J. Griesfeller, L. Jones, J. Kapsomenakis, E. Katragkou, S. Kinne, B. Langerock, M. Razinger, A. Richter, M. Schultz, M. Schulz, N. Sudarchikova, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Geosci. Model Dev., 8, 3523–3543, https://doi.org/10.5194/gmd-8-3523-2015, https://doi.org/10.5194/gmd-8-3523-2015, 2015
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The MACC project is preparing the operational atmosphere service of the European Copernicus Programme, and uses data assimilation to combine atmospheric models with available observations. Our paper provides an overview of the aerosol and trace gas validation activity of MACC. Topics are the validation requirements, the measurement data, the assimilation systems, the upgrade procedure, operational aspects and the scoring methods. A summary is provided of recent results, including special events.
M. Sicard, G. D'Amico, A. Comerón, L. Mona, L. Alados-Arboledas, A. Amodeo, H. Baars, J. M. Baldasano, L. Belegante, I. Binietoglou, J. A. Bravo-Aranda, A. J. Fernández, P. Fréville, D. García-Vizcaíno, A. Giunta, M. J. Granados-Muñoz, J. L. Guerrero-Rascado, D. Hadjimitsis, A. Haefele, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, R. E. Mamouri, I. Mattis, F. Molero, N. Montoux, A. Muñoz, C. Muñoz Porcar, F. Navas-Guzmán, D. Nicolae, A. Nisantzi, N. Papagiannopoulos, A. Papayannis, S. Pereira, J. Preißler, M. Pujadas, V. Rizi, F. Rocadenbosch, K. Sellegri, V. Simeonov, G. Tsaknakis, F. Wagner, and G. Pappalardo
Atmos. Meas. Tech., 8, 4587–4613, https://doi.org/10.5194/amt-8-4587-2015, https://doi.org/10.5194/amt-8-4587-2015, 2015
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In the framework of the ACTRIS summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. The paper describes the measurement protocol and discusses the delivery of real-time and near-real-time lidar-derived products.
T. Trickl, H. Vogelmann, H. Flentje, and L. Ries
Atmos. Chem. Phys., 15, 9631–9649, https://doi.org/10.5194/acp-15-9631-2015, https://doi.org/10.5194/acp-15-9631-2015, 2015
A. Inness, A. Benedetti, J. Flemming, V. Huijnen, J. W. Kaiser, M. Parrington, and S. Remy
Atmos. Chem. Phys., 15, 9083–9097, https://doi.org/10.5194/acp-15-9083-2015, https://doi.org/10.5194/acp-15-9083-2015, 2015
E. Gryspeerdt, P. Stier, B. A. White, and Z. Kipling
Atmos. Chem. Phys., 15, 7557–7570, https://doi.org/10.5194/acp-15-7557-2015, https://doi.org/10.5194/acp-15-7557-2015, 2015
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Wet scavenging generates differences between the aerosol properties in clear-sky scenes (observed by satellites) and cloudy scenes, leading to different
aerosol-precipitation relationships in satellite data and global models. Convective systems usually draw in air from clear-sky regions, but global models have difficulty separating this aerosol from the aerosol in cloudy scenes within a model gridbox. This may prevent models from reproducing the observed aerosol-precipitation relationships.
S. Remy and J. W. Kaiser
Atmos. Chem. Phys., 14, 13377–13390, https://doi.org/10.5194/acp-14-13377-2014, https://doi.org/10.5194/acp-14-13377-2014, 2014
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This paper describes a method to correct the bias in daily fire radiative power (FRP) observations from any low Earth orbit satellite, so that that the budget of daily smoke emissions remains independent of the number of satellites from which FRP observations are taken into account. This ensures the possibility of running a system assimilating observations from several sensors, e.g. the Global Fire Assimilation System (GFAS), in case of failure of one of the MODIS instruments.
G. Pappalardo, A. Amodeo, A. Apituley, A. Comeron, V. Freudenthaler, H. Linné, A. Ansmann, J. Bösenberg, G. D'Amico, I. Mattis, L. Mona, U. Wandinger, V. Amiridis, L. Alados-Arboledas, D. Nicolae, and M. Wiegner
Atmos. Meas. Tech., 7, 2389–2409, https://doi.org/10.5194/amt-7-2389-2014, https://doi.org/10.5194/amt-7-2389-2014, 2014
M. Wiegner, F. Madonna, I. Binietoglou, R. Forkel, J. Gasteiger, A. Geiß, G. Pappalardo, K. Schäfer, and W. Thomas
Atmos. Meas. Tech., 7, 1979–1997, https://doi.org/10.5194/amt-7-1979-2014, https://doi.org/10.5194/amt-7-1979-2014, 2014
R. E. L. West, P. Stier, A. Jones, C. E. Johnson, G. W. Mann, N. Bellouin, D. G. Partridge, and Z. Kipling
Atmos. Chem. Phys., 14, 6369–6393, https://doi.org/10.5194/acp-14-6369-2014, https://doi.org/10.5194/acp-14-6369-2014, 2014
D. C. S. Beddows, M. Dall'Osto, R. M. Harrison, M. Kulmala, A. Asmi, A. Wiedensohler, P. Laj, A.M. Fjaeraa, K. Sellegri, W. Birmili, N. Bukowiecki, E. Weingartner, U. Baltensperger, V. Zdimal, N. Zikova, J.-P. Putaud, A. Marinoni, P. Tunved, H.-C. Hansson, M. Fiebig, N. Kivekäs, E. Swietlicki, H. Lihavainen, E. Asmi, V. Ulevicius, P. P. Aalto, N. Mihalopoulos, N. Kalivitis, I. Kalapov, G. Kiss, G. de Leeuw, B. Henzing, C. O'Dowd, S. G. Jennings, H. Flentje, F. Meinhardt, L. Ries, H. A. C. Denier van der Gon, and A. J. H. Visschedijk
Atmos. Chem. Phys., 14, 4327–4348, https://doi.org/10.5194/acp-14-4327-2014, https://doi.org/10.5194/acp-14-4327-2014, 2014
U. Schumann, R. Hempel, H. Flentje, M. Garhammer, K. Graf, S. Kox, H. Lösslein, and B. Mayer
Atmos. Meas. Tech., 6, 3597–3612, https://doi.org/10.5194/amt-6-3597-2013, https://doi.org/10.5194/amt-6-3597-2013, 2013
Z. Kipling, P. Stier, J. P. Schwarz, A. E. Perring, J. R. Spackman, G. W. Mann, C. E. Johnson, and P. J. Telford
Atmos. Chem. Phys., 13, 5969–5986, https://doi.org/10.5194/acp-13-5969-2013, https://doi.org/10.5194/acp-13-5969-2013, 2013
A. Asmi, M. Collaud Coen, J. A. Ogren, E. Andrews, P. Sheridan, A. Jefferson, E. Weingartner, U. Baltensperger, N. Bukowiecki, H. Lihavainen, N. Kivekäs, E. Asmi, P. P. Aalto, M. Kulmala, A. Wiedensohler, W. Birmili, A. Hamed, C. O'Dowd, S. G Jennings, R. Weller, H. Flentje, A. M. Fjaeraa, M. Fiebig, C. L. Myhre, A. G. Hallar, E. Swietlicki, A. Kristensson, and P. Laj
Atmos. Chem. Phys., 13, 895–916, https://doi.org/10.5194/acp-13-895-2013, https://doi.org/10.5194/acp-13-895-2013, 2013
M. Collaud Coen, E. Andrews, A. Asmi, U. Baltensperger, N. Bukowiecki, D. Day, M. Fiebig, A. M. Fjaeraa, H. Flentje, A. Hyvärinen, A. Jefferson, S. G. Jennings, G. Kouvarakis, H. Lihavainen, C. Lund Myhre, W. C. Malm, N. Mihapopoulos, J. V. Molenar, C. O'Dowd, J. A. Ogren, B. A. Schichtel, P. Sheridan, A. Virkkula, E. Weingartner, R. Weller, and P. Laj
Atmos. Chem. Phys., 13, 869–894, https://doi.org/10.5194/acp-13-869-2013, https://doi.org/10.5194/acp-13-869-2013, 2013
Related subject area
Atmospheric sciences
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
The ddeq Python library for point source quantification from remote sensing images (Version 1.0)
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
Investigating Ground-Level Ozone Pollution in Semi-Arid and Arid Regions of Arizona Using WRF-Chem v4.4 Modeling
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
FUME 2.0 – Flexible Universal processor for Modeling Emissions
Assessment of tropospheric ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Application of regional meteorology and air quality models based on MIPS CPU Platform
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Nathan Patrick Arnold
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-245, https://doi.org/10.5194/gmd-2023-245, 2024
Revised manuscript accepted for GMD
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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.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 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.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, 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.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 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 emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
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Short summary
Atmospheric aerosols crucially impact air quality, climate and weather. Thus, global model forecasts of atmospheric constituents are published daily on the ECMWF website and are regularly verified by the CAMS service team. The IFS-AER model is largely able to reproduce observed 3-D distributions of the important particle types over Germany. The particle concentration is mostly captured within several tens of percent, but quantification of some specific processes still remains a challenge.
Atmospheric aerosols crucially impact air quality, climate and weather. Thus, global model...
