Articles | Volume 14, issue 6
Geosci. Model Dev., 14, 3335–3359, 2021
https://doi.org/10.5194/gmd-14-3335-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: The Norwegian Earth System Model: NorESM; basic development,...
Geosci. Model Dev., 14, 3335–3359, 2021
https://doi.org/10.5194/gmd-14-3335-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper 04 Jun 2021
Development and technical paper | 04 Jun 2021
Implementing a sectional scheme for early aerosol growth from new particle formation in the Norwegian Earth System Model v2: comparison to observations and climate impacts
Sara M. Blichner et al.
Related authors
Sara Marie Blichner, Moa Kristina Sporre, and Terje Koren Berntsen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-151, https://doi.org/10.5194/acp-2021-151, 2021
Preprint under review for ACP
Short summary
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In this study we quantify how a new way of modeling the formation of new particles in the atmosphere, affects the estimated cooling from aerosol-cloud interactions since pre-industrial times. Our improved scheme merges two common approaches to aerosol modelling: a sectional scheme for treating the early growth and the pre-existing modal scheme in the NorESM. We find that the cooling from aerosol-cloud interactions since pre-industrial time is reduced by 10 % when the new scheme is used.
Moa K. Sporre, Sara M. Blichner, Roland Schrödner, Inger H. H. Karset, Terje K. Berntsen, Twan van Noije, Tommi Bergman, Declan O'Donnell, and Risto Makkonen
Atmos. Chem. Phys., 20, 8953–8973, https://doi.org/10.5194/acp-20-8953-2020, https://doi.org/10.5194/acp-20-8953-2020, 2020
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We investigate how emissions and parameters in current
SOA parameterisations in three ESMs affect both the resulting SOA in the models and the impact this has on climate through the direct and indirect aerosol effects. The SOA changes induce very different responses in the models, especially in terms of the indirect aerosol effect. This introduces uncertainties in ESM estimates of SOA climate impact through feedbacks in a warming climate and through anthropogenic land use change.
Moa K. Sporre, Sara M. Blichner, Inger H. H. Karset, Risto Makkonen, and Terje K. Berntsen
Atmos. Chem. Phys., 19, 4763–4782, https://doi.org/10.5194/acp-19-4763-2019, https://doi.org/10.5194/acp-19-4763-2019, 2019
Short summary
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In this study, an Earth system model has been used to investigate climate feedbacks associated with increasing BVOC emissions due to higher CO2 concentrations and temperatures. Higher BVOC emissions associated with a changed climate are found to induce an important negative climate feedback through increased aerosol formation and resulting changes in cloud properties. This feedback is found to have the potential to offset about 13 % of the radiative forcing associated with a doubling of CO2.
Stefanie Falk, Ane Victoria Vollsnes, Aud Eriksen, Frode Stordal, and Terje Koren Berntsen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-527, https://doi.org/10.5194/acp-2021-527, 2021
Preprint under review for ACP
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We evaluate regional and global models for ozone modeling and damage risk mapping of vegetation over subarctic Europe. Our analysis suggests that low-resolution global models do not reproduce the observed ozone seasonal cycle at ground level underestimating ozone by 30–50 %. High-resolution regional models capture the seasonal cycle well still underestimating ozone by up to 20 %. Our proposed gap-filling method for site observations shows a 78 % accuracy compared to the regional model (73 %).
Oscar S. Sandvik, Johan Friberg, Moa K. Sporre, and Bengt G. Martinsson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-94, https://doi.org/10.5194/amt-2021-94, 2021
Preprint under review for AMT
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A method to form SO2 profiles in the stratosphere with high vertical resolution following volcanic eruptions is introduced. The method combines space-based high-resolution vertical aerosol profiles and SO2 measurements the first two weeks after an eruption with air trajectory analyses. The profile agrees with a published high-resolution aerosol profile when most of the SO2 is converted to sulphate aerosol. The detailed resolution of the SO2 profile is unprecedented compared to other methods.
Hanna Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Michael Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Ye Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Koster, Elena Lapsina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenko, Dimitry Orlov, Jean-Daniel Paris, Robertta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qui, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergey Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-341, https://doi.org/10.5194/acp-2021-341, 2021
Preprint under review for ACP
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We summarize results during the last five years in the Northern Eurasian region, especially from Russia, and introduce recent observations on the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate-Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Sara Marie Blichner, Moa Kristina Sporre, and Terje Koren Berntsen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-151, https://doi.org/10.5194/acp-2021-151, 2021
Preprint under review for ACP
Short summary
Short summary
In this study we quantify how a new way of modeling the formation of new particles in the atmosphere, affects the estimated cooling from aerosol-cloud interactions since pre-industrial times. Our improved scheme merges two common approaches to aerosol modelling: a sectional scheme for treating the early growth and the pre-existing modal scheme in the NorESM. We find that the cooling from aerosol-cloud interactions since pre-industrial time is reduced by 10 % when the new scheme is used.
Tommi Bergman, Risto Makkonen, Roland Schrödner, Erik Swietlicki, Vaughan T. J. Phillips, Philippe Le Sager, and Twan van Noije
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-49, https://doi.org/10.5194/gmd-2021-49, 2021
Preprint under review for GMD
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We describe in this paper the implementation of a process based secondary organic aerosol and new particle formation scheme within the chemistry transport model TM5-MP version 1.1. The performance of the model simulations for year 2010 are evaluated against in-situ observations, ground-based remote sensing and satellite retrievals. Overall, the simulated aerosol fields are improved although in some areas the model shows decline in performance.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Almut Arneth, Thomas Arsouze, Tommi Bergmann, Raffaele Bernadello, Souhail Bousetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, Francois Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O’Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-446, https://doi.org/10.5194/gmd-2020-446, 2021
Revised manuscript under review for GMD
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The Earth System Model EC-Earth3 is documented here. Key performance metrics show physical behaviour and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Peter Horvath, Hui Tang, Rune Halvorsen, Frode Stordal, Lena Merete Tallaksen, Terje Koren Berntsen, and Anders Bryn
Biogeosciences, 18, 95–112, https://doi.org/10.5194/bg-18-95-2021, https://doi.org/10.5194/bg-18-95-2021, 2021
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We evaluated the performance of three methods for representing vegetation cover. Remote sensing provided the best match to a reference dataset, closely followed by distribution modelling (DM), whereas the dynamic global vegetation model (DGVM) in CLM4.5BGCDV deviated strongly from the reference. Sensitivity tests show that use of threshold values for predictors identified by DM may improve DGVM performance. The results highlight the potential of using DM in the development of DGVMs.
Twan van Noije, Tommi Bergman, Philippe Le Sager, Declan O'Donnell, Risto Makkonen, María Gonçalves-Ageitos, Ralf Döscher, Uwe Fladrich, Jost von Hardenberg, Jukka-Pekka Keskinen, Hannele Korhonen, Anton Laakso, Stelios Myriokefalitakis, Pirkka Ollinaho, Carlos Pérez García-Pando, Thomas Reerink, Roland Schrödner, Klaus Wyser, and Shuting Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-413, https://doi.org/10.5194/gmd-2020-413, 2020
Revised manuscript under review for GMD
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This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). We describe the model in detail and provide information about the applied tuning and spin-up procedures. The model's performance is characterized using coupled simulations conducted for CMIP6. The model has an effective equilibrium climate sensitivity of 3.9 °C and a transient climate response of 2.1 °C.
Marianne T. Lund, Borgar Aamaas, Camilla W. Stjern, Zbigniew Klimont, Terje K. Berntsen, and Bjørn H. Samset
Earth Syst. Dynam., 11, 977–993, https://doi.org/10.5194/esd-11-977-2020, https://doi.org/10.5194/esd-11-977-2020, 2020
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Achieving the Paris Agreement temperature goals requires both near-zero levels of long-lived greenhouse gases and deep cuts in emissions of short-lived climate forcers (SLCFs). Here we quantify the near- and long-term global temperature impacts of emissions of individual SLCFs and CO2 from 7 economic sectors in 13 regions in order to provide the detailed knowledge needed to design efficient mitigation strategies at the sectoral and regional levels.
Stina Ausmeel, Axel Eriksson, Erik Ahlberg, Moa K. Sporre, Mårten Spanne, and Adam Kristensson
Atmos. Chem. Phys., 20, 9135–9151, https://doi.org/10.5194/acp-20-9135-2020, https://doi.org/10.5194/acp-20-9135-2020, 2020
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Emissions from shipping have an impact on air quality, especially in coastal areas. We have measured properties of the airborne particles in several plumes from ships that are sailing within an Emission Control Area. Individual ships showed large variability in contribution to total particle mass and nitrogen dioxide. Organics and sulfate dominated the particle mass, and most plumes contained very little or no soot. We also present recommendations for future stationary ship plume measurements.
Moa K. Sporre, Sara M. Blichner, Roland Schrödner, Inger H. H. Karset, Terje K. Berntsen, Twan van Noije, Tommi Bergman, Declan O'Donnell, and Risto Makkonen
Atmos. Chem. Phys., 20, 8953–8973, https://doi.org/10.5194/acp-20-8953-2020, https://doi.org/10.5194/acp-20-8953-2020, 2020
Short summary
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We investigate how emissions and parameters in current
SOA parameterisations in three ESMs affect both the resulting SOA in the models and the impact this has on climate through the direct and indirect aerosol effects. The SOA changes induce very different responses in the models, especially in terms of the indirect aerosol effect. This introduces uncertainties in ESM estimates of SOA climate impact through feedbacks in a warming climate and through anthropogenic land use change.
Maria Sand, Terje K. Berntsen, Annica M. L. Ekman, Hans-Christen Hansson, and Anna Lewinschal
Atmos. Chem. Phys., 20, 3079–3089, https://doi.org/10.5194/acp-20-3079-2020, https://doi.org/10.5194/acp-20-3079-2020, 2020
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There has been a growing interest in reducing emissions of soot particles to slow global warming and improve air quality. However, estimating the effect of reduced emissions is complex, as soot particles absorb solar radiation and influence heating rates, clouds, and humidity and can influence climate far outside their emission region. Here we investigate the impact of soot emitted in four major emissions areas, using different emissions rates, to see whether location and magnitude matter.
Giulia Saponaro, Moa K. Sporre, David Neubauer, Harri Kokkola, Pekka Kolmonen, Larisa Sogacheva, Antti Arola, Gerrit de Leeuw, Inger H. H. Karset, Ari Laaksonen, and Ulrike Lohmann
Atmos. Chem. Phys., 20, 1607–1626, https://doi.org/10.5194/acp-20-1607-2020, https://doi.org/10.5194/acp-20-1607-2020, 2020
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The understanding of cloud processes is based on the quality of the representation of cloud properties. We compared cloud parameters from three models with satellite observations. We report on the performance of each data source, highlighting strengths and deficiencies, which should be considered when deriving the effect of aerosols on cloud properties.
Borgar Aamaas, Terje Koren Berntsen, and Bjørn Hallvard Samset
Atmos. Chem. Phys., 19, 15235–15245, https://doi.org/10.5194/acp-19-15235-2019, https://doi.org/10.5194/acp-19-15235-2019, 2019
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Cutting short-lived pollutants can help keep cool the climate – but only if we are clever. We investigate how regional temperatures may change in response to different packages of air quality measures. One package consists of mitigation measures that mainly target emissions that are known to result in a cooler climate, while in the other, emissions are cut as much as technically possible in response to air quality concerns. We estimate the different contributions from various sectors and region.
Ulas Im, Jesper H. Christensen, Ole-Kenneth Nielsen, Maria Sand, Risto Makkonen, Camilla Geels, Camilla Anderson, Jaakko Kukkonen, Susana Lopez-Aparicio, and Jørgen Brandt
Atmos. Chem. Phys., 19, 12975–12992, https://doi.org/10.5194/acp-19-12975-2019, https://doi.org/10.5194/acp-19-12975-2019, 2019
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Sectoral contributions of anthropogenic emissions in Denmark, Finland, Norway and Sweden on air pollution and mortality over the Nordic and the Arctic regions are calculated. 80 % of PM2.5 over the Nordic countries is transported from outside Scandinavia. Residential combustion, industry and traffic are the main sectors to be targeted in emission mitigation. Exposure to ambient air pollution in the Nordic countries leads to more than 10 000 deaths in the region annually and costs EUR 7 billion.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
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Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Moa K. Sporre, Sara M. Blichner, Inger H. H. Karset, Risto Makkonen, and Terje K. Berntsen
Atmos. Chem. Phys., 19, 4763–4782, https://doi.org/10.5194/acp-19-4763-2019, https://doi.org/10.5194/acp-19-4763-2019, 2019
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In this study, an Earth system model has been used to investigate climate feedbacks associated with increasing BVOC emissions due to higher CO2 concentrations and temperatures. Higher BVOC emissions associated with a changed climate are found to induce an important negative climate feedback through increased aerosol formation and resulting changes in cloud properties. This feedback is found to have the potential to offset about 13 % of the radiative forcing associated with a doubling of CO2.
Anna Lewinschal, Annica M. L. Ekman, Hans-Christen Hansson, Maria Sand, Terje K. Berntsen, and Joakim Langner
Atmos. Chem. Phys., 19, 2385–2403, https://doi.org/10.5194/acp-19-2385-2019, https://doi.org/10.5194/acp-19-2385-2019, 2019
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We use a global climate model to study how anthropogenic emissions of short-lived atmospheric particles in different parts of the world influence the global temperature distribution. We find that the global mean temperature change per unit emission is similar for all emission regions, and the largest temperature response is found in the Arctic no matter where the emissions occur. However, for European emissions, the temperature change per unit emission is found to depend on emission strength.
Kjetil S. Aas, Léo Martin, Jan Nitzbon, Moritz Langer, Julia Boike, Hanna Lee, Terje K. Berntsen, and Sebastian Westermann
The Cryosphere, 13, 591–609, https://doi.org/10.5194/tc-13-591-2019, https://doi.org/10.5194/tc-13-591-2019, 2019
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Many permafrost landscapes contain large amounts of excess ground ice, which gives rise to small-scale elevation differences. This results in lateral fluxes of snow, water, and heat, which we investigate and show how it can be accounted for in large-scale models. Using a novel model technique which can account for these differences, we are able to model both the current state of permafrost and how these landscapes change as permafrost thaws, in a way that could not previously be achieved.
Ragnhild Bieltvedt Skeie, Terje Berntsen, Magne Aldrin, Marit Holden, and Gunnar Myhre
Earth Syst. Dynam., 9, 879–894, https://doi.org/10.5194/esd-9-879-2018, https://doi.org/10.5194/esd-9-879-2018, 2018
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A key question in climate science is how the global mean surface temperature responds to changes in greenhouse gases. This dependency is quantified by the climate sensitivity, which is determined by the complex feedbacks in the climate system. In this study observations of past climate change are used to estimate this sensitivity. Our estimate is consistent with values for the equilibrium climate sensitivity estimated by complex climate models but sensitive to the use of uncertain input data.
Inger Helene Hafsahl Karset, Terje Koren Berntsen, Trude Storelvmo, Kari Alterskjær, Alf Grini, Dirk Olivié, Alf Kirkevåg, Øyvind Seland, Trond Iversen, and Michael Schulz
Atmos. Chem. Phys., 18, 7669–7690, https://doi.org/10.5194/acp-18-7669-2018, https://doi.org/10.5194/acp-18-7669-2018, 2018
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This study highlights the role of oxidants in modeling of the preindustrial-to-present-day aerosol indirect effects. We argue that the aerosol precursor gases should be exposed to oxidants of its era to get a more correct representation of secondary aerosol formation. Our global model simulations show that the total aerosol indirect effect changes from −1.32 to −1.07 W m−2 when the precursor gases in the preindustrial simulation are exposed to preindustrial instead of present-day oxidants.
Maria Sand, Bjørn H. Samset, Yves Balkanski, Susanne Bauer, Nicolas Bellouin, Terje K. Berntsen, Huisheng Bian, Mian Chin, Thomas Diehl, Richard Easter, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Jean-François Lamarque, Guangxing Lin, Xiaohong Liu, Gan Luo, Gunnar Myhre, Twan van Noije, Joyce E. Penner, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Fangqun Yu, Kai Zhang, and Hua Zhang
Atmos. Chem. Phys., 17, 12197–12218, https://doi.org/10.5194/acp-17-12197-2017, https://doi.org/10.5194/acp-17-12197-2017, 2017
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The role of aerosols in the changing polar climate is not well understood and the aerosols are poorly constrained in the models. In this study we have compared output from 16 different aerosol models with available observations at both poles. We show that the model median is representative of the observations, but the model spread is large. The Arctic direct aerosol radiative effect over the industrial area is positive during spring due to black carbon and negative during summer due to sulfate.
Johan Martinsson, Guillaume Monteil, Moa K. Sporre, Anne Maria Kaldal Hansen, Adam Kristensson, Kristina Eriksson Stenström, Erik Swietlicki, and Marianne Glasius
Atmos. Chem. Phys., 17, 11025–11040, https://doi.org/10.5194/acp-17-11025-2017, https://doi.org/10.5194/acp-17-11025-2017, 2017
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This study attempts to link observations of biogenic organic compounds found in atmospheric particles to landscape exposure of the incoming air mass. The results revealed that several of the observed compounds were connected to exposure of coniferous forests. There were also a number of landscape types that did not contribute to the biogenic organic compounds, sea and ocean as an example. This type of methodology may be important in order to study land use changes impact on air quality.
Borgar Aamaas, Terje K. Berntsen, Jan S. Fuglestvedt, Keith P. Shine, and William J. Collins
Atmos. Chem. Phys., 17, 10795–10809, https://doi.org/10.5194/acp-17-10795-2017, https://doi.org/10.5194/acp-17-10795-2017, 2017
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The climate impacts for emissions of different pollutants can be made comparable with weighting factors. This article estimates these weights based on temperature change for short-lived pollutants, such as methane and black carbon. Emissions from different seasons and regions are compared, for instance Europe and East Asia. The responses are calculated for four regions, where we see that the responses can be much higher in the Arctic than globally in some cases.
Marianne T. Lund, Borgar Aamaas, Terje Berntsen, Lisa Bock, Ulrike Burkhardt, Jan S. Fuglestvedt, and Keith P. Shine
Earth Syst. Dynam., 8, 547–563, https://doi.org/10.5194/esd-8-547-2017, https://doi.org/10.5194/esd-8-547-2017, 2017
Marianne T. Lund, Terje K. Berntsen, and Bjørn H. Samset
Atmos. Chem. Phys., 17, 6003–6022, https://doi.org/10.5194/acp-17-6003-2017, https://doi.org/10.5194/acp-17-6003-2017, 2017
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This study investigates possibilities for improving the representation of black carbon (BC) distribution in a global atmospheric chemistry-transport model by exploring uncertainties in key processes controlling the removal of aerosols from the atmosphere. Our results provide an increased understanding of the processes contributing to uncertainties in the BC abundance and climate impact and underline the importance of more observations and experimental data further constrain models.
Johan Martinsson, Hafiz Abdul Azeem, Moa K. Sporre, Robert Bergström, Erik Ahlberg, Emilie Öström, Adam Kristensson, Erik Swietlicki, and Kristina Eriksson Stenström
Atmos. Chem. Phys., 17, 4265–4281, https://doi.org/10.5194/acp-17-4265-2017, https://doi.org/10.5194/acp-17-4265-2017, 2017
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In this study we have focused our attention on the sources atmospheric carbon particles. More specifically, we evaluate a fast and inexpensive method which determines the source of these particles by utilizing light absorption by the particles. We found that this method is suitable for source estimation by comparing it to another method based on carbon isotopes and chemical tracer molecules. Cheap and fast methods based on light absorption can be utilized widely to deduce particle sources.
Borgar Aamaas, Terje K. Berntsen, Jan S. Fuglestvedt, and Glen P. Peters
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-25, https://doi.org/10.5194/esd-2017-25, 2017
Manuscript not accepted for further review
Moa K. Sporre, Ewan J. O'Connor, Nina Håkansson, Anke Thoss, Erik Swietlicki, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 3193–3203, https://doi.org/10.5194/amt-9-3193-2016, https://doi.org/10.5194/amt-9-3193-2016, 2016
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Satellite measurements of cloud top height and liquid water path are compared to ground-based remote sensing to evaluate the satellite retrievals. The overall performance of the satellite retrievals of cloud top height are good, but they become more problematic when several layers of clouds are present. The liquid water path retrievals also agree well, and the average differences are within the estimated measurement uncertainties.
Borgar Aamaas, Terje K. Berntsen, Jan S. Fuglestvedt, Keith P. Shine, and Nicolas Bellouin
Atmos. Chem. Phys., 16, 7451–7468, https://doi.org/10.5194/acp-16-7451-2016, https://doi.org/10.5194/acp-16-7451-2016, 2016
Kjetil S. Aas, Thorben Dunse, Emily Collier, Thomas V. Schuler, Terje K. Berntsen, Jack Kohler, and Bartłomiej Luks
The Cryosphere, 10, 1089–1104, https://doi.org/10.5194/tc-10-1089-2016, https://doi.org/10.5194/tc-10-1089-2016, 2016
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A high-resolution, coupled atmosphere--climatic mass balance (CMB) model is applied to Svalbard for the period 2003 to 2013. The mean CMB during this period is negative but displays large spatial and temporal variations. Comparison with observations on different scales shows a good overall model performance except for one particular glacier, where wind strongly affects the spatial patterns of CMB. The model also shows considerable sensitivity to model resolution, especially on local scales.
A. Stohl, B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. Olivié, J. Quaas, B. Quennehen, J.-C. Raut, S. T. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu
Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, https://doi.org/10.5194/acp-15-10529-2015, 2015
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This paper presents a summary of the findings of the ECLIPSE EU project. The project has investigated the climate and air quality impacts of short-lived climate pollutants (especially methane, ozone, aerosols) and has designed a global mitigation strategy that maximizes co-benefits between air quality and climate policy. Transient climate model simulations allowed quantifying the impacts on temperature (e.g., reduction in global warming by 0.22K for the decade 2041-2050) and precipitation.
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
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The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
B. H. Samset, G. Myhre, A. Herber, Y. Kondo, S.-M. Li, N. Moteki, M. Koike, N. Oshima, J. P. Schwarz, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, M. Chin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, M. Schulz, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 14, 12465–12477, https://doi.org/10.5194/acp-14-12465-2014, https://doi.org/10.5194/acp-14-12465-2014, 2014
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Far from black carbon (BC) emission sources, present climate models are unable to reproduce flight measurements. By comparing recent models with data, we find that the atmospheric lifetime of BC may be overestimated in models. By adjusting modeled BC concentrations to measurements in remote regions - over oceans and at high altitudes - we arrive at a reduced estimate for BC radiative forcing over the industrial era.
M. K. Sporre, E. Swietlicki, P. Glantz, and M. Kulmala
Atmos. Chem. Phys., 14, 12167–12179, https://doi.org/10.5194/acp-14-12167-2014, https://doi.org/10.5194/acp-14-12167-2014, 2014
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
R. B. Skeie, T. Berntsen, M. Aldrin, M. Holden, and G. Myhre
Earth Syst. Dynam., 5, 139–175, https://doi.org/10.5194/esd-5-139-2014, https://doi.org/10.5194/esd-5-139-2014, 2014
C. Jiao, M. G. Flanner, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, K. S. Carslaw, M. Chin, N. De Luca, T. Diehl, S. J. Ghan, T. Iversen, A. Kirkevåg, D. Koch, X. Liu, G. W. Mann, J. E. Penner, G. Pitari, M. Schulz, Ø. Seland, R. B. Skeie, S. D. Steenrod, P. Stier, T. Takemura, K. Tsigaridis, T. van Noije, Y. Yun, and K. Zhang
Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, https://doi.org/10.5194/acp-14-2399-2014, 2014
M. K. Sporre, E. Swietlicki, P. Glantz, and M. Kulmala
Atmos. Chem. Phys., 14, 2203–2217, https://doi.org/10.5194/acp-14-2203-2014, https://doi.org/10.5194/acp-14-2203-2014, 2014
M. S. Eide, S. B. Dalsøren, Ø. Endresen, B. Samset, G. Myhre, J. Fuglestvedt, and T. Berntsen
Atmos. Chem. Phys., 13, 4183–4201, https://doi.org/10.5194/acp-13-4183-2013, https://doi.org/10.5194/acp-13-4183-2013, 2013
Y. H. Lee, J.-F. Lamarque, M. G. Flanner, C. Jiao, D. T. Shindell, T. Berntsen, M. M. Bisiaux, J. Cao, W. J. Collins, M. Curran, R. Edwards, G. Faluvegi, S. Ghan, L. W. Horowitz, J. R. McConnell, J. Ming, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. B. Skeie, K. Sudo, T. Takemura, F. Thevenon, B. Xu, and J.-H. Yoon
Atmos. Chem. Phys., 13, 2607–2634, https://doi.org/10.5194/acp-13-2607-2013, https://doi.org/10.5194/acp-13-2607-2013, 2013
B. H. Samset, G. Myhre, M. Schulz, Y. Balkanski, S. Bauer, T. K. Berntsen, H. Bian, N. Bellouin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, S. Kinne, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 13, 2423–2434, https://doi.org/10.5194/acp-13-2423-2013, https://doi.org/10.5194/acp-13-2423-2013, 2013
M. Sand, T. K. Berntsen, J. E. Kay, J. F. Lamarque, Ø. Seland, and A. Kirkevåg
Atmos. Chem. Phys., 13, 211–224, https://doi.org/10.5194/acp-13-211-2013, https://doi.org/10.5194/acp-13-211-2013, 2013
Ø. Hodnebrog, T. K. Berntsen, O. Dessens, M. Gauss, V. Grewe, I. S. A. Isaksen, B. Koffi, G. Myhre, D. Olivié, M. J. Prather, F. Stordal, S. Szopa, Q. Tang, P. van Velthoven, and J. E. Williams
Atmos. Chem. Phys., 12, 12211–12225, https://doi.org/10.5194/acp-12-12211-2012, https://doi.org/10.5194/acp-12-12211-2012, 2012
Related subject area
Atmospheric sciences
Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): organization and experimental design
Sensitivity analysis of the PALM model system 6.0 in the urban environment
Investigating the importance of sub-grid particle formation in point source plumes over eastern China using IAP-AACM v1.0 with a sub-grid parameterization
SCARLET-1.0: SpheriCal Approximation for viRtuaL aggrEgaTes
BARRA v1.0: kilometre-scale downscaling of an Australian regional atmospheric reanalysis over four midlatitude domains
Grid-independent high-resolution dust emissions (v1.0) for chemical transport models: application to GEOS-Chem (12.5.0)
Oxidation of low-molecular-weight organic compounds in cloud droplets: development of the Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC) in CAABA/MECCA (version 4.5.0)
Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 – Part 2: The city contribution
Vertical structure of cloud radiative heating in the tropics: confronting the EC-Earth v3.3.1/3P model with satellite observations
Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States
MSDM v1.0: A machine learning model for precipitation nowcasting over eastern China using multisource data
A climatology of tropical wind shear produced by clustering wind profiles from the Met Office Unified Model (GA7.0)
Surface representation impacts on turbulent heat fluxes in the Weather Research and Forecasting (WRF) model (v.4.1.3)
Effects of heterogeneous reactions on tropospheric chemistry: a global simulation with the chemistry–climate model CHASER V4.0
Development of a large-eddy simulation subgrid model based on artificial neural networks: a case study of turbulent channel flow
WRF-GC (v2.0): online two-way coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.7.2) for modeling regional atmospheric chemistry–meteorology interactions
Modifying emissions scenario projections to account for the effects of COVID-19: protocol for CovidMIP
Towards an improved treatment of cloud–radiation interaction in weather and climate models: exploring the potential of the Tripleclouds method for various cloud types using libRadtran 2.0.4
A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1)
OpenIFS@home version 1: a citizen science project for ensemble weather and climate forecasting
Regional CO2 inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0
The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) modeling system version 5.3.2
Evaluation of the dynamic core of the PALM model system 6.0 in a neutrally stratified urban environment: comparison between LES and wind-tunnel experiments
Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)
Simulation of O3 and NOx in São Paulo street urban canyons with VEIN (v0.2.2) and MUNICH (v1.0)
A case study of wind farm effects using two wake parameterizations in the Weather Research and Forecasting (WRF) model (V3.7.1) in the presence of low-level jets
Radiative Transfer Model 3.0 integrated into the PALM model system 6.0
Development and evaluation of CO2 transport in MPAS-A v6.3
Variational regional inverse modeling of reactive species emissions with PYVAR-CHIMERE-v2019
A new gas absorption optical depth parameterisation for RTTOV version 13
The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation
Development and evaluation of spectral nudging strategy for the simulation of summer precipitation over the Tibetan Plateau using WRF (v4.0)
Combining homogeneous and heterogeneous chemistry to model inorganic compound concentrations in indoor environments: the H2I model (v1.0)
Interpol-IAGOS: a new method for assessing long-term chemistry–climate simulations in the UTLS based on IAGOS data, and its application to the MOCAGE CCMI REF-C1SD simulation
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
Improvements to the representation of BVOC chemistry-climate interactions in UKCA (vn11.5) with the CRI-Strat 2 mechanism: Incorporation and Evaluation
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
Exploring Deep Learning for Air Pollutant Emission Estimation
urbanChemFoam 1.0: Large-Eddy Simulation of Non-Stationary Chemical Transport of Traffic Emissions in an Idealized Street Canyon
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
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Michal Belda, Jaroslav Resler, Jan Geletič, Pavel Krč, Björn Maronga, Matthias Sühring, Mona Kurppa, Farah Kanani-Sühring, Vladimír Fuka, Kryštof Eben, Nina Benešová, and Mikko Auvinen
Geosci. Model Dev., 14, 4443–4464, https://doi.org/10.5194/gmd-14-4443-2021, https://doi.org/10.5194/gmd-14-4443-2021, 2021
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The analysis summarizes how sensitive the modelling of urban environment is to changes in physical parameters describing the city (e.g. reflectivity of surfaces) and to several heat island mitigation scenarios in a city quarter in Prague, Czech Republic. We used the large-eddy simulation modelling system PALM 6.0. Surface parameters connected to radiation show the highest sensitivity in this configuration. For heat island mitigation, urban vegetation is shown to be the most effective measure.
Ying Wei, Xueshun Chen, Huansheng Chen, Yele Sun, Wenyi Yang, Huiyun Du, Qizhong Wu, Dan Chen, Xiujuan Zhao, Jie Li, and Zifa Wang
Geosci. Model Dev., 14, 4411–4428, https://doi.org/10.5194/gmd-14-4411-2021, https://doi.org/10.5194/gmd-14-4411-2021, 2021
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The sub-grid particle formation (SGPF) in plumes plays an important role in air pollution and climate. We coupled an SGPF scheme to a chemical transport model with an aerosol microphysics module and applied it to investigate the SGPF impact over China. The scheme clearly improved the model performance in simulating aerosol components and particle number at typical sites influenced by point sources. The results indicate the significant effects of SGPF on aerosol particles in industrial areas.
Eduardo Rossi and Costanza Bonadonna
Geosci. Model Dev., 14, 4379–4400, https://doi.org/10.5194/gmd-14-4379-2021, https://doi.org/10.5194/gmd-14-4379-2021, 2021
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SCARLET-1.0 is a MATLAB package that creates virtual aggregates starting from a population of irregular shapes. Shapes are described in terms of the Standard Triangulation Language (STL) format, and this allows importing a great variety of shapes, such as from 3D scanning. The package produces a new STL file as an output and different analytical information about the packing, such as the porosity. It has been specifically designed for use in volcanology and scientific education.
Chun-Hsu Su, Nathan Eizenberg, Dörte Jakob, Paul Fox-Hughes, Peter Steinle, Christopher J. White, and Charmaine Franklin
Geosci. Model Dev., 14, 4357–4378, https://doi.org/10.5194/gmd-14-4357-2021, https://doi.org/10.5194/gmd-14-4357-2021, 2021
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The Bureau of Meteorology Atmospheric Regional Reanalysis for Australia (BARRA) has produced a very high-resolution reconstruction of Australian historical weather from 1990 to 2018. This paper demonstrates the added weather and climate information to supplement coarse- or moderate-resolution regional and global reanalyses. The new climate data can allow greater understanding of past weather, including extreme events, at very local kilometre scales.
Jun Meng, Randall V. Martin, Paul Ginoux, Melanie Hammer, Melissa P. Sulprizio, David A. Ridley, and Aaron van Donkelaar
Geosci. Model Dev., 14, 4249–4260, https://doi.org/10.5194/gmd-14-4249-2021, https://doi.org/10.5194/gmd-14-4249-2021, 2021
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Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emission strengths calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with an optimized global dust strength, presented in this work, can be implemented into GEOS-Chem as offline emission inventory so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.
Simon Rosanka, Rolf Sander, Andreas Wahner, and Domenico Taraborrelli
Geosci. Model Dev., 14, 4103–4115, https://doi.org/10.5194/gmd-14-4103-2021, https://doi.org/10.5194/gmd-14-4103-2021, 2021
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The Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC) is developed and implemented into the Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA). JAMOC is an explicit in-cloud oxidation scheme for oxygenated volatile organic compounds (OVOCs), which is suitable for global model applications. Within a box-model study, we show that JAMOC yields reduced gas-phase concentrations of most OVOCs and oxidants, except for nitrogen oxides.
Matthieu Pommier
Geosci. Model Dev., 14, 4143–4158, https://doi.org/10.5194/gmd-14-4143-2021, https://doi.org/10.5194/gmd-14-4143-2021, 2021
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Within the Copernicus Atmosphere Monitoring Service (CAMS), a forecasting system calculating the city source contribution for the surface urban background PM10 in European cities has been developed. The system uses the EMEP model and this paper presents the product by focusing on an event which occurred from 1 to 9 December 2016.
Erik Johansson, Abhay Devasthale, Michael Tjernström, Annica M. L. Ekman, Klaus Wyser, and Tristan L'Ecuyer
Geosci. Model Dev., 14, 4087–4101, https://doi.org/10.5194/gmd-14-4087-2021, https://doi.org/10.5194/gmd-14-4087-2021, 2021
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Understanding the coupling of clouds to large-scale circulation is a grand challenge for the climate community. Cloud radiative heating (CRH) is a key parameter in this coupling and is therefore essential to model realistically. We, therefore, evaluate a climate model against satellite observations. Our findings indicate good agreement in the seasonal pattern of CRH even if the magnitude differs. We also find that increasing the horizontal resolution in the model has little effect on the CRH.
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021, https://doi.org/10.5194/gmd-14-3969-2021, 2021
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The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
Dawei Li, Yudi Liu, and Chaohui Chen
Geosci. Model Dev., 14, 4019–4034, https://doi.org/10.5194/gmd-14-4019-2021, https://doi.org/10.5194/gmd-14-4019-2021, 2021
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In the daily weather forecast business, numerical weather prediction is mainly used to forecast precipitation, but its performance for nowcasting tasks within 0–2 h is very poor. Hence, we hope to use machine learning to improve the accuracy and resolution of quantitative precipitation nowcasting (QPN) tasks. Previous works focused on the extrapolation of radar echo without using abundant meteorological data. Therefore, we designed a model using three kinds of data for QPN in eastern china.
Mark R. Muetzelfeldt, Robert S. Plant, Peter A. Clark, Alison J. Stirling, and Steven J. Woolnough
Geosci. Model Dev., 14, 4035–4049, https://doi.org/10.5194/gmd-14-4035-2021, https://doi.org/10.5194/gmd-14-4035-2021, 2021
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Wind shear causes organized convection in the tropics, producing, e.g., squall lines. We have developed a procedure for producing a climatology of sheared wind profiles in a climate model and demonstrated that the profiles are linked with organized convection, both in terms of their structure and their spatio-temporal distribution. The procedure could be used to diagnose organization of convection in a climate model, which could lead to improvements in the model's representation of convection.
Carlos Román-Cascón, Marie Lothon, Fabienne Lohou, Oscar Hartogensis, Jordi Vila-Guerau de Arellano, David Pino, Carlos Yagüe, and Eric R. Pardyjak
Geosci. Model Dev., 14, 3939–3967, https://doi.org/10.5194/gmd-14-3939-2021, https://doi.org/10.5194/gmd-14-3939-2021, 2021
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The type of vegetation (or land cover) and its status influence the heat and water transfers between the surface and the air, affecting the processes that develop in the atmosphere at different (but connected) spatiotemporal scales. In this work, we investigate how these transfers are affected by the way the surface is represented in a widely used weather model. The results encourage including realistic high-resolution and updated land cover databases in models to improve their predictions.
Phuc T. M. Ha, Ryoki Matsuda, Yugo Kanaya, Fumikazu Taketani, and Kengo Sudo
Geosci. Model Dev., 14, 3813–3841, https://doi.org/10.5194/gmd-14-3813-2021, https://doi.org/10.5194/gmd-14-3813-2021, 2021
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Policies to mitigate air pollution require an understanding of tropospheric oxidizing capacity, which is controlled by mechanisms including heterogeneous processes on aerosols and clouds. This study uses a chemistry–climate model CHASER (MIROC) to explore the heterogeneous effects in the troposphere for -2.96 % O3, -2.19 % NOx, +3.28 % CO, and +5.91 % CH4 lifetime. Besides, these processes affect polluted areas and remote areas and can bring challenges to pollution reduction efforts.
Robin Stoffer, Caspar M. van Leeuwen, Damian Podareanu, Valeriu Codreanu, Menno A. Veerman, Martin Janssens, Oscar K. Hartogensis, and Chiel C. van Heerwaarden
Geosci. Model Dev., 14, 3769–3788, https://doi.org/10.5194/gmd-14-3769-2021, https://doi.org/10.5194/gmd-14-3769-2021, 2021
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Turbulent flows are often simulated with the large-eddy simulation (LES) technique, which requires subgrid models to account for the smallest scales. Current subgrid models often require strong simplifying assumptions. We therefore developed a subgrid model based on artificial neural networks, which requires fewer assumptions. Our data-driven SGS model showed high potential in accurately representing the smallest scales but still introduced instability when incorporated into an actual LES.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, Qi Chen, and Zhiwei Han
Geosci. Model Dev., 14, 3741–3768, https://doi.org/10.5194/gmd-14-3741-2021, https://doi.org/10.5194/gmd-14-3741-2021, 2021
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WRF-GC is an online coupling of the WRF meteorological model and GEOS-Chem chemical transport model for regional atmospheric chemistry and air quality modeling. In WRF-GC v2.0, we implemented the aerosol–radiation interactions and aerosol–cloud interactions, as well as the capability to nest multiple domains for high-resolution simulations based on the modular framework of WRF-GC v1.0. This allows the GEOS-Chem users to investigate the meteorology–atmospheric chemistry interactions.
Robin D. Lamboll, Chris D. Jones, Ragnhild B. Skeie, Stephanie Fiedler, Bjørn H. Samset, Nathan P. Gillett, Joeri Rogelj, and Piers M. Forster
Geosci. Model Dev., 14, 3683–3695, https://doi.org/10.5194/gmd-14-3683-2021, https://doi.org/10.5194/gmd-14-3683-2021, 2021
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Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions. We can estimate the changes in emissions at a country level, but to make predictions about how this will affect our climate, we need more precise information about where the emissions happen. Here we combine older estimates of where emissions normally occur with very recent estimates of sector activity levels to enable different groups to make simulations of the climatic effects of lockdown.
Nina Črnivec and Bernhard Mayer
Geosci. Model Dev., 14, 3663–3682, https://doi.org/10.5194/gmd-14-3663-2021, https://doi.org/10.5194/gmd-14-3663-2021, 2021
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This study aims to advance the cloud–radiation interplay treatment in global weather and climate prediction, focusing on cloud horizontal inhomogeneity misrepresentation. We explore the potential of the Tripleclouds method for diverse cloud types, namely the stratocumulus, cirrus and cumulonimbus. The validity of global cloud variability estimate with various condensate distribution assumptions is assessed. Optimizations for overcast and extremely heterogeneous cloudiness are further endorsed.
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
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A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
Sarah Sparrow, Andrew Bowery, Glenn D. Carver, Marcus O. Köhler, Pirkka Ollinaho, Florian Pappenberger, David Wallom, and Antje Weisheimer
Geosci. Model Dev., 14, 3473–3486, https://doi.org/10.5194/gmd-14-3473-2021, https://doi.org/10.5194/gmd-14-3473-2021, 2021
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This paper describes how the research version of the European Centre for Medium-Range Weather Forecasts’ Integrated Forecast System is combined with climateprediction.net’s public volunteer computing resource to develop OpenIFS@home. Thousands of volunteer personal computers simulated slightly different realizations of Tropical Cyclone Karl to demonstrate the performance of the large-ensemble forecast. OpenIFS@Home offers researchers a new tool to study weather forecasts and related questions.
Guillaume Monteil and Marko Scholze
Geosci. Model Dev., 14, 3383–3406, https://doi.org/10.5194/gmd-14-3383-2021, https://doi.org/10.5194/gmd-14-3383-2021, 2021
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LUMIA is a Python library for atmospheric inversions, originally developed at Lund University to perform regional atmospheric CO2 inversions. The inversions rely on coupling the regional transport model FLEXPART and the global transport model TM5. The paper presents the modeling setup and some first results, and it introduces the LUMIA Python package as a toolbox for inversions beyond the use case presented in the paper.
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., 14, 3407–3420, https://doi.org/10.5194/gmd-14-3407-2021, https://doi.org/10.5194/gmd-14-3407-2021, 2021
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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 aspect of atmospheric modeling.
Tobias Gronemeier, Kerstin Surm, Frank Harms, Bernd Leitl, Björn Maronga, and Siegfried Raasch
Geosci. Model Dev., 14, 3317–3333, https://doi.org/10.5194/gmd-14-3317-2021, https://doi.org/10.5194/gmd-14-3317-2021, 2021
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We demonstrate the capability of the PALM model system version 6.0 to simulate urban boundary layers. The studied situation includes a real-world building setup of the HafenCity area in Hamburg, Germany. We evaluate the simulation results against wind-tunnel measurements utilizing PALM's virtual measurement module. The comparison reveals an overall high agreement between simulation results and wind-tunnel measurements including mean wind speed and direction as well as turbulence statistics.
Timothy Glotfelty, Diana Ramírez-Mejía, Jared Bowden, Adrian Ghilardi, and J. Jason West
Geosci. Model Dev., 14, 3215–3249, https://doi.org/10.5194/gmd-14-3215-2021, https://doi.org/10.5194/gmd-14-3215-2021, 2021
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Land use and land cover change is a major contributor to climate change in Africa. Here we document deficiencies in how a weather model represents the land surface of Africa and how we modify a common land surface model to overcome these deficiencies. Our tests reveal that the default weather model does not accurately predict and transition the properties of different African biomes and growing cycles. This paper demonstrates that our modified model addresses these limitations.
Mario Eduardo Gavidia-Calderón, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade
Geosci. Model Dev., 14, 3251–3268, https://doi.org/10.5194/gmd-14-3251-2021, https://doi.org/10.5194/gmd-14-3251-2021, 2021
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The MUNICH model was used to calculate pollutant concentrations inside the streets of São Paulo. The VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the street rooftops. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.
Xiaoli G. Larsén and Jana Fischereit
Geosci. Model Dev., 14, 3141–3158, https://doi.org/10.5194/gmd-14-3141-2021, https://doi.org/10.5194/gmd-14-3141-2021, 2021
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For the first time, turbulent 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 the Fitch et al. (2012) scheme. We examined the effect of farm-induced TKE advection in connection with the Fitch scheme. Through a case study with a low-level jet (LLJ), we analyzed the key features of LLJs and raised the issue of interaction between wind farms and LLJs.
Pavel Krč, Jaroslav Resler, Matthias Sühring, Sebastian Schubert, Mohamed H. Salim, and Vladimír Fuka
Geosci. Model Dev., 14, 3095–3120, https://doi.org/10.5194/gmd-14-3095-2021, https://doi.org/10.5194/gmd-14-3095-2021, 2021
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The adverse effects of an urban environment, e.g. heat stress and air pollution, pose a risk to health and well-being. Precise modelling of the urban climate is crucial to mitigate these effects. Conventional atmospheric models are inadequate for modelling the complex structures of the urban environment; in particular, they lack a 3-D model of radiation and its interaction with surfaces and the plant canopy. The new RTM simulates these processes within the PALM-4U urban climate model.
Tao Zheng, Sha Feng, Kenneth J. Davis, Sandip Pal, and Josep-Anton Morguí
Geosci. Model Dev., 14, 3037–3066, https://doi.org/10.5194/gmd-14-3037-2021, https://doi.org/10.5194/gmd-14-3037-2021, 2021
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Carbon dioxide is the most important greenhouse gas. We develop the numerical model that represents carbon dioxide transport in the atmosphere. This model development is based on the MPAS model, which has a variable-resolution capability. The purpose of developing carbon dioxide transport in MPAS is to allow for high-resolution transport model simulation that is not limited by the lateral boundaries. It will also form the base for a future development of MPAS-based carbon inversion system.
Audrey Fortems-Cheiney, Isabelle Pison, Grégoire Broquet, Gaëlle Dufour, Antoine Berchet, Elise Potier, Adriana Coman, Guillaume Siour, and Lorenzo Costantino
Geosci. Model Dev., 14, 2939–2957, https://doi.org/10.5194/gmd-14-2939-2021, https://doi.org/10.5194/gmd-14-2939-2021, 2021
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Up-to-date and accurate emission inventories for air pollutants are essential for understanding their role in the formation of tropospheric ozone and particulate matter, for anticipating pollution peaks and for identifying the key drivers that could help mitigate their emissions. Complementarily with bottom-up inventories, the system described here aims at updating and improving the knowledge on the high spatiotemporal variability of emissions of air pollutants.
James Hocking, Jérôme Vidot, Pascal Brunel, Pascale Roquet, Bruna Silveira, Emma Turner, and Cristina Lupu
Geosci. Model Dev., 14, 2899–2915, https://doi.org/10.5194/gmd-14-2899-2021, https://doi.org/10.5194/gmd-14-2899-2021, 2021
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RTTOV is a fast radiative transfer model for simulating passive satellite-based observations at visible, infrared, 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.
K. Wyat Appel, Jesse O. Bash, Kathleen M. Fahey, Kristen M. Foley, Robert C. Gilliam, Christian Hogrefe, William T. Hutzell, Daiwen Kang, Rohit Mathur, Benjamin N. Murphy, Sergey L. Napelenok, Christopher G. Nolte, Jonathan E. Pleim, George A. Pouliot, Havala O. T. Pye, Limei Ran, Shawn J. Roselle, Golam Sarwar, Donna B. Schwede, Fahim I. Sidi, Tanya L. Spero, and David C. Wong
Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, https://doi.org/10.5194/gmd-14-2867-2021, 2021
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This paper details the scientific updates in the recently released CMAQ version 5.3 (and v5.3.1) and also includes operational and diagnostic evaluations of CMAQv5.3.1 against observations and the previous version of the CMAQ (v5.2.1). This work was done to improve the underlying science in CMAQ. This article is used to inform the CMAQ modeling community of the updates to the modeling system and the expected change in model performance from these updates (versus the previous model version).
Ziyu Huang, Lei Zhong, Yaoming Ma, and Yunfei Fu
Geosci. Model Dev., 14, 2827–2841, https://doi.org/10.5194/gmd-14-2827-2021, https://doi.org/10.5194/gmd-14-2827-2021, 2021
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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 driving fields over the Tibetan Plateau (TP) would possibly introduce extra biases when spectral nudging is applied. The results show that the precipitation simulations were significantly improved when limiting the application of spectral nudging toward the potential temperature and water vapor mixing ratio over the TP.
Eve-Agnès Fiorentino, Henri Wortham, and Karine Sartelet
Geosci. Model Dev., 14, 2747–2780, https://doi.org/10.5194/gmd-14-2747-2021, https://doi.org/10.5194/gmd-14-2747-2021, 2021
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Indoor air quality (IAQ) is strongly influenced by reactivity with surfaces, which is called heterogeneous reactivity. To date, this reactivity is barely integrated into numerical models due to the strong uncertainties it is subjected to. In this work, an open-source IAQ model, called the H2I model, is developed to consider both gas-phase and heterogeneous reactivity and simulate indoor concentrations of inorganic compounds.
Yann Cohen, Virginie Marécal, Béatrice Josse, and Valérie Thouret
Geosci. Model Dev., 14, 2659–2689, https://doi.org/10.5194/gmd-14-2659-2021, https://doi.org/10.5194/gmd-14-2659-2021, 2021
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Assessing long-term chemistry–climate simulations with in situ and frequent observations near the tropopause is possible with the IAGOS commercial aircraft data set. This study presents a method that distributes the IAGOS data (ozone and CO) on a monthly model grid, limiting the impact of resolution for the evaluation of the modelled chemical fields. We applied it to the CCMI REF-C1SD simulation from the MOCAGE CTM and notably highlighted well-reproduced O3 behaviour in the lower stratosphere.
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.
James Weber, Scott Archer-Nicholls, Nathan Luke Abraham, Youngsub Matthew Shin, Thomas J. Bannan, Carl J. Percival, Asan Bacak, Paulo Artaxo, Michael Jenkin, M. Anwar H. Khan, Dudley E. Shallcross, Rebecca H. Schwantes, Jonathan Williams, and Alex T. Archibald
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-119, https://doi.org/10.5194/gmd-2021-119, 2021
Revised manuscript accepted for GMD
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The new mechanism CRI-Strat 2 features state-of-the-art isoprene chemistry, not previously available in UKCA, and improves UKCA’s ability to reproduce observed concentrations of isoprene, monoterpenes and OH in tropical regions. The enhanced ability to model isoprene, the most widely emitted non-methane volatile organic compound, will facilitate improved understanding into how isoprene and other BVOCs affect atmospheric composition and, through biosphere-atmosphere feedbacks, climate change.
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.
Lin Huang, Song Liu, Zeyuan Yang, Jia Xing, Jia Zhang, Jiang Bian, Siwei Li, Shovan Kumar Sahu, Shuxiao Wang, and Tie-Yan Liu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-80, https://doi.org/10.5194/gmd-2021-80, 2021
Revised manuscript accepted for GMD
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Accurate estimation of emissions is the prerequisite for effectively controlling air pollution, while current methods either lack sufficient data or representation of nonlinearity. Here we proposed a novel deep learning method to model the dual relationship between emission and pollutant concentration. The emission can be updated through backpropagating the gradient of the loss function measuring the deviation between simulations and observations, resulting in a better model performance.
Edward C. Chan and Timothy M. Butler
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-432, https://doi.org/10.5194/gmd-2020-432, 2021
Revised manuscript accepted for GMD
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A large-eddy simulation based chemical transport model is implemented for an idealized street canyon. The dynamics of the model are evaluated using stationary measurements. A transient model run is also conducted over a 24-hour period, where variations of pollutant concentrations indicate dependence on emissions, background concentrations, and solar state. Comparison stationary model runs show changes in flow structures concentrations.
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.
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Short summary
Aerosol–cloud interactions are the largest contributor to climate forcing uncertainty. In this study we combine two common approaches to aerosol representation in global models: a sectional scheme, which is closer to first principals, for the smallest particles forming in the atmosphere and a log-modal scheme, which is faster, for the larger particles. With this approach, we improve the aerosol representation compared to observations, while only increasing the computational cost by 15 %.
Aerosol–cloud interactions are the largest contributor to climate forcing uncertainty. In this...
