Articles | Volume 10, issue 8
Geosci. Model Dev., 10, 2971–2999, 2017
https://doi.org/10.5194/gmd-10-2971-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Coupled chemistry–meteorology modelling: status and...
Geosci. Model Dev., 10, 2971–2999, 2017
https://doi.org/10.5194/gmd-10-2971-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper 08 Aug 2017
Model description paper | 08 Aug 2017
Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2)
Alexander Baklanov et al.
Related authors
Roman Nuterman, Alexander Mahura, Alexander Baklanov, Bjarne Amstrup, and Ashraf Zakey
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1308, https://doi.org/10.5194/acp-2020-1308, 2021
Revised manuscript under review for ACP
Short summary
Short summary
The street air pollution is usually higher than the pollution at regional and urban scales. It mostly associated with both local emission sources and urban weather conditions. We present the downscaling system for regional, sub-regional/urban and street scales and evaluate it for acute air-pollution episode. Its evaluation showed a good prediction score across various spatio-temporal scales as well as feasibility of deterministic modelling approach for the operational street scale forecasting.
Alexander Kurganskiy, Carsten Ambelas Skjøth, Alexander Baklanov, Mikhail Sofiev, Annika Saarto, Elena Severova, Sergei Smyshlyaev, and Eigil Kaas
Atmos. Chem. Phys., 20, 2099–2121, https://doi.org/10.5194/acp-20-2099-2020, https://doi.org/10.5194/acp-20-2099-2020, 2020
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The aim of the study was to evaluate three birch pollen source maps using a state-of-the-art atmospheric model Enviro-HIRLAM. Enviro-HIRLAM is a so-called online model where both weather and air pollution are calculated at all time steps.
The evaluation has been performed for 12 pollen observation sites located in Denmark, Finland, and Russia.
Mikhail Varentsov, Pavel Konstantinov, Alexander Baklanov, Igor Esau, Victoria Miles, and Richard Davy
Atmos. Chem. Phys., 18, 17573–17587, https://doi.org/10.5194/acp-18-17573-2018, https://doi.org/10.5194/acp-18-17573-2018, 2018
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This study reports on the urban heat island (UHI) in a typical Arctic city in winter. Using in situ observations, remote sensing data and modeling, we show that the urban temperature anomaly reaches up to 11 K with a mean value of 1.9 K. At least 50 % of this anomaly is caused by the UHI effect, driven mostly by heating. The rest is created by natural microclimatic variability over the hilly terrain. This is a strong argument in support of energy efficiency measures in the Arctic cities.
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.
Laura Palacios-Peña, Rocío Baró, Alexander Baklanov, Alessandra Balzarini, Dominik Brunner, Renate Forkel, Marcus Hirtl, Luka Honzak, José María López-Romero, Juan Pedro Montávez, Juan Luis Pérez, Guido Pirovano, Roberto San José, Wolfram Schröder, Johannes Werhahn, Ralf Wolke, Rahela Žabkar, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 18, 5021–5043, https://doi.org/10.5194/acp-18-5021-2018, https://doi.org/10.5194/acp-18-5021-2018, 2018
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Atmospheric aerosols modify the radiative budget of the Earth, and it is therefore mandatory to have an accurate representation of their optical properties for understanding their climatic role. This work therefore evaluates the skill in the representation of optical properties by different remote-sensing sensors and regional online coupled chemistry–climate models over Europe.
Rocío Baró, Laura Palacios-Peña, Alexander Baklanov, Alessandra Balzarini, Dominik Brunner, Renate Forkel, Marcus Hirtl, Luka Honzak, Juan Luis Pérez, Guido Pirovano, Roberto San José, Wolfram Schröder, Johannes Werhahn, Ralf Wolke, Rahela Žabkar, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 17, 9677–9696, https://doi.org/10.5194/acp-17-9677-2017, https://doi.org/10.5194/acp-17-9677-2017, 2017
Short summary
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The influence on modeled max., mean and min. temperature over Europe of including aerosol–radiation–cloud interactions has been assessed for two case studies in 2010. Data were taken from an ensemble of online regional chemistry–climate models from EuMetChem COST Action. The results indicate that including these interactions clearly improves the spatiotemporal variability in the temperature signal simulated by the models, with implications for reducing the uncertainty in climate projections.
Alexander Baklanov
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-1174, https://doi.org/10.5194/acp-2016-1174, 2017
Preprint retracted
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The article provides an introduction to the COST Action ES1004 – European framework for online integrated air quality and meteorology modelling (EuMetChem) – goals and outcomes for this Special Issue "Coupled chemistry–meteorology modelling: status and relevance for numerical weather prediction, air quality and climate communities" which collects key scientific papers of EuMetChem and its collaborators from different continents.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
M. Kulmala, H. K. Lappalainen, T. Petäjä, T. Kurten, V.-M. Kerminen, Y. Viisanen, P. Hari, S. Sorvari, J. Bäck, V. Bondur, N. Kasimov, V. Kotlyakov, G. Matvienko, A. Baklanov, H. D. Guo, A. Ding, H.-C. Hansson, and S. Zilitinkevich
Atmos. Chem. Phys., 15, 13085–13096, https://doi.org/10.5194/acp-15-13085-2015, https://doi.org/10.5194/acp-15-13085-2015, 2015
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The Pan-European Experiment (PEEX) is introduced. PEEX is a multidisciplinary, multiscale and multicomponent research, research infrastructure and capacity-building program. This paper outlines the mission, vision and objectives of PEEX and introduces its main components, including the research agenda, research infrastructure, knowledge transfer and potential impacts on society. The paper also summarizes the main scientific questions that PEEX is going to tackle in the future.
M. Beekmann, A. S. H. Prévôt, F. Drewnick, J. Sciare, S. N. Pandis, H. A. C. Denier van der Gon, M. Crippa, F. Freutel, L. Poulain, V. Ghersi, E. Rodriguez, S. Beirle, P. Zotter, S.-L. von der Weiden-Reinmüller, M. Bressi, C. Fountoukis, H. Petetin, S. Szidat, J. Schneider, A. Rosso, I. El Haddad, A. Megaritis, Q. J. Zhang, V. Michoud, J. G. Slowik, S. Moukhtar, P. Kolmonen, A. Stohl, S. Eckhardt, A. Borbon, V. Gros, N. Marchand, J. L. Jaffrezo, A. Schwarzenboeck, A. Colomb, A. Wiedensohler, S. Borrmann, M. Lawrence, A. Baklanov, and U. Baltensperger
Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, https://doi.org/10.5194/acp-15-9577-2015, 2015
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A detailed characterization of air quality in the Paris (France) agglomeration, a megacity, during two summer and winter intensive campaigns and from additional 1-year observations, revealed that about 70% of the fine particulate matter (PM) at urban background is transported into the megacity from upwind regions. Unexpectedly, a major part of organic PM is of modern origin (woodburning and cooking activities, secondary formation from biogenic VOC).
M. Bocquet, H. Elbern, H. Eskes, M. Hirtl, R. Žabkar, G. R. Carmichael, J. Flemming, A. Inness, M. Pagowski, J. L. Pérez Camaño, P. E. Saide, R. San Jose, M. Sofiev, J. Vira, A. Baklanov, C. Carnevale, G. Grell, and C. Seigneur
Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, https://doi.org/10.5194/acp-15-5325-2015, 2015
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Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of concentrations, and perform inverse modeling. Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. We review here the current status of data assimilation in atmospheric chemistry models, with a particular focus on future prospects for data assimilation in CCMM.
A. Baklanov, K. Schlünzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. S. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang
Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, https://doi.org/10.5194/acp-14-317-2014, 2014
Sissal Vágsheyg Erenbjerg, Jon Albretsen, Knud Simonsen, Erna Olsen, Eigil Kaas, and Bogi Hansen
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-23, https://doi.org/10.5194/os-2021-23, 2021
Preprint under review for OS
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Here, we describe an estuary that has narrow and shallow sills in both ends and is close to an amphidromic region. This generates tidally driven flows into and out of the estuary, but with very different exchange rates across the entrances in both ends so that the estuary behaves like a mixture between a sound and a fjord. Using a numerical model, we find a rather surprising fortnightly signal in the net transport through the estuary. Our findings are verified by observations.
Roman Nuterman, Alexander Mahura, Alexander Baklanov, Bjarne Amstrup, and Ashraf Zakey
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1308, https://doi.org/10.5194/acp-2020-1308, 2021
Revised manuscript under review for ACP
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The street air pollution is usually higher than the pollution at regional and urban scales. It mostly associated with both local emission sources and urban weather conditions. We present the downscaling system for regional, sub-regional/urban and street scales and evaluate it for acute air-pollution episode. Its evaluation showed a good prediction score across various spatio-temporal scales as well as feasibility of deterministic modelling approach for the operational street scale forecasting.
Tuukka Petäjä, Ella-Maria Duplissy, Ksenia Tabakova, Julia Schmale, Barbara Altstädter, Gerard Ancellet, Mikhail Arshinov, Yurii Balin, Urs Baltensperger, Jens Bange, Alison Beamish, Boris Belan, Antoine Berchet, Rossana Bossi, Warren R. L. Cairns, Ralf Ebinghaus, Imad El Haddad, Beatriz Ferreira-Araujo, Anna Franck, Lin Huang, Antti Hyvärinen, Angelika Humbert, Athina-Cerise Kalogridis, Pavel Konstantinov, Astrid Lampert, Matthew MacLeod, Olivier Magand, Alexander Mahura, Louis Marelle, Vladimir Masloboev, Dmitri Moisseev, Vaios Moschos, Niklas Neckel, Tatsuo Onishi, Stefan Osterwalder, Aino Ovaska, Pauli Paasonen, Mikhail Panchenko, Fidel Pankratov, Jakob B. Pernov, Andreas Platis, Olga Popovicheva, Jean-Christophe Raut, Aurélie Riandet, Torsten Sachs, Rosamaria Salvatori, Roberto Salzano, Ludwig Schröder, Martin Schön, Vladimir Shevchenko, Henrik Skov, Jeroen E. Sonke, Andrea Spolaor, Vasileios K. Stathopoulos, Mikko Strahlendorff, Jennie L. Thomas, Vito Vitale, Sterios Vratolis, Carlo Barbante, Sabine Chabrillat, Aurélien Dommergue, Konstantinos Eleftheriadis, Jyri Heilimo, Kathy S. Law, Andreas Massling, Steffen M. Noe, Jean-Daniel Paris, André S. H. Prévôt, Ilona Riipinen, Birgit Wehner, Zhiyong Xie, and Hanna K. Lappalainen
Atmos. Chem. Phys., 20, 8551–8592, https://doi.org/10.5194/acp-20-8551-2020, https://doi.org/10.5194/acp-20-8551-2020, 2020
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The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. Here we summarize initial results from our integrative project exploring the Arctic environment and pollution to deliver data products, metrics, and indicators for stakeholders.
Alexander Kurganskiy, Carsten Ambelas Skjøth, Alexander Baklanov, Mikhail Sofiev, Annika Saarto, Elena Severova, Sergei Smyshlyaev, and Eigil Kaas
Atmos. Chem. Phys., 20, 2099–2121, https://doi.org/10.5194/acp-20-2099-2020, https://doi.org/10.5194/acp-20-2099-2020, 2020
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The aim of the study was to evaluate three birch pollen source maps using a state-of-the-art atmospheric model Enviro-HIRLAM. Enviro-HIRLAM is a so-called online model where both weather and air pollution are calculated at all time steps.
The evaluation has been performed for 12 pollen observation sites located in Denmark, Finland, and Russia.
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Piątek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew P. Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New
Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019, https://doi.org/10.5194/gmd-12-4425-2019, 2019
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This paper presents an overview of the ESCAPE project. Dwarfs (key patterns in terms of computation and communication) are identified in weather prediction models. They are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain-specific languages. Different numerical techniques are compared in terms of energy efficiency and performance for a variety of computing technologies.
Fidel Pankratov, Alexander Mahura, Tuukka Petäjä, Valentin Popov, and Vladimir Masloboev
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1228, https://doi.org/10.5194/acp-2018-1228, 2018
Revised manuscript not accepted
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Analysis of long-term observations for atmospheric mercury in the Russian Arctic, considering inter-annual, seasonal and monthly variabilities is in focus. Linkage of elevated concentrations with volcanic eruptions in Iceland is explored. Results showed that active volcanoes can play a role of sources for increased mercury levels in the Northern Hemisphere due to long-range atmospheric transport of volcanic clouds towards the Arctic.
Mikhail Varentsov, Pavel Konstantinov, Alexander Baklanov, Igor Esau, Victoria Miles, and Richard Davy
Atmos. Chem. Phys., 18, 17573–17587, https://doi.org/10.5194/acp-18-17573-2018, https://doi.org/10.5194/acp-18-17573-2018, 2018
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This study reports on the urban heat island (UHI) in a typical Arctic city in winter. Using in situ observations, remote sensing data and modeling, we show that the urban temperature anomaly reaches up to 11 K with a mean value of 1.9 K. At least 50 % of this anomaly is caused by the UHI effect, driven mostly by heating. The rest is created by natural microclimatic variability over the hilly terrain. This is a strong argument in support of energy efficiency measures in the Arctic cities.
Dion Häfner, René Løwe Jacobsen, Carsten Eden, Mads R. B. Kristensen, Markus Jochum, Roman Nuterman, and Brian Vinter
Geosci. Model Dev., 11, 3299–3312, https://doi.org/10.5194/gmd-11-3299-2018, https://doi.org/10.5194/gmd-11-3299-2018, 2018
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Well-performing, easy-to-use ocean models are a central ingredient to further the understanding of our Earth and climate. Veros, the versatile ocean simulator, is the first full-blown ocean model entirely written in the high-level programming language Python. It is considerably more approachable than traditional Fortran models and leverages modern best practices; at the same time, thanks to the Bohrium framework, Veros is about half as fast as a reference implementation in Fortran 90.
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.
Laura Palacios-Peña, Rocío Baró, Alexander Baklanov, Alessandra Balzarini, Dominik Brunner, Renate Forkel, Marcus Hirtl, Luka Honzak, José María López-Romero, Juan Pedro Montávez, Juan Luis Pérez, Guido Pirovano, Roberto San José, Wolfram Schröder, Johannes Werhahn, Ralf Wolke, Rahela Žabkar, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 18, 5021–5043, https://doi.org/10.5194/acp-18-5021-2018, https://doi.org/10.5194/acp-18-5021-2018, 2018
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Atmospheric aerosols modify the radiative budget of the Earth, and it is therefore mandatory to have an accurate representation of their optical properties for understanding their climatic role. This work therefore evaluates the skill in the representation of optical properties by different remote-sensing sensors and regional online coupled chemistry–climate models over Europe.
Ruth Mottram, Kristian Pagh Nielsen, Emily Gleeson, and Xiaohua Yang
Adv. Sci. Res., 14, 323–334, https://doi.org/10.5194/asr-14-323-2017, https://doi.org/10.5194/asr-14-323-2017, 2017
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The HARMONIE weather forecasting model is used successfully in Greenland, but there are some problems over the ice sheet due to the lack of realistic glacier surface characteristics. By introducing a correction to the model, preventing glacier surface temperatures over 0 °C, we improve both 2 m air temperature and the surface winds (both strength and direction) forecast by the model.
We also identify other corrections needed before HARMONIE can be used for climate and ice sheet modelling.
Rocío Baró, Laura Palacios-Peña, Alexander Baklanov, Alessandra Balzarini, Dominik Brunner, Renate Forkel, Marcus Hirtl, Luka Honzak, Juan Luis Pérez, Guido Pirovano, Roberto San José, Wolfram Schröder, Johannes Werhahn, Ralf Wolke, Rahela Žabkar, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 17, 9677–9696, https://doi.org/10.5194/acp-17-9677-2017, https://doi.org/10.5194/acp-17-9677-2017, 2017
Short summary
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The influence on modeled max., mean and min. temperature over Europe of including aerosol–radiation–cloud interactions has been assessed for two case studies in 2010. Data were taken from an ensemble of online regional chemistry–climate models from EuMetChem COST Action. The results indicate that including these interactions clearly improves the spatiotemporal variability in the temperature signal simulated by the models, with implications for reducing the uncertainty in climate projections.
Bo Christiansen, Nis Jepsen, Rigel Kivi, Georg Hansen, Niels Larsen, and Ulrik Smith Korsholm
Atmos. Chem. Phys., 17, 9347–9364, https://doi.org/10.5194/acp-17-9347-2017, https://doi.org/10.5194/acp-17-9347-2017, 2017
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Ozone soundings in the troposphere from nine Arctic stations covering the period 1984–2014 have been analyzed. Stations with the best data coverage show a consistent and significant temporal variation with a maximum near 2005 followed by a decrease. Some significant changes are found in the annual cycle in agreement with the notion that the ozone summer maximum is appearing earlier in the year. Such changes in Arctic ozone in the free troposphere have not been reported before.
Laura Rontu, Emily Gleeson, Petri Räisänen, Kristian Pagh Nielsen, Hannu Savijärvi, and Bent Hansen Sass
Adv. Sci. Res., 14, 195–215, https://doi.org/10.5194/asr-14-195-2017, https://doi.org/10.5194/asr-14-195-2017, 2017
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This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the NWP model, without compromising on computational efficiency. Fast physically based radiation parametrizations are also valuable for high-resolution ensemble forecasting.
Alexander Baklanov
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-1174, https://doi.org/10.5194/acp-2016-1174, 2017
Preprint retracted
Short summary
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The article provides an introduction to the COST Action ES1004 – European framework for online integrated air quality and meteorology modelling (EuMetChem) – goals and outcomes for this Special Issue "Coupled chemistry–meteorology modelling: status and relevance for numerical weather prediction, air quality and climate communities" which collects key scientific papers of EuMetChem and its collaborators from different continents.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Emily Gleeson, Velle Toll, Kristian Pagh Nielsen, Laura Rontu, and Ján Mašek
Atmos. Chem. Phys., 16, 5933–5948, https://doi.org/10.5194/acp-16-5933-2016, https://doi.org/10.5194/acp-16-5933-2016, 2016
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The direct shortwave (SW) radiative effect of aerosols under clear-sky conditions in the ALADIN-HIRLAM numerical weather prediction system was investigated using three SW radiation schemes in diagnostic single-column experiments. Each scheme accurately simulates the direct SW effect when observed aerosols are used, particularly for heavy pollution scenarios.
M. Kulmala, H. K. Lappalainen, T. Petäjä, T. Kurten, V.-M. Kerminen, Y. Viisanen, P. Hari, S. Sorvari, J. Bäck, V. Bondur, N. Kasimov, V. Kotlyakov, G. Matvienko, A. Baklanov, H. D. Guo, A. Ding, H.-C. Hansson, and S. Zilitinkevich
Atmos. Chem. Phys., 15, 13085–13096, https://doi.org/10.5194/acp-15-13085-2015, https://doi.org/10.5194/acp-15-13085-2015, 2015
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The Pan-European Experiment (PEEX) is introduced. PEEX is a multidisciplinary, multiscale and multicomponent research, research infrastructure and capacity-building program. This paper outlines the mission, vision and objectives of PEEX and introduces its main components, including the research agenda, research infrastructure, knowledge transfer and potential impacts on society. The paper also summarizes the main scientific questions that PEEX is going to tackle in the future.
M. Beekmann, A. S. H. Prévôt, F. Drewnick, J. Sciare, S. N. Pandis, H. A. C. Denier van der Gon, M. Crippa, F. Freutel, L. Poulain, V. Ghersi, E. Rodriguez, S. Beirle, P. Zotter, S.-L. von der Weiden-Reinmüller, M. Bressi, C. Fountoukis, H. Petetin, S. Szidat, J. Schneider, A. Rosso, I. El Haddad, A. Megaritis, Q. J. Zhang, V. Michoud, J. G. Slowik, S. Moukhtar, P. Kolmonen, A. Stohl, S. Eckhardt, A. Borbon, V. Gros, N. Marchand, J. L. Jaffrezo, A. Schwarzenboeck, A. Colomb, A. Wiedensohler, S. Borrmann, M. Lawrence, A. Baklanov, and U. Baltensperger
Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, https://doi.org/10.5194/acp-15-9577-2015, 2015
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A detailed characterization of air quality in the Paris (France) agglomeration, a megacity, during two summer and winter intensive campaigns and from additional 1-year observations, revealed that about 70% of the fine particulate matter (PM) at urban background is transported into the megacity from upwind regions. Unexpectedly, a major part of organic PM is of modern origin (woodburning and cooking activities, secondary formation from biogenic VOC).
M. Bocquet, H. Elbern, H. Eskes, M. Hirtl, R. Žabkar, G. R. Carmichael, J. Flemming, A. Inness, M. Pagowski, J. L. Pérez Camaño, P. E. Saide, R. San Jose, M. Sofiev, J. Vira, A. Baklanov, C. Carnevale, G. Grell, and C. Seigneur
Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, https://doi.org/10.5194/acp-15-5325-2015, 2015
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Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of concentrations, and perform inverse modeling. Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. We review here the current status of data assimilation in atmospheric chemistry models, with a particular focus on future prospects for data assimilation in CCMM.
K. P. Nielsen, E. Gleeson, and L. Rontu
Geosci. Model Dev., 7, 1433–1449, https://doi.org/10.5194/gmd-7-1433-2014, https://doi.org/10.5194/gmd-7-1433-2014, 2014
P. H. Lauritzen, P. A. Ullrich, C. Jablonowski, P. A. Bosler, D. Calhoun, A. J. Conley, T. Enomoto, L. Dong, S. Dubey, O. Guba, A. B. Hansen, E. Kaas, J. Kent, J.-F. Lamarque, M. J. Prather, D. Reinert, V. V. Shashkin, W. C. Skamarock, B. Sørensen, M. A. Taylor, and M. A. Tolstykh
Geosci. Model Dev., 7, 105–145, https://doi.org/10.5194/gmd-7-105-2014, https://doi.org/10.5194/gmd-7-105-2014, 2014
A. Baklanov, K. Schlünzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. S. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang
Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, https://doi.org/10.5194/acp-14-317-2014, 2014
E. Kaas, B. Sørensen, P. H. Lauritzen, and A. B. Hansen
Geosci. Model Dev., 6, 2023–2047, https://doi.org/10.5194/gmd-6-2023-2013, https://doi.org/10.5194/gmd-6-2023-2013, 2013
B. Sørensen, E. Kaas, and U. S. Korsholm
Geosci. Model Dev., 6, 1029–1042, https://doi.org/10.5194/gmd-6-1029-2013, https://doi.org/10.5194/gmd-6-1029-2013, 2013
Related subject area
Atmospheric sciences
The Environment and Climate Change Canada Carbon Assimilation System (EC-CAS v1.0): demonstration with simulated CO observations
WRF4PALM v1.0: a mesoscale dynamical driver for the microscale PALM model system 6.0
pyPI (v1.3): Tropical Cyclone Potential Intensity Calculations in Python
Comparison of three aerosol representations of NHM-Chem (v1.0) for the simulations of air quality and climate-relevant variables
JlBox v1.1: a Julia-based multi-phase atmospheric chemistry box model
A new Lagrangian in-time particle simulation module (Itpas v1) for atmospheric particle dispersion
Effects of black carbon morphology on brown carbon absorption estimation: from numerical aspects
Simulation of the evolution of biomass burning organic aerosol with different volatility basis set schemes in PMCAMx-SRv1.0
Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0
Evaluation of ECMWF IFS-AER (CAMS) operational forecasts during cycle 41r1–46r1 with calibrated ceilometer profiles over Germany
Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50
Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates
MLAir (v1.0) – a tool to enable fast and flexible machine learning on air data time series
snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation
Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya
On the suitability of second-order accurate finite-volume solvers for the simulation of atmospheric boundary layer flow
An urban large-eddy-simulation-based dispersion model for marginal grid resolutions: CAIRDIO v1.0
Applying a new integrated mass-flux adjustment filter in rapid update cycling of convective-scale data assimilation for the COSMO model (v5.07)
On the model uncertainties in Bayesian source reconstruction using an ensemble of weather predictions, the emission inverse modelling system FREAR v1.0, and the Lagrangian transport and dispersion model Flexpart v9.0.2
Evaluation of the interactive stratospheric ozone (O3v2) module in the E3SM version 1 Earth system model
Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications
The Vertical City Weather Generator (VCWG v1.3.2)
A new gas absorption optical depth parameterisation for RTTOV v13
A zero-dimensional view of atmospheric degradation of levoglucosan (LEVCHEM_v1) using numerical chamber simulations
The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates
Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1
Development of WRF/CUACE v1.0 model and its preliminary application in simulating air quality in China
PyCHAM (v2.1.1): a Python box model for simulating aerosol chambers
A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54
Improving dust simulations in WRF-Chem v4.1.3 coupled with the GOCART aerosol module
FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 2: Model validation
Implementation of a synthetic inflow turbulence generator in idealised WRF v3.6.1 large eddy simulations under neutral atmospheric conditions
Numerical study of the effects of initial conditions and emissions on PM2.5 concentration simulations with CAMx v6.1: a Xi'an case study
A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales
Ground-based lidar processing and simulator framework for comparing models and observations (ALCF 1.0)
Development of an Ozone Monitoring Instrument (OMI) aerosol index (AI) data assimilation scheme for aerosol modeling over bright surfaces – a step toward direct radiance assimilation in the UV spectrum
IntelliO3-ts v1.0: a neural network approach to predict near-surface ozone concentrations in Germany
Development and evaluation of spectral nudging strategy for the simulation of summer precipitation over the Tibetan Plateau
ISBA-MEB (SURFEX v8.1): model snow evaluation for local-scale forest sites
Evaluating and improving the treatment of gases in radiation schemes: the Correlated K-Distribution Model Intercomparison Project (CKDMIP)
A case study of wind farm effects using two wake parameterizations in WRF (V3.7) in the presence of low level jets
GenChem v1.0 – a chemical pre-processing and testing system for atmospheric modelling
The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) Modeling System version 5.3
Incoming data quality control in high-resolution urban climate simulations: a Hong Kong–Shenzhen area urban climate simulation as a case study using the WRF/Noah LSM/SLUCM model (Version 3.7.1)
Configuration and evaluation of a global unstructured mesh atmospheric model (GRIST-A20.9) based on the variable-resolution approach
Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model
Development of a three-dimensional variational assimilation system for lidar profile data based on a size-resolved aerosol model in WRF–Chem model v3.9.1 and its application in PM2.5 forecasts across China
Using wavelet transform and dynamic time warping to identify the limitations of the CNN model as an air quality forecasting system
In-cloud scavenging scheme for sectional aerosol modules – implementation in the framework of the Sectional Aerosol module for Large Scale Applications version 2.0 (SALSA2.0) global aerosol module
APFoam-1.0: integrated CFD simulation of O3–NOx–VOCs chemistry and pollutant dispersion in typical street canyon
Vikram Khade, Saroja M. Polavarapu, Michael Neish, Pieter L. Houtekamer, Dylan B. A. Jones, Seung-Jong Baek, Tai-Long He, and Sylvie Gravel
Geosci. Model Dev., 14, 2525–2544, https://doi.org/10.5194/gmd-14-2525-2021, https://doi.org/10.5194/gmd-14-2525-2021, 2021
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A new modeling system has been developed at Environment and Climate Change Canada to ingest observations of carbon monoxide (CO) into a coupled weather and constituent transport model. We show that accounting for the uncertainty in surface flux leads to a better estimate of CO distributions. The benefit of assimilating observations from different simulated networks varies with region. This is the first step towards developing a state and flux estimation system for greenhouse gases.
Dongqi Lin, Basit Khan, Marwan Katurji, Leroy Bird, Ricardo Faria, and Laura E. Revell
Geosci. Model Dev., 14, 2503–2524, https://doi.org/10.5194/gmd-14-2503-2021, https://doi.org/10.5194/gmd-14-2503-2021, 2021
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We present an open-source toolbox WRF4PALM, which enables weather dynamics simulation within urban landscapes. WRF4PALM passes meteorological information from the popular Weather Research and Forecasting (WRF) model to the turbulence-resolving PALM model system 6.0. WRF4PALM can potentially extend the use of WRF and PALM with realistic boundary conditions to any part of the world. WRF4PALM will help study air pollution dispersion, wind energy prospecting, and high-impact wind forecasting.
Daniel M. Gilford
Geosci. Model Dev., 14, 2351–2369, https://doi.org/10.5194/gmd-14-2351-2021, https://doi.org/10.5194/gmd-14-2351-2021, 2021
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Potential intensity (PI) is a tropical cyclone's maximum speed limit given by modeling the storm as a thermal heat engine. pyPI is the first software package fully documenting the PI algorithm and translating it to Python. This study details/validates the underlying PI model and demonstrates its use in tropical cyclone intensity research. pyPI supports open science and transparency in the tropical meteorological community and is ideally suited for ongoing community development and improvement.
Mizuo Kajino, Makoto Deushi, Tsuyoshi Thomas Sekiyama, Naga Oshima, Keiya Yumimoto, Taichu Yasumichi Tanaka, Joseph Ching, Akihiro Hashimoto, Tetsuya Yamamoto, Masaaki Ikegami, Akane Kamada, Makoto Miyashita, Yayoi Inomata, Shin-ichiro Shima, Pradeep Khatri, Atsushi Shimizu, Hitoshi Irie, Kouji Adachi, Yuji Zaizen, Yasuhito Igarashi, Hiromasa Ueda, Takashi Maki, and Masao Mikami
Geosci. Model Dev., 14, 2235–2264, https://doi.org/10.5194/gmd-14-2235-2021, https://doi.org/10.5194/gmd-14-2235-2021, 2021
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This study compares performance of aerosol representation methods of the Japan Meteorological Agency's regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). It indicates separate treatment of sea salt and dust in coarse mode and that of light-absorptive and non-absorptive particles in fine mode could provide accurate assessments on aerosol feedback processes.
Langwen Huang and David Topping
Geosci. Model Dev., 14, 2187–2203, https://doi.org/10.5194/gmd-14-2187-2021, https://doi.org/10.5194/gmd-14-2187-2021, 2021
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As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. With this in mind we present JlBox v1.1, written in Julia.
Matthias Faust, Ralf Wolke, Steffen Münch, Roger Funk, and Kerstin Schepanski
Geosci. Model Dev., 14, 2205–2220, https://doi.org/10.5194/gmd-14-2205-2021, https://doi.org/10.5194/gmd-14-2205-2021, 2021
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Trajectory dispersion models are powerful and intuitive tools for tracing air pollution through the atmosphere. But the turbulent nature of the atmospheric boundary layer makes it challenging to provide accurate predictions near the surface. To overcome this, we propose an approach using wind and turbulence information at high temporal resolution. Finally, we demonstrate the strength of our approach in a case study on dust emissions from agriculture.
Jie Luo, Yongming Zhang, and Qixing Zhang
Geosci. Model Dev., 14, 2113–2126, https://doi.org/10.5194/gmd-14-2113-2021, https://doi.org/10.5194/gmd-14-2113-2021, 2021
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In this work, we developed a numerical method to investigate the effects of black carbon (BC) morphology on the estimation of brown carbon (BrC) absorption using the absorption Ångström exponent (AAE) method. We found that BC morphologies have significant impacts on the estimated BrC absorptions. Moreover, we have demonstrated under what conditions the AAE methods can provide good or bad estimations and explored the reasons for why the good or bad estimations were caused.
Georgia N. Theodoritsi, Giancarlo Ciarelli, and Spyros N. Pandis
Geosci. Model Dev., 14, 2041–2055, https://doi.org/10.5194/gmd-14-2041-2021, https://doi.org/10.5194/gmd-14-2041-2021, 2021
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Two schemes based on the volatility basis set were used for the simulation of biomass burning organic aerosol (bbOA) in the continental US. The first is the default scheme of the PMCAMx-SR model, and the second is a recently developed scheme based on laboratory experiments. The alternative bbOA scheme predicts much higher concentrations. The default scheme performed better during summer and fall, while the alternative scheme was a little better during spring.
Dana L. McGuffin, Yuanlong Huang, Richard C. Flagan, Tuukka Petäjä, B. Erik Ydstie, and Peter J. Adams
Geosci. Model Dev., 14, 1821–1839, https://doi.org/10.5194/gmd-14-1821-2021, https://doi.org/10.5194/gmd-14-1821-2021, 2021
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Atmospheric particle formation, emissions, and growth process rates are significant sources of uncertainty in predicting climate change. We aim to reduce that uncertainty by using measurements from several ground-based sites across Europe. We developed an estimation technique to adapt the governing process rates so model–measurement bias decays. The estimation framework developed has potential to improve model predictions while providing insight into the underlying atmospheric particle physics.
Harald Flentje, Ina Mattis, Zak Kipling, Samuel Rémy, and Werner Thomas
Geosci. Model Dev., 14, 1721–1751, https://doi.org/10.5194/gmd-14-1721-2021, https://doi.org/10.5194/gmd-14-1721-2021, 2021
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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.
Jianhui Jiang, Imad El Haddad, Sebnem Aksoyoglu, Giulia Stefenelli, Amelie Bertrand, Nicolas Marchand, Francesco Canonaco, Jean-Eudes Petit, Olivier Favez, Stefania Gilardoni, Urs Baltensperger, and André S. H. Prévôt
Geosci. Model Dev., 14, 1681–1697, https://doi.org/10.5194/gmd-14-1681-2021, https://doi.org/10.5194/gmd-14-1681-2021, 2021
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We developed a box model with a volatility basis set to simulate organic aerosol (OA) from biomass burning and optimized the vapor-wall-loss-corrected OA yields with a genetic algorithm. The optimized parameterizations were then implemented in the air quality model CAMx v6.5. Comparisons with ambient measurements indicate that the vapor-wall-loss-corrected parameterization effectively improves the model performance in predicting OA, which reduced the mean fractional bias from −72.9 % to −1.6 %.
Oliver Branch, Thomas Schwitalla, Marouane Temimi, Ricardo Fonseca, Narendra Nelli, Michael Weston, Josipa Milovac, and Volker Wulfmeyer
Geosci. Model Dev., 14, 1615–1637, https://doi.org/10.5194/gmd-14-1615-2021, https://doi.org/10.5194/gmd-14-1615-2021, 2021
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Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates where extreme events like heat waves, flash floods, and dust storms are becoming more severe. This study employs a high-resolution simulation with the WRF-NOAHMP model, and the output is compared with seasonal observation data from 50 weather stations. This type of verification is vital to identify model deficiencies and improve forecasting systems for arid regions.
Lukas Hubert Leufen, Felix Kleinert, and Martin G. Schultz
Geosci. Model Dev., 14, 1553–1574, https://doi.org/10.5194/gmd-14-1553-2021, https://doi.org/10.5194/gmd-14-1553-2021, 2021
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MLAir provides a coherent end-to-end structure for a typical time series analysis workflow using machine learning (ML). MLAir is adaptable to a wide range of ML use cases, focusing in particular on deep learning. The user has a free hand with the ML model itself and can select from different methods during preprocessing, training, and postprocessing. MLAir offers tools to track the experiment conduction, documents necessary ML parameters, and creates a variety of publication-ready plots.
Davide Ori, Leonie von Terzi, Markus Karrer, and Stefan Kneifel
Geosci. Model Dev., 14, 1511–1531, https://doi.org/10.5194/gmd-14-1511-2021, https://doi.org/10.5194/gmd-14-1511-2021, 2021
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Snowflakes have very complex shapes, and modeling their properties requires vast computing power. We produced a large number of realistic snowflakes and modeled their average properties by leveraging their fractal structure. Our approach allows modeling the properties of big ensembles of snowflakes, taking into account their natural variability, at a much lower cost. This enables the usage of remote sensing instruments, such as radars, to monitor the evolution of clouds and precipitation.
Jaydeep Singh, Narendra Singh, Narendra Ojha, Amit Sharma, Andrea Pozzer, Nadimpally Kiran Kumar, Kunjukrishnapillai Rajeev, Sachin S. Gunthe, and V. Rao Kotamarthi
Geosci. Model Dev., 14, 1427–1443, https://doi.org/10.5194/gmd-14-1427-2021, https://doi.org/10.5194/gmd-14-1427-2021, 2021
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Atmospheric models often have limitations in simulating the geographically complex and climatically important central Himalayan region. In this direction, we have performed regional modeling at high resolutions to improve the simulation of meteorology and dynamics through a better representation of the topography. The study has implications for further model applications to investigate the effects of anthropogenic pressure over the Himalaya.
Beatrice Giacomini and Marco G. Giometto
Geosci. Model Dev., 14, 1409–1426, https://doi.org/10.5194/gmd-14-1409-2021, https://doi.org/10.5194/gmd-14-1409-2021, 2021
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The present work evaluates the suitability of an important class of second-order finite-volume solvers for the large-eddy simulation of atmospheric boundary- layer flows. Results show that these solvers do not capture the dominant mechanisms responsible for momentum transport in boundary layers, leading to a misprediction of relevant flow statistics and to an enhanced sensitivity of the solution to variations in grid resolution.
Michael Weger, Oswald Knoth, and Bernd Heinold
Geosci. Model Dev., 14, 1469–1492, https://doi.org/10.5194/gmd-14-1469-2021, https://doi.org/10.5194/gmd-14-1469-2021, 2021
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A new numerical air-quality transport model for cities is presented, in which buildings are described diffusively. The used diffusive-obstacles approach helps to reduce the computational costs for high-resolution simulations as the grid spacing can be more coarse than in traditional approaches. The research which led to this model development was primarily motivated by the need for a computationally feasible downscaling tool for urban wind and pollution fields from meteorological model output.
Yuefei Zeng, Alberto de Lozar, Tijana Janjic, and Axel Seifert
Geosci. Model Dev., 14, 1295–1307, https://doi.org/10.5194/gmd-14-1295-2021, https://doi.org/10.5194/gmd-14-1295-2021, 2021
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A new integrated mass-flux adjustment filter is introduced and examined with an idealized setup for convective-scale radar data assimilation. It is found that the new filter slightly reduces the accuracy of background and analysis states; however, it preserves the main structure of cold pools and primary mesocyclone properties of supercells. More importantly, it successfully diminishes the imbalance in the analysis considerably and improves the forecasts.
Pieter De Meutter, Ian Hoffman, and Kurt Ungar
Geosci. Model Dev., 14, 1237–1252, https://doi.org/10.5194/gmd-14-1237-2021, https://doi.org/10.5194/gmd-14-1237-2021, 2021
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Inverse atmospheric transport modelling is an important tool in several disciplines. However, the specification of atmospheric transport model error remains challenging. In this paper, we employ a state-of-the-art ensemble technique combined with a state-of-the-art Bayesian inference algorithm to infer point sources. Our research helps to fill the gap in our understanding of model error in the context of inverse atmospheric transport modelling.
Qi Tang, Michael J. Prather, Juno Hsu, Daniel J. Ruiz, Philip J. Cameron-Smith, Shaocheng Xie, and Jean-Christophe Golaz
Geosci. Model Dev., 14, 1219–1236, https://doi.org/10.5194/gmd-14-1219-2021, https://doi.org/10.5194/gmd-14-1219-2021, 2021
Basit Khan, Sabine Banzhaf, Edward C. Chan, Renate Forkel, Farah Kanani-Sühring, Klaus Ketelsen, Mona Kurppa, Björn Maronga, Matthias Mauder, Siegfried Raasch, Emmanuele Russo, Martijn Schaap, and Matthias Sühring
Geosci. Model Dev., 14, 1171–1193, https://doi.org/10.5194/gmd-14-1171-2021, https://doi.org/10.5194/gmd-14-1171-2021, 2021
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An atmospheric chemistry model has been implemented in the microscale PALM model system 6.0. This article provides a detailed description of the model, its structure, input requirements, various features and limitations. Several pre-compiled ready-to-use chemical mechanisms are included in the chemistry model code; however, users can also easily implement other mechanisms. A case study is presented to demonstrate the application of the new chemistry model in the urban environment.
Mohsen Moradi, Benjamin Dyer, Amir Nazem, Manoj K. Nambiar, M. Rafsan Nahian, Bruno Bueno, Chris Mackey, Saeran Vasanthakumar, Negin Nazarian, E. Scott Krayenhoff, Leslie K. Norford, and Amir A. Aliabadi
Geosci. Model Dev., 14, 961–984, https://doi.org/10.5194/gmd-14-961-2021, https://doi.org/10.5194/gmd-14-961-2021, 2021
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The Vertical City Weather Generator (VCWG) is an urban microclimate model developed to predict temporal and vertical variation of potential temperature, wind speed, and specific humidity. VCWG is forced by climate variables at a nearby rural site and coupled to radiation and building energy models. VCWG is evaluated against field observations of the BUBBLE campaign. It is run under exploration mode to assess its performance given urban characteristics, seasonal variations, and climate zones.
James Hocking, Jérôme Vidot, Pascal Brunel, Pascale Roquet, Bruna Silveira, Emma Turner, and Cristina Lupu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-424, https://doi.org/10.5194/gmd-2020-424, 2021
Revised manuscript accepted for GMD
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RTTOV is a fast radiative transfer model for simulating passive satellite-based observations at visible, infra-red and microwave wavelengths. A core part of the model is a parameterisation of the absorption of radiation by the various gases present in the atmosphere. We present a new parameterisation that performs well compared to the existing one in terms of accuracy and can be developed further more easily. The new parameterisation is implemented in the latest release, RTTOV v13.0.
Loredana G. Suciu, Robert J. Griffin, and Caroline A. Masiello
Geosci. Model Dev., 14, 907–921, https://doi.org/10.5194/gmd-14-907-2021, https://doi.org/10.5194/gmd-14-907-2021, 2021
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Understanding the atmospheric degradation of biomass burning tracers such as levoglucosan is essential to decreasing uncertainties in the role of biomass burning in air quality, carbon cycling and paleoclimate. Using a 0-D modeling approach and numerical chamber simulations, we found that the multiphase atmospheric degradation of levoglucosan occurs over timescales of hours to days, can form secondary organic aerosols and affects other key tropospheric gases, such as ozone.
Chihiro Kodama, Tomoki Ohno, Tatsuya Seiki, Hisashi Yashiro, Akira T. Noda, Masuo Nakano, Yohei Yamada, Woosub Roh, Masaki Satoh, Tomoko Nitta, Daisuke Goto, Hiroaki Miura, Tomoe Nasuno, Tomoki Miyakawa, Ying-Wen Chen, and Masato Sugi
Geosci. Model Dev., 14, 795–820, https://doi.org/10.5194/gmd-14-795-2021, https://doi.org/10.5194/gmd-14-795-2021, 2021
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This paper describes the latest stable version of NICAM, a global atmospheric model, developed for high-resolution climate simulations toward the IPCC Assessment Report. Our model explicitly treats convection, clouds, and precipitation and could reduce the uncertainty of climate change projection. A series of test simulations demonstrated improvements (e.g., high cloud) and issues (e.g., low cloud, precipitation pattern), suggesting further necessity for model improvement and higher resolutions.
Jingyu Wang, Jiwen Fan, Robert A. Houze Jr., Stella R. Brodzik, Kai Zhang, Guang J. Zhang, and Po-Lun Ma
Geosci. Model Dev., 14, 719–734, https://doi.org/10.5194/gmd-14-719-2021, https://doi.org/10.5194/gmd-14-719-2021, 2021
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This paper presents an evaluation of the E3SM model against NEXRAD radar observations for the warm seasons during 2014–2016. The COSP forward simulator package is implemented in the model to generate radar reflectivity, and the NEXRAD observations are coarsened to the model resolution for comparison. The model severely underestimates the reflectivity above 4 km. Sensitivity tests on the parameters from cumulus parameterization and cloud microphysics do not improve this model bias.
Lei Zhang, Sunling Gong, Tianliang Zhao, Chunhong Zhou, Yuesi Wang, Jiawei Li, Dongsheng Ji, Jianjun He, Hongli Liu, Ke Gui, Xiaomei Guo, Jinhui Gao, Yunpeng Shan, Hong Wang, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 14, 703–718, https://doi.org/10.5194/gmd-14-703-2021, https://doi.org/10.5194/gmd-14-703-2021, 2021
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Development of chemical transport models with advanced physics and chemical schemes is important for improving air-quality forecasts. This study develops the chemical module CUACE by updating with a new particle dry deposition scheme and adding heterogenous chemical reactions and couples it with the WRF model. The coupled model (WRF/CUACE) was able to capture well the variations of PM2.5, O3, NO2, and secondary inorganic aerosols in eastern China.
Simon Patrick O'Meara, Shuxuan Xu, David Topping, M. Rami Alfarra, Gerard Capes, Douglas Lowe, Yunqi Shao, and Gordon McFiggans
Geosci. Model Dev., 14, 675–702, https://doi.org/10.5194/gmd-14-675-2021, https://doi.org/10.5194/gmd-14-675-2021, 2021
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User-friendly and open-source software for simulating aerosol chambers is a valuable tool for research scientists in designing and analysing their experiments. This paper describes a new version of such software and will therefore provide a useful reference for those applying it. Central to the paper is an assessment of the software's accuracy through comparison against previously published simulations.
Tamara Emmerichs, Astrid Kerkweg, Huug Ouwersloot, Silvano Fares, Ivan Mammarella, and Domenico Taraborrelli
Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021, https://doi.org/10.5194/gmd-14-495-2021, 2021
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Dry deposition to vegetation is a major sink of ground-level ozone. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for global tropospheric ozone. We extended the current model parameterization with a relevant pathway and important meteorological adjustment factors. The comparison with measurements shows that this enables a more realistic model representation of ozone dry deposition velocity. Globally, annual dry deposition loss increases.
Alexander Ukhov, Ravan Ahmadov, Georg Grell, and Georgiy Stenchikov
Geosci. Model Dev., 14, 473–493, https://doi.org/10.5194/gmd-14-473-2021, https://doi.org/10.5194/gmd-14-473-2021, 2021
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We discuss and evaluate the effects of inconsistencies found in the WRF-Chem code when using the GOCART module. First, PM surface concentrations were miscalculated. Second, dust optical depth was underestimated by 25 %–30 %. Third, an inconsistency in the process of gravitational settling led to the overestimation of dust column loadings by 4 %–6 %, PM10 by 2 %–4 %, and the rate of gravitational dust settling by 5 %–10 %. We also presented diagnostics that can be used to estimate these effects.
Andrew T. Prata, Leonardo Mingari, Arnau Folch, Giovanni Macedonio, and Antonio Costa
Geosci. Model Dev., 14, 409–436, https://doi.org/10.5194/gmd-14-409-2021, https://doi.org/10.5194/gmd-14-409-2021, 2021
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This paper presents FALL3D-8.0, the latest version release of an open-source code with a track record of 15+ years and a growing number of users in the volcanological and atmospheric communities. The code, originally conceived for atmospheric dispersal and deposition of tephra particles, has been extended to model other types of particles, aerosols and radionuclides. This paper details new model applications and validation of FALL3D-8.0 using satellite, ground-deposit load and radionuclide data.
Jian Zhong, Xiaoming Cai, and Zheng-Tong Xie
Geosci. Model Dev., 14, 323–336, https://doi.org/10.5194/gmd-14-323-2021, https://doi.org/10.5194/gmd-14-323-2021, 2021
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A synthetic inflow turbulence generator was implemented in the idealised Weather Research and Forecasting large eddy simulation. The inflow case yielded a mean velocity profile and second-moment profiles that agreed well with those generated using periodic boundary conditions, after a short adjustment distance. This implementation can be extended to a multi-scale seamless nesting simulation from a meso-scale domain with a kilometre-scale resolution to LES domains with metre-scale resolutions.
Han Xiao, Qizhong Wu, Xiaochun Yang, Lanning Wang, and Huaqiong Cheng
Geosci. Model Dev., 14, 223–238, https://doi.org/10.5194/gmd-14-223-2021, https://doi.org/10.5194/gmd-14-223-2021, 2021
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Few studies have investigated the effects of initial conditions on the simulation or prediction of PM2.5 concentrations. Here, sensitivity experiments are used to explore the effects of three initial mechanisms (clean, restart, and continuous) and emissions in Xi’an in December 2016. According to this work, if the restart mechanism cannot be used due to computing resource and storage space limitations when forecasting PM2.5 concentrations, a spin-up time of at least 27 h is needed.
Hsi-Yen Ma, Chen Zhou, Yunyan Zhang, Stephen A. Klein, Mark D. Zelinka, Xue Zheng, Shaocheng Xie, Wei-Ting Chen, and Chien-Ming Wu
Geosci. Model Dev., 14, 73–90, https://doi.org/10.5194/gmd-14-73-2021, https://doi.org/10.5194/gmd-14-73-2021, 2021
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We propose an experimental design of a suite of multi-year, short-term hindcasts and compare them with corresponding observations or measurements for periods based on different weather and climate phenomena. This atypical way of evaluating model performance is particularly useful and beneficial, as these hindcasts can give scientists a robust picture of modeled precipitation, and cloud and radiation processes from their diurnal variation to year-to-year variability.
Peter Kuma, Adrian J. McDonald, Olaf Morgenstern, Richard Querel, Israel Silber, and Connor J. Flynn
Geosci. Model Dev., 14, 43–72, https://doi.org/10.5194/gmd-14-43-2021, https://doi.org/10.5194/gmd-14-43-2021, 2021
Jianglong Zhang, Robert J. D. Spurr, Jeffrey S. Reid, Peng Xian, Peter R. Colarco, James R. Campbell, Edward J. Hyer, and Nancy L. Baker
Geosci. Model Dev., 14, 27–42, https://doi.org/10.5194/gmd-14-27-2021, https://doi.org/10.5194/gmd-14-27-2021, 2021
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A first-of-its-kind scheme has been developed for assimilating Ozone Monitoring Instrument (OMI) aerosol index (AI) measurements into the Naval Aerosol Analysis and Predictive System. Improvements in model simulations demonstrate the utility of OMI AI data assimilation for improving the accuracy of aerosol model analysis over cloudy regions and bright surfaces. This study can be considered one of the first attempts at direct radiance assimilation in the UV spectrum for aerosol analyses.
Felix Kleinert, Lukas H. Leufen, and Martin G. Schultz
Geosci. Model Dev., 14, 1–25, https://doi.org/10.5194/gmd-14-1-2021, https://doi.org/10.5194/gmd-14-1-2021, 2021
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With IntelliO3-ts v1.0, we present an artificial neural network as a new forecasting model for daily aggregated near-surface ozone concentrations with a lead time of up to 4 d. We used measurement and reanalysis data from more than 300 German monitoring stations to train, fine tune, and test the model. We show that the model outperforms standard reference models like persistence models and demonstrate that IntelliO3-ts outperforms climatological reference models for the first 2 d.
Ziyu Huang, Lei Zhong, Yaoming Ma, and Yunfei Fu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-394, https://doi.org/10.5194/gmd-2020-394, 2020
Revised manuscript accepted for GMD
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Spectral nudging is an effective dynamical downscaling method used to improve precipitation simulations of regional climate models (RCMs). However, the biases of the reference fields over the Tibetan Plateau (TP) would possibly introduce extra biases when spectral nudging is applied. Results show that the precipitation simulations were significantly improved when limiting the application of spectral nudging towards the potential temperature and water vapor mixing ratio over the TP.
Adrien Napoly, Aaron Boone, and Théo Welfringer
Geosci. Model Dev., 13, 6523–6545, https://doi.org/10.5194/gmd-13-6523-2020, https://doi.org/10.5194/gmd-13-6523-2020, 2020
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Accurate modeling of snow impact on surface energy and mass fluxes is required from land surface models. This new version of the SURFEX model improves the representation of the snowpack. In particular, it prevents its ablation from occurring too early in the season, which also leads to better soil temperatures and energy fluxes toward the atmosphere. This was made possible with a more explicit and distinct representation of each layer that constitutes the surface (soil, snow, and vegetation).
Robin J. Hogan and Marco Matricardi
Geosci. Model Dev., 13, 6501–6521, https://doi.org/10.5194/gmd-13-6501-2020, https://doi.org/10.5194/gmd-13-6501-2020, 2020
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A key component of computer models used to predict weather and climate is the radiation scheme, which calculates how solar and infrared radiation heats and cools the atmosphere and surface, including the important role of greenhouse gases. This paper describes the experimental protocol and large datasets for a new project, CKDMIP, to evaluate and improve the accuracy of the treatment of atmospheric gases in the radiation schemes used worldwide, as well as their computational speed.
Xiaoli G. Larsén and Jana Fischereit
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-358, https://doi.org/10.5194/gmd-2020-358, 2020
Revised manuscript accepted for GMD
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For the first time, turbulence kinetic energy (TKE) calculated from the explicit wake parameterization (EWP) in WRF is examined using high frequency measurements over a wind farm, and compared with that calculated using scheme from Fitch et al. (2012). We examined the effect of farm-induced TKE advection in connection with the Fitch scheme. Through the case study with Low Level Jet (LLJ), we analyzed the key features of LLJ and raised the issue of interaction between wind farm and LLJ.
David Simpson, Robert Bergström, Alan Briolat, Hannah Imhof, John Johansson, Michael Priestley, and Alvaro Valdebenito
Geosci. Model Dev., 13, 6447–6465, https://doi.org/10.5194/gmd-13-6447-2020, https://doi.org/10.5194/gmd-13-6447-2020, 2020
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This paper outlines the structure and usage of the GenChem system, which includes a chemical pre-processor (GenChem.py) and a simple box model (boxChem). GenChem provides scripts and input files for converting chemical equations into differential form for use in atmospheric chemical transport models (CTMs) and/or the boxChem system. Although GenChem is primarily intended for users of the EMEP MSC-W CTM and related systems, boxChem can be run as a stand-alone chemical solver.
Benjamin N. Murphy, Christopher G. Nolte, Fahim Sidi, Jesse O. Bash, K. Wyat Appel, Carey Jang, Daiwen Kang, James Kelly, Rohit Mathur, Sergey Napelenok, George Pouliot, and Havala O. T. Pye
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-361, https://doi.org/10.5194/gmd-2020-361, 2020
Revised manuscript accepted for GMD
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The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical of atmospheric modeling.
Zhiqiang Li, Bingcheng Wan, Yulun Zhou, and Hokit Wong
Geosci. Model Dev., 13, 6349–6360, https://doi.org/10.5194/gmd-13-6349-2020, https://doi.org/10.5194/gmd-13-6349-2020, 2020
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Our results provide evidence of the effects of incoming land surface data quality on the accuracy of high-resolution urban climate simulations and emphasize the importance of the incoming data quality control.
Yihui Zhou, Yi Zhang, Jian Li, Rucong Yu, and Zhuang Liu
Geosci. Model Dev., 13, 6325–6348, https://doi.org/10.5194/gmd-13-6325-2020, https://doi.org/10.5194/gmd-13-6325-2020, 2020
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This paper explores the configuration of a global atmospheric model (global-to-regional integrated forecast system-atmosphere; GRIST-A) with various multiresolution grids. The model performance is evaluated from dry dynamics to simple physics and full physics. The model is able to resolve the fine-scale structures in the grid-refinement region, and the adverse impact due to the mesh transition and the coarse-resolution area can be controlled well.
Bruce Rolstad Denby, Michael Gauss, Peter Wind, Qing Mu, Eivind Grøtting Wærsted, Hilde Fagerli, Alvaro Valdebenito, and Heiko Klein
Geosci. Model Dev., 13, 6303–6323, https://doi.org/10.5194/gmd-13-6303-2020, https://doi.org/10.5194/gmd-13-6303-2020, 2020
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Air pollution is both a local and a global problem. Since measurements cannot be made everywhere, mathematical models are used to calculate air quality over cities or countries. Modelling over countries limits the level of detail of the models. For countries, the level of detail is only a few kilometres, so air quality at kerb sides is not properly represented. The uEMEP model is used together with the regional air quality model EMEP MSC-W to model details down to kerb side for all of Norway.
Yanfei Liang, Zengliang Zang, Dong Liu, Peng Yan, Yiwen Hu, Yan Zhou, and Wei You
Geosci. Model Dev., 13, 6285–6301, https://doi.org/10.5194/gmd-13-6285-2020, https://doi.org/10.5194/gmd-13-6285-2020, 2020
Ebrahim Eslami, Yunsoo Choi, Yannic Lops, Alqamah Sayeed, and Ahmed Khan Salman
Geosci. Model Dev., 13, 6237–6251, https://doi.org/10.5194/gmd-13-6237-2020, https://doi.org/10.5194/gmd-13-6237-2020, 2020
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As using deep learning algorithms has become a popular data analytic technique, atmospheric scientists should have a balanced perception of their strengths and limitations so that they can provide a powerful analysis of complex data with well-established procedures. This study addresses significant limitations of an advanced deep learning algorithm, the convolutional neural network.
Eemeli Holopainen, Harri Kokkola, Anton Laakso, and Thomas Kühn
Geosci. Model Dev., 13, 6215–6235, https://doi.org/10.5194/gmd-13-6215-2020, https://doi.org/10.5194/gmd-13-6215-2020, 2020
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This paper introduces an in-cloud wet deposition scheme for liquid and ice phase clouds for global aerosol–climate models. With the default setup, our wet deposition scheme behaves spuriously and better representation can be achieved with this scheme when black carbon is mixed with soluble compounds at emission time. This work is done as many of the global models fail to reproduce the transport of black carbon to the Arctic, which may be due to the poor representation of wet removal in models.
Luolin Wu, Jian Hang, Xuemei Wang, Min Shao, and Cheng Gong
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-387, https://doi.org/10.5194/gmd-2020-387, 2020
Revised manuscript accepted for GMD
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In order to improve the resolution and numerical accuracy of urban air quality simulation, this study has developed the APFoam-1.0 to examine the micro-scale reactive pollutant formation and dispersion in the urban area. The model has been validated and shows the good agreement with wind tunnel experimental data. Model sensitivity cases reveal that the vehicle emissions, background concentrations and wind conditions are the key factors affecting the photochemical reaction process.
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Special issue
Short summary
The Environment – HIgh Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction and atmospheric chemical transport model for research and forecasting of joint meteorological, chemical and biological weather. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and ''fit-for-purpose'' model configurations for the meteorological and air quality communities are discussed.
The Environment – HIgh Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully...
