Articles | Volume 10, issue 2
https://doi.org/10.5194/gmd-10-903-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-903-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
23 Feb 2017
Development and technical paper |
| 23 Feb 2017
Implementation of the MEGAN (v2.1) biogenic emission model in the ECHAM6-HAMMOZ chemistry climate model
Alexandra-Jane Henrot
CORRESPONDING AUTHOR
Forschungszentrum Jülich GmbH, IEK-8:Troposphere, Jülich, Germany
Unité de Modélisation du Climat et des Cycles Biogéochimiques, University of Liège, Liège, Belgium
Tanja Stanelle
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sabine Schröder
Forschungszentrum Jülich GmbH, IEK-8:Troposphere, Jülich, Germany
Colombe Siegenthaler
Center for Climate System Modelling, ETH Zurich, Zurich, Switzerland
Domenico Taraborrelli
Forschungszentrum Jülich GmbH, IEK-8:Troposphere, Jülich, Germany
Martin G. Schultz
Forschungszentrum Jülich GmbH, IEK-8:Troposphere, Jülich, Germany
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Felix Kleinert, Lukas H. Leufen, and Martin G. Schultz
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Martine G. de Vos, Wilco Hazeleger, Driss Bari, Jörg Behrens, Sofiane Bendoukha, Irene Garcia-Marti, Ronald van Haren, Sue Ellen Haupt, Rolf Hut, Fredrik Jansson, Andreas Mueller, Peter Neilley, Gijs van den Oord, Inti Pelupessy, Paolo Ruti, Martin G. Schultz, and Jeremy Walton
Geosci. Commun., 3, 191–201, https://doi.org/10.5194/gc-3-191-2020, https://doi.org/10.5194/gc-3-191-2020, 2020
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Simon Rosanka, Giang H. T. Vu, Hue M. T. Nguyen, Tien V. Pham, Umar Javed, Domenico Taraborrelli, and Luc Vereecken
Atmos. Chem. Phys., 20, 6671–6686, https://doi.org/10.5194/acp-20-6671-2020, https://doi.org/10.5194/acp-20-6671-2020, 2020
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Vincent Huijnen, Kazuyuki Miyazaki, Johannes Flemming, Antje Inness, Takashi Sekiya, and Martin G. Schultz
Geosci. Model Dev., 13, 1513–1544, https://doi.org/10.5194/gmd-13-1513-2020, https://doi.org/10.5194/gmd-13-1513-2020, 2020
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Anna Novelli, Luc Vereecken, Birger Bohn, Hans-Peter Dorn, Georgios I. Gkatzelis, Andreas Hofzumahaus, Frank Holland, David Reimer, Franz Rohrer, Simon Rosanka, Domenico Taraborrelli, Ralf Tillmann, Robert Wegener, Zhujun Yu, Astrid Kiendler-Scharr, Andreas Wahner, and Hendrik Fuchs
Atmos. Chem. Phys., 20, 3333–3355, https://doi.org/10.5194/acp-20-3333-2020, https://doi.org/10.5194/acp-20-3333-2020, 2020
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David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Philip Stier, Daniel G. Partridge, Ina Tegen, Isabelle Bey, Tanja Stanelle, Harri Kokkola, and Ulrike Lohmann
Geosci. Model Dev., 12, 3609–3639, https://doi.org/10.5194/gmd-12-3609-2019, https://doi.org/10.5194/gmd-12-3609-2019, 2019
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Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
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Ina Tegen, David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Isabelle Bey, Nick Schutgens, Philip Stier, Duncan Watson-Parris, Tanja Stanelle, Hauke Schmidt, Sebastian Rast, Harri Kokkola, Martin Schultz, Sabine Schroeder, Nikos Daskalakis, Stefan Barthel, Bernd Heinold, and Ulrike Lohmann
Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019, https://doi.org/10.5194/gmd-12-1643-2019, 2019
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We describe a new version of the aerosol–climate model ECHAM–HAM and show tests of the model performance by comparing different aspects of the aerosol distribution with different datasets. The updated version of HAM contains improved descriptions of aerosol processes, including updated emission fields and cloud processes. While there are regional deviations between the model and observations, the model performs well overall.
Rolf Sander, Andreas Baumgaertner, David Cabrera-Perez, Franziska Frank, Sergey Gromov, Jens-Uwe Grooß, Hartwig Harder, Vincent Huijnen, Patrick Jöckel, Vlassis A. Karydis, Kyle E. Niemeyer, Andrea Pozzer, Hella Riede, Martin G. Schultz, Domenico Taraborrelli, and Sebastian Tauer
Geosci. Model Dev., 12, 1365–1385, https://doi.org/10.5194/gmd-12-1365-2019, https://doi.org/10.5194/gmd-12-1365-2019, 2019
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We present the atmospheric chemistry box model CAABA/MECCA which
now includes a number of new features: skeletal mechanism
reduction, the MOM chemical mechanism for volatile organic
compounds, an option to include reactions from the Master
Chemical Mechanism (MCM) and other chemical mechanisms, updated
isotope tagging, improved and new photolysis modules, and the new
feature of coexisting multiple chemistry mechanisms.
CAABA/MECCA is a community model published under the GPL.
Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
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We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Arlene M. Fiore, Emily V. Fischer, George P. Milly, Shubha Pandey Deolal, Oliver Wild, Daniel A. Jaffe, Johannes Staehelin, Olivia E. Clifton, Dan Bergmann, William Collins, Frank Dentener, Ruth M. Doherty, Bryan N. Duncan, Bernd Fischer, Stefan Gilge, Peter G. Hess, Larry W. Horowitz, Alexandru Lupu, Ian A. MacKenzie, Rokjin Park, Ludwig Ries, Michael G. Sanderson, Martin G. Schultz, Drew T. Shindell, Martin Steinbacher, David S. Stevenson, Sophie Szopa, Christoph Zellweger, and Guang Zeng
Atmos. Chem. Phys., 18, 15345–15361, https://doi.org/10.5194/acp-18-15345-2018, https://doi.org/10.5194/acp-18-15345-2018, 2018
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We demonstrate a proof-of-concept approach for applying northern midlatitude mountaintop peroxy acetyl nitrate (PAN) measurements and a multi-model ensemble during April to constrain the influence of continental-scale anthropogenic precursor emissions on PAN. Our findings imply a role for carefully coordinated multi-model ensembles in helping identify observations for discriminating among widely varying (and poorly constrained) model responses of atmospheric constituents to changes in emissions.
Harri Kokkola, Thomas Kühn, Anton Laakso, Tommi Bergman, Kari E. J. Lehtinen, Tero Mielonen, Antti Arola, Scarlet Stadtler, Hannele Korhonen, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Ina Tegen, Colombe Siegenthaler-Le Drian, Martin G. Schultz, Isabelle Bey, Philip Stier, Nikos Daskalakis, Colette L. Heald, and Sami Romakkaniemi
Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, https://doi.org/10.5194/gmd-11-3833-2018, 2018
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In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.
Scarlet Stadtler, Thomas Kühn, Sabine Schröder, Domenico Taraborrelli, Martin G. Schultz, and Harri Kokkola
Geosci. Model Dev., 11, 3235–3260, https://doi.org/10.5194/gmd-11-3235-2018, https://doi.org/10.5194/gmd-11-3235-2018, 2018
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Atmospheric aerosols interact with our climate system and have adverse health effects. Nevertheless, these particles are a source of uncertainty in climate projections and the formation process of secondary aerosols formed by organic gas-phase precursors is particularly not fully understood. In order to gain a deeper understanding of secondary organic aerosol formation, this model system explicitly represents gas-phase and aerosol formation processes. Finally, this allows for process discussion.
Chinmay Mallik, Laura Tomsche, Efstratios Bourtsoukidis, John N. Crowley, Bettina Derstroff, Horst Fischer, Sascha Hafermann, Imke Hüser, Umar Javed, Stephan Keßel, Jos Lelieveld, Monica Martinez, Hannah Meusel, Anna Novelli, Gavin J. Phillips, Andrea Pozzer, Andreas Reiffs, Rolf Sander, Domenico Taraborrelli, Carina Sauvage, Jan Schuladen, Hang Su, Jonathan Williams, and Hartwig Harder
Atmos. Chem. Phys., 18, 10825–10847, https://doi.org/10.5194/acp-18-10825-2018, https://doi.org/10.5194/acp-18-10825-2018, 2018
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OH and HO2 control the transformation of air pollutants and O3 formation. Their implication for air quality over the climatically sensitive Mediterranean region was studied during a field campaign in Cyprus. Production of OH, HO2, and recycled OH was lower in aged marine air masses. Box model simulations of OH and HO2 agreed with measurements except at high terpene concentrations when model RO2 due to terpenes caused large HO2 loss. Autoxidation schemes for RO2 improved the agreement.
Martin G. Schultz, Scarlet Stadtler, Sabine Schröder, Domenico Taraborrelli, Bruno Franco, Jonathan Krefting, Alexandra Henrot, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Colombe Siegenthaler-Le Drian, Sebastian Wahl, Harri Kokkola, Thomas Kühn, Sebastian Rast, Hauke Schmidt, Philip Stier, Doug Kinnison, Geoffrey S. Tyndall, John J. Orlando, and Catherine Wespes
Geosci. Model Dev., 11, 1695–1723, https://doi.org/10.5194/gmd-11-1695-2018, https://doi.org/10.5194/gmd-11-1695-2018, 2018
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The chemistry–climate model ECHAM-HAMMOZ contains a detailed representation of tropospheric and stratospheric reactive chemistry and state-of-the-art parameterizations of aerosols. It thus allows for detailed investigations of chemical processes in the climate system. Evaluation of the model with various observational data yields good results, but the model has a tendency to produce too much OH in the tropics. This highlights the important interplay between atmospheric chemistry and dynamics.
Scarlet Stadtler, David Simpson, Sabine Schröder, Domenico Taraborrelli, Andreas Bott, and Martin Schultz
Atmos. Chem. Phys., 18, 3147–3171, https://doi.org/10.5194/acp-18-3147-2018, https://doi.org/10.5194/acp-18-3147-2018, 2018
David Cabrera-Perez, Domenico Taraborrelli, Jos Lelieveld, Thorsten Hoffmann, and Andrea Pozzer
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-928, https://doi.org/10.5194/acp-2017-928, 2017
Revised manuscript not accepted
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Aromatic compounds are present in rural and urban atmospheres. The aim of this work is to disentangle the impacts of these compounds in different important atmospheric chemical species with the help of a numerical model. Aromatics have low impact OH, NOx and Ozone concentrations in the global scale (below 4 %). The impact however is larger in the regional scale (up to 10 %). The largest impact is in glyoxal and NO3 concentrations, with changes up to 10 % globally and 40 % regionally.
Florian Berkes, Patrick Neis, Martin G. Schultz, Ulrich Bundke, Susanne Rohs, Herman G. J. Smit, Andreas Wahner, Paul Konopka, Damien Boulanger, Philippe Nédélec, Valerie Thouret, and Andreas Petzold
Atmos. Chem. Phys., 17, 12495–12508, https://doi.org/10.5194/acp-17-12495-2017, https://doi.org/10.5194/acp-17-12495-2017, 2017
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This study highlights the importance of independent global measurements with high and long-term accuracy to quantify long-term changes, especially in the UTLS region, and to help identify inconsistencies between different data sets of observations and models. Here we investigated temperature trends over different regions within a climate-sensitive area of the atmosphere and demonstrated the value of the IAGOS temperature observations as an anchor point for the evaluation of reanalyses.
Stephan Keßel, David Cabrera-Perez, Abraham Horowitz, Patrick R. Veres, Rolf Sander, Domenico Taraborrelli, Maria Tucceri, John N. Crowley, Andrea Pozzer, Christof Stönner, Luc Vereecken, Jos Lelieveld, and Jonathan Williams
Atmos. Chem. Phys., 17, 8789–8804, https://doi.org/10.5194/acp-17-8789-2017, https://doi.org/10.5194/acp-17-8789-2017, 2017
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In this study we identify an often overlooked stable oxide of carbon, namely carbon suboxide (C3O2), in ambient air. We have made C3O2 and in the laboratory determined its absorption cross section data and the rate of reaction with two important atmospheric oxidants, OH and O3. By incorporating known sources and sinks in a global model we have generated a first global picture of the distribution of this species in the atmosphere.
David Cabrera-Perez, Domenico Taraborrelli, Rolf Sander, and Andrea Pozzer
Atmos. Chem. Phys., 16, 6931–6947, https://doi.org/10.5194/acp-16-6931-2016, https://doi.org/10.5194/acp-16-6931-2016, 2016
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The global atmospheric budget and distribution of monocyclic aromatic compounds is estimated, using an atmospheric chemistry general circulation model. Simulation results are evaluated with observations with the goal of understanding emission, production and removal of these compounds. Anthropogenic and biomass burning are the main sources of aromatic compounds to the atmosphere. The main sink is photochemical decomposition and in lesser importance dry deposition.
Olga Lyapina, Martin G. Schultz, and Andreas Hense
Atmos. Chem. Phys., 16, 6863–6881, https://doi.org/10.5194/acp-16-6863-2016, https://doi.org/10.5194/acp-16-6863-2016, 2016
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This study applies numerical clustering for the classification of about 1500 ozone data sets in Europe. We show the usefulness of cluster analysis (CA) for the quantitative evaluation of a global model: pre-selection of stations and validation of a global model in a phase-space produce clearer and more interpretable results. CA can be easily updated for new stations, different length of data, and other type of input properties, as well as other type of data (for example, meteorological).
Sabine Egerer, Martin Claussen, Christian Reick, and Tanja Stanelle
Clim. Past, 12, 1009–1027, https://doi.org/10.5194/cp-12-1009-2016, https://doi.org/10.5194/cp-12-1009-2016, 2016
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We demonstrate for the first time the direct link between dust accumulation in marine sediment cores and Saharan land surface by simulating the mid-Holocene and pre-industrial dust cycle as a function of Saharan land surface cover and atmosphere-ocean conditions using the coupled atmosphere-aerosol model ECHAM6-HAM2.1. Mid-Holocene surface characteristics, including vegetation cover and lake surface area, are derived from proxy data and simulations.
H. Eskes, V. Huijnen, A. Arola, A. Benedictow, A.-M. Blechschmidt, E. Botek, O. Boucher, I. Bouarar, S. Chabrillat, E. Cuevas, R. Engelen, H. Flentje, A. Gaudel, J. Griesfeller, L. Jones, J. Kapsomenakis, E. Katragkou, S. Kinne, B. Langerock, M. Razinger, A. Richter, M. Schultz, M. Schulz, N. Sudarchikova, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Geosci. Model Dev., 8, 3523–3543, https://doi.org/10.5194/gmd-8-3523-2015, https://doi.org/10.5194/gmd-8-3523-2015, 2015
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The MACC project is preparing the operational atmosphere service of the European Copernicus Programme, and uses data assimilation to combine atmospheric models with available observations. Our paper provides an overview of the aerosol and trace gas validation activity of MACC. Topics are the validation requirements, the measurement data, the assimilation systems, the upgrade procedure, operational aspects and the scoring methods. A summary is provided of recent results, including special events.
S. Fadnavis, K. Semeniuk, M. G. Schultz, M. Kiefer, A. Mahajan, L. Pozzoli, and S. Sonbawane
Atmos. Chem. Phys., 15, 11477–11499, https://doi.org/10.5194/acp-15-11477-2015, https://doi.org/10.5194/acp-15-11477-2015, 2015
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The model and MIPAS satellite data show that there are three regions which contribute substantial pollution to the south Asian UTLS: the Asian summer monsoon (ASM), the North American monsoon (NAM) and the West African monsoon (WAM). However, penetration due to ASM convection reaches deeper into the UTLS compared to NAM and WAM outflow. Simulations show that westerly winds drive North American and European pollutants eastward where they can become part of the ASM and lifted to LS.
E. Katragkou, P. Zanis, A. Tsikerdekis, J. Kapsomenakis, D. Melas, H. Eskes, J. Flemming, V. Huijnen, A. Inness, M. G. Schultz, O. Stein, and C. S. Zerefos
Geosci. Model Dev., 8, 2299–2314, https://doi.org/10.5194/gmd-8-2299-2015, https://doi.org/10.5194/gmd-8-2299-2015, 2015
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This work is an extended evaluation of near-surface ozone as part of the global reanalysis of atmospheric composition, produced within the European-funded project MACC (Monitoring Atmospheric Composition and Climate). It includes an evaluation over the period 2003-2012 and provides an overall assessment of the modelling system performance with respect to near surface ozone for specific European subregions.
H. Fischer, A. Pozzer, T. Schmitt, P. Jöckel, T. Klippel, D. Taraborrelli, and J. Lelieveld
Atmos. Chem. Phys., 15, 6971–6980, https://doi.org/10.5194/acp-15-6971-2015, https://doi.org/10.5194/acp-15-6971-2015, 2015
A. Inness, A.-M. Blechschmidt, I. Bouarar, S. Chabrillat, M. Crepulja, R. J. Engelen, H. Eskes, J. Flemming, A. Gaudel, F. Hendrick, V. Huijnen, L. Jones, J. Kapsomenakis, E. Katragkou, A. Keppens, B. Langerock, M. de Mazière, D. Melas, M. Parrington, V. H. Peuch, M. Razinger, A. Richter, M. G. Schultz, M. Suttie, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Atmos. Chem. Phys., 15, 5275–5303, https://doi.org/10.5194/acp-15-5275-2015, https://doi.org/10.5194/acp-15-5275-2015, 2015
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The paper presents results from data assimilation studies with the new Composition-IFS model developed in the MACC project. This system was used in MACC to produce daily analyses and 5-day forecasts of atmospheric composition and is now run daily in the EU’s Copernicus Atmosphere Monitoring Service. The paper looks at the quality of the CO, O3 and NO2 analysis fields obtained with this system, comparing them against observations, a control run and an older version of the model.
J. Flemming, V. Huijnen, J. Arteta, P. Bechtold, A. Beljaars, A.-M. Blechschmidt, M. Diamantakis, R. J. Engelen, A. Gaudel, A. Inness, L. Jones, B. Josse, E. Katragkou, V. Marecal, V.-H. Peuch, A. Richter, M. G. Schultz, O. Stein, and A. Tsikerdekis
Geosci. Model Dev., 8, 975–1003, https://doi.org/10.5194/gmd-8-975-2015, https://doi.org/10.5194/gmd-8-975-2015, 2015
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We describe modules for atmospheric chemistry, wet and dry deposition and lightning NO production, which have been newly introduced in ECMWF's weather forecasting model. With that model, we want to forecast global air pollution as part of the European Copernicus Atmosphere Monitoring Service. We show that the new model results compare as well or better with in situ and satellite observations of ozone, CO, NO2, SO2 and formaldehyde as the previous model.
R. Paugam, M. Wooster, J. Atherton, S. R. Freitas, M. G. Schultz, and J. W. Kaiser
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-9815-2015, https://doi.org/10.5194/acpd-15-9815-2015, 2015
Revised manuscript not accepted
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The transport of Biomass Burning emissions in Chemical Transport Model rely on parametrization of plumes injection height. Using fire observation selected to ensure match-up of fire-atmosphere-plume dynamics; a popular plume rise model was improved and optimized. The resulting model shows response to the effect of atmospheric stability consistent with previous findings and is able to predict higher injection height than any other tested parametrizations, giving a closer match with observation.
K. Lefever, R. van der A, F. Baier, Y. Christophe, Q. Errera, H. Eskes, J. Flemming, A. Inness, L. Jones, J.-C. Lambert, B. Langerock, M. G. Schultz, O. Stein, A. Wagner, and S. Chabrillat
Atmos. Chem. Phys., 15, 2269–2293, https://doi.org/10.5194/acp-15-2269-2015, https://doi.org/10.5194/acp-15-2269-2015, 2015
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We validate and discuss the analyses of stratospheric ozone delivered in near-real time between 2009 and 2012 by four different data assimilation systems: IFS-MOZART, BASCOE, SACADA and TM3DAM. It is shown that the characteristics of the assimilation systems are much less important than those of the assimilated data sets. A correct representation of the vertical distribution of ozone requires satellite observations which are well resolved vertically and extend into the lowermost stratosphere.
S. Fadnavis, M. G. Schultz, K. Semeniuk, A. S. Mahajan, L. Pozzoli, S. Sonbawne, S. D. Ghude, M. Kiefer, and E. Eckert
Atmos. Chem. Phys., 14, 12725–12743, https://doi.org/10.5194/acp-14-12725-2014, https://doi.org/10.5194/acp-14-12725-2014, 2014
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The Asian summer monsoon transports pollutants from local emission sources to the upper troposphere and lower stratosphere (UTLS). The increasing trend of these pollutants may have climatic impact. This study addresses the impact of convectively lifted Indian and Chinese emissions on the ULTS. Sensitivity experiments with emission changes in particular regions show that Chinese emissions have a greater impact on the concentrations of NOY species than Indian emissions.
O. Stein, M. G. Schultz, I. Bouarar, H. Clark, V. Huijnen, A. Gaudel, M. George, and C. Clerbaux
Atmos. Chem. Phys., 14, 9295–9316, https://doi.org/10.5194/acp-14-9295-2014, https://doi.org/10.5194/acp-14-9295-2014, 2014
K. Hens, A. Novelli, M. Martinez, J. Auld, R. Axinte, B. Bohn, H. Fischer, P. Keronen, D. Kubistin, A. C. Nölscher, R. Oswald, P. Paasonen, T. Petäjä, E. Regelin, R. Sander, V. Sinha, M. Sipilä, D. Taraborrelli, C. Tatum Ernest, J. Williams, J. Lelieveld, and H. Harder
Atmos. Chem. Phys., 14, 8723–8747, https://doi.org/10.5194/acp-14-8723-2014, https://doi.org/10.5194/acp-14-8723-2014, 2014
S. Fadnavis, K. Semeniuk, M. G. Schultz, A. Mahajan, L. Pozzoli, S. Sonbawane, and M. Kiefer
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-20159-2014, https://doi.org/10.5194/acpd-14-20159-2014, 2014
Revised manuscript not accepted
A. Basu, M. G. Schultz, S. Schröder, L. Francois, X. Zhang, G. Lohmann, and T. Laepple
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-3193-2014, https://doi.org/10.5194/acpd-14-3193-2014, 2014
Revised manuscript not accepted
S. Fadnavis, K. Semeniuk, L. Pozzoli, M. G. Schultz, S. D. Ghude, S. Das, and R. Kakatkar
Atmos. Chem. Phys., 13, 8771–8786, https://doi.org/10.5194/acp-13-8771-2013, https://doi.org/10.5194/acp-13-8771-2013, 2013
A. Inness, F. Baier, A. Benedetti, I. Bouarar, S. Chabrillat, H. Clark, C. Clerbaux, P. Coheur, R. J. Engelen, Q. Errera, J. Flemming, M. George, C. Granier, J. Hadji-Lazaro, V. Huijnen, D. Hurtmans, L. Jones, J. W. Kaiser, J. Kapsomenakis, K. Lefever, J. Leitão, M. Razinger, A. Richter, M. G. Schultz, A. J. Simmons, M. Suttie, O. Stein, J.-N. Thépaut, V. Thouret, M. Vrekoussis, C. Zerefos, and the MACC team
Atmos. Chem. Phys., 13, 4073–4109, https://doi.org/10.5194/acp-13-4073-2013, https://doi.org/10.5194/acp-13-4073-2013, 2013
Related subject area
Atmospheric sciences
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
The ddeq Python library for point source quantification from remote sensing images (Version 1.0)
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
Investigating Ground-Level Ozone Pollution in Semi-Arid and Arid Regions of Arizona Using WRF-Chem v4.4 Modeling
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
FUME 2.0 – Flexible Universal processor for Modeling Emissions
Assessment of tropospheric ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Application of regional meteorology and air quality models based on MIPS CPU Platform
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
A General Comprehensive Evaluation Method for Cross-Scale Precipitation Forecasts
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter Notebooks included in the library.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2023-2613, https://doi.org/10.5194/egusphere-2023-2613, 2023
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By directly analysing the proximity of precipitation forecasts and observations, a precipitation forecast accuracy score (PAS) method was constructed. This method does not utilize the traditional contingency table-based classification verification, can replace the threat score (TS), equitable threat score (ETS) and other skill score methods, and can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Cited articles
Arneth, A., Niinemets, Ü., Pressley, S., Bäck, J., Hari, P., Karl, T., Noe, S., Prentice, I. C., Serça, D., Hickler, T., Wolf, A., and Smith, B.: Process-based estimates of terrestrial ecosystem isoprene emissions: incorporating the effects of a direct CO2-isoprene interaction, Atmos. Chem. Phys., 7, 31–53, https://doi.org/10.5194/acp-7-31-2007, 2007.
Arneth, A., Schurgers, G., Lathiere, J., Duhl, T., Beerling, D. J., Hewitt, C. N., Martin, M., and Guenther, A.: Global terrestrial isoprene emission models: sensitivity to variability in climate and vegetation, Atmos. Chem. Phys., 11, 8037–8052, https://doi.org/10.5194/acp-11-8037-2011, 2011.
Ashworth, K., Boissard, C., Folberth, G., Lathière, J., and Schurgers, G.: Global Modelling of Volatile Organic Compound Emissions, in: Biology, Controls and Models of Tree Volatile Organic Compound Emissions, edited by: Niinemets, U. and Monson, R. K., chap. 16, 451–489, Springer, Berlin, Germany, 2013.
Atkinson, R. and Arey, J.: Gas-phase tropospheric chemistry of biogenic volatile organic compounds: a review, Atmos. Environ., 37, 197–219, 2003.
Brovkin, V., Raddatz, T., Reick, C., Claussen, M., and Gayler, V.: Global biogeophysical interactions between forest and climate, Geophys. Res. Lett., 36, L07405, https://doi.org/10.1029/2009GL037543, 2009.
Brovkin, V., Boysen, L., Raddatz, T., Gayler, V., Loew, A., and Claussen, M.: Evaluation of vegetation cover and land-surface albedo in MPI-ESM CMIP5 simulations, J. Adv. Model. Earth Syst., 5, 48–57, 2013.
Cabrera-Perez, D., Taraborrelli, D., Sander, R., and Pozzer, A.: Global atmospheric budget of simple monocyclic aromatic compounds, Atmos. Chem. Phys., 16, 6931–6947, https://doi.org/10.5194/acp-16-6931-2016, 2016.
Collins, W. J., Derwent, R. G., Johnson, C. E., and Stevenson, D. S.: The oxidation of organic compounds in the troposphere and their global warming potentials, Climatic Change, 52, 453–479, 2002.
Constable, J. V. H., Litvak, M. E., Greenberg, J. P., and Monson, R. K.: Monoterpene emission from coniferous trees in response to elevated CO2 concentration and climate warming, Glob. Change Biol., 5, 255–267, 1999.
Crippa, M., Janssens-Maenhout, G., Dentener, F., Guizzardi, D., Sindelarova, K., Muntean, M., Van Dingenen, R., and Granier, C.: Forty years of improvements in European air quality: regional policy-industry interactions with global impacts, Atmos. Chem. Phys., 16, 3825–3841, https://doi.org/10.5194/acp-16-3825-2016, 2016.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Khöler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc. A, 137, 553–597, 2011.
Emmons, L. K., Walters, S., Hess, P. G., Lamarque, J.-F., Pfister, G. G., Fillmore, D., Granier, C., Guenther, A., Kinnison, D., Laepple, T., Orlando, J., Tie, X., Tyndall, G., Wiedinmyer, C., Baughcum, S. L., and Kloster, S.: Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4), Geosci. Model Dev., 3, 43–67, https://doi.org/10.5194/gmd-3-43-2010, 2010.
Fischer, E. V., Jacob, D. J., Millet, D. B., Yantosca, R. M., and Mao, J.: The role of the ocean in the global atmospheric budget of acetone, Geophys. Res. Lett., 39, L01807, https://doi.org/10.1029/2011GL050086, 2012.
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Syst., 5, 572–597, 2012.
Granier, C., Pétron, G., Müller, J.-F., and Brasseur, G.: The impact of natural and anthropogenic hydrocarbons on the tropospheric budget of carbon monoxide, Atmos. Environ., 34, 5255–5270, 2000.
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006.
Guenther, A. B., Zimmerman, P. R., Harley, P. C., Monson, R. K., and Fall, R.: Isoprene and monoterpene emission rate variability: Model evaluations and sensitivity analyses, J. Geophys. Res., 98, 12609–12617, 1993.
Guenther, A. B., Hewitt, C. N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., Mckay, W. A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., and Zimmerman, P.: A global model of natural volatile organic compound emissions, J. Geophys. Res., 100, 8873–8892, 1995.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Hagemann, S. and Stacke, T.: Impact of the soil hydrology scheme on simulated soil moisture memory, Clim. Dynam., 44, 1731, https://doi.org/10.1007/s00382-014-2221-6, 2015.
Hallquist, M., Wenger, J. C., Baltensperger, U., Rudich, Y., Simpson, D., Claeys, M., Dommen, J., Donahue, N. M., George, C., Goldstein, A. H., Hamilton, J. F., Herrmann, H., Hoffmann, T., Iinuma, Y., Jang, M., Jenkin, M. E., Jimenez, J. L., Kiendler-Scharr, A., Maenhaut, W., McFiggans, G., Mentel, Th. F., Monod, A., Prévôt, A. S. H., Seinfeld, J. H., Surratt, J. D., Szmigielski, R., and Wildt, J.: The formation, properties and impact of secondary organic aerosol: current and emerging issues, Atmos. Chem. Phys., 9, 5155–5236, https://doi.org/10.5194/acp-9-5155-2009, 2009.
Heald, C. L., Henze, D. K., Horowitz, L. W., Feddema, J., Lamarque, J.-F., Guenther, A., Hess, P. G., Vitt, F., Seinfeld, J. H., Goldstein, A. H., and Fung, I.: Predicted change in global secondary organic aerosol concentrations in response to future climate, emissions, and land use change, J. Geophys. Res., 113, D05211, https://doi.org/10.1029/2007JD009092, 2008.
Heald, C. L., Wilkinson, M. J., Monson, R. K., Alo, C. A., Wang, G., and Guenther, A.: Response of isoprene emission to ambient CO2 changes and implications for global budgets, Glob. Change Biol., 15, 1127–1140, 2009.
Jacob, D. J., Field, B. D., Jin, E. M., Bey, I., Li, Q., Logan, J. A., and Yantosca, R. M.: Atmospheric budget of acetone, J. Geophys. Res., 107, D104100, https://doi.org/10.1029/2001JD000694, 2002.
Jacob, D. J., Field, B. D., Li, Q., Blake, D. R., de Gouw, J., Warneke, C., Hansel, A., Wisthaler, A., Singh, H. B., and Guenther, A.: Global budget of methanol: Constraints from atmospheric observations, J. Geophys. Res., 110, D08303, https://doi.org/10.1029/2004JD005172, 2005.
Lamarque, J.-F., Emmons, L. K., Hess, P. G., Kinnison, D. E., Tilmes, S., Vitt, F., Heald, C. L., Holland, E. A., Lauritzen, P. H., Neu, J., Orlando, J. J., Rasch, P. J., and Tyndall, G. K.: CAM-chem: description and evaluation of interactive atmospheric chemistry in the Community Earth System Model, Geosci. Model Dev., 5, 369–411, https://doi.org/10.5194/gmd-5-369-2012, 2012.
Lathière, J., Hauglustaine, D. A., Friend, A. D., De Noblet-Ducoudré, N., Viovy, N., and Folberth, G. A.: Impact of climate variability and land use changes on global biogenic volatile organic compound emissions, Atmos. Chem. Phys., 6, 2129–2146, https://doi.org/10.5194/acp-6-2129-2006, 2006.
Lathière, J., Hewitt, C. N., and Beerling, D. J.: Sensitivity of isoprene emissions from the terrestrial biosphere to 20th century changes in atmospheric CO2 concentration, climate, and land use, Global Biogeochem. Cy., 24, GB1004, https://doi.org/10.1029/2009GB003548, 2010.
Lawrence, D. M. and Chase, T. N.: Representing a new MODIS consistent land surface in the Community Land Model (CLM 3.0), J. Geophys. Res., 112, G01023, https://doi.org/10.1029/2006JG000168, 2007.
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson, S. C., Lawrence, P. J., Zeng, X., Yang, Z.-L., Levis, S., Sakaguchi, K., Bonan, G. B., and Slater, A. G.: Parameterization improvements and functional and structural advances in version 4 of the Community Land Model, J. Adv. Model. Earth Syst., 3, M03001, https://doi.org/10.1029/2011MS00045, 2011.
Levis, S., Wiedinmyer, C., Bonan, G. B., and Guenther, A.: Simulating biogenic volatile organic compound emissions in the Community Climate System Model, J. Geophys. Res., 108, 4659, https://doi.org/10.1029/2002JD003203, 2003.
Levis, S., Bonan, G. B., Vertenstein, M., and Oleson, K. W.: The Community Land Model's Dynamic Global Vegetation Model (CLM-DGVM): Technical Description and User's Guide, Tech. Rep. NCAR/TN-459+IA, NCAR, Boulder, Colorado, USA, 2004.
Li, Z. and Sharkey, T. D.: Molecular and pathway controls on biogenic volatile organic compound emissions, in: Biology, Controls and Models of Tree Volatile Organic Compound Emissions, edited by: Niinemets, U. and Monson, R. K., chap. 5, 119–151, Springer, Berlin, Germany, 2013.
Lohmann, U. and Ferrachat, S.: Impact of parametric uncertainties on the present-day climate and on the anthropogenic aerosol effect, Atmos. Chem. Phys., 10, 11373–11383, https://doi.org/10.5194/acp-10-11373-2010, 2010.
Lohmann, U. and Hoose, C.: Sensitivity studies of different aerosol indirect effects in mixed-phase clouds, Atmos. Chem. Phys., 9, 8917–8934, https://doi.org/10.5194/acp-9-8917-2009, 2009.
Martin, M., Stirling, C., Humphries, S., and Long, S.: A process-based model to predict the effects of climatic change on leaf isoprene emission rates, Ecol. Model., 131, 161–174, 2000.
Messina, P., Lathière, J., Sindelarova, K., Vuichard, N., Granier, C., Ghattas, J., Cozic, A., and Hauglustaine, D. A.: Global biogenic volatile organic compound emissions in the ORCHIDEE and MEGAN models and sensitivity to key parameters, Atmos. Chem. Phys., 16, 14169–14202, https://doi.org/10.5194/acp-16-14169-2016, 2016.
Millet, D. B., Jacob, D. J., Custer, T. G., de Gouw, J. A., Goldstein, A. H., Karl, T., Singh, H. B., Sive, B. C., Talbot, R. W., Warneke, C., and Williams, J.: New constraints on terrestrial and oceanic sources of atmospheric methanol, Atmos. Chem. Phys., 8, 6887–6905, https://doi.org/10.5194/acp-8-6887-2008, 2008.
Millet, D. B., Guenther, A., Siegel, D. A., Nelson, N. B., Singh, H. B., de Gouw, J. A., Warneke, C., Williams, J., Eerdekens, G., Sinha, V., Karl, T., Flocke, F., Apel, E., Riemer, D. D., Palmer, P. I., and Barkley, M.: Global atmospheric budget of acetaldehyde: 3-D model analysis and constraints from in-situ and satellite observations, Atmos. Chem. Phys., 10, 3405–3425, https://doi.org/10.5194/acp-10-3405-2010, 2010.
Misztal, P. K., Hewitt, C. N., Wildt, J., Blande, J. D., Eller, A. S. D., Fares, S., Gentner, D. R., Gilman, J. B., Graus, M., Greenberg, J., Guenther, A. B., Hansel, A., Harley, P., Huang, M., Jardine, K., Karl, T., Kaser, L., Keutsch, F. N., Kiendler-Scharr, A., Kleist, E., Lerner, B. M., Li, T., Mak, J., Nölscher, A. C., Schnitzhofer, R., Sinha, V., Thornton, B., Warneke, C., Wegener, F., Werner, C., Williams, J., Worton, D., Yassaa, N., and Goldstein, A. H.: Atmospheric benzenoid emissions from plants rival those from fossil fuels, Sci. Rep., 5, 12064, https://doi.org/10.1038/srep12064, 2015.
Müller, J.-F., Stavrakou, T., Wallens, S., De Smedt, I., Van Roozendael, M., Potosnak, M. J., Rinne, J., Munger, B., Goldstein, A., and Guenther, A. B.: Global isoprene emissions estimated using MEGAN, ECMWF analyses and a detailed canopy environment model, Atmos. Chem. Phys., 8, 1329–1341, https://doi.org/10.5194/acp-8-1329-2008, 2008.
Niinemets, U., Tenhunen, J. D., Harley, P. C., and Steinbrecher, R.: A model of isoprene emission based on energetic requirements for isoprene synthesis and leaf photosynthetic properties for Liquidambar and Quercus, Plant Cell Environ., 22, 1319–1335, 1999.
O'Donnell, D., Tsigaridis, K., and Feichter, J.: Estimating the direct and indirect effects of secondary organic aerosols using ECHAM5-HAM, Atmos. Chem. Phys., 11, 8635–8659, https://doi.org/10.5194/acp-11-8635-2011, 2011.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E., Lawrence, P. J., Levis, S., Swenson, S. C., Thornton, P. E., Dai, A., Decker, M., Dickinson, R., Feddema, J., Heald, C. L., Hoffman, F., Lamarque, J.-F., Mahowald, N., Niu, G.-Y., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stöckli, R., Wang, A., Yang, Z.-L., Zeng, X., and Zeng, X.: Technical description of version 4.0 of the Community Land Model (CLM), Tech. Rep. TN-478+STR, NCAR, Boulder, Colorado, USA, 2010.
Pacifico, F., Harrison, S. P., Jones, C., and Sitch, S.: Isoprene emission and climate, Atmos. Environ., 43, 6121–6135, 2009.
Pegoraro, E., Rey, A., Greenberg, J., Harley, P., Grace, J., Malhi, Y., and Guenther, A.: Effect of drought on isoprene emission rates from leaves of Quercus virginiana Mill, Atmos. Environ., 38, 6149–6156, 2004.
Pfister, G. G., Emmons, L. K., Hess, P. G., Lamarque, J.-F., Orlando, J. J., Walters, S., Guenther, A., Palmer, P. I., and Lawrence, P. J.: Contribution of isoprene to chemical budgets: A model tracer study with the NCAR CTM MOZART-4, J. Geophys. Res., 113, D05308, https://doi.org/10.1029/2007JD008948, 2008.
Pierce, T. E. and Waldruff, P. S.: Pc-Beis – a Personal-Computer Version of the Biogenic Emissions Inventory System, J. Air Waste Manage., 41, 937–941, 1991.
Pongratz, J., Reick, C., Raddatz, T., and Claussen, M.: A Global Land Cover Reconstruction AD 800 to 1992 – Technical Description, Tech. Rep. 51, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 2008.
Pongratz, J., Reick, C., Raddatz, T., and Claussen, M.: Effects of anthropogenic land cover change on the carbon cycle of the last millennium, Global Biogeochem. Cycles, 23, GB4001, https://doi.org/10.1029/2009GB003488, 2009.
Pugh, T. A. M., Ashworth, K., Wild, O., and Hewitt, C. N.: Effects of the spatial resolution of climate data on estimates of biogenic isoprene emissions, Atmos. Environ., 70, 1–6, 2013.
Raddatz, T. C., Reick, C., Knorr, W., and Kattge, J.: Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty-first century?, Clim. Dynam., 29, 565–574, 2007.
Ramankutty, N. and Foley, J. A.: Estimating historical changes in global land cover: croplands from 1700 to 1992, Global Biogeochem. Cy., 13, 997–1027, 1999.
Ramankutty, N., Evan, A., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, https://doi.org/10.1029/2007GB002952, 2008.
Reick, C. H., Raddatz, T., Brovkin, V., and Gayler, V.: Representation of natural and anthropogenic land cover change in MPI-ESM, J. Adv. Model. Earth Syst., 5, 459–482, 2013.
Rinne, J.: Interactive comment on "Global biogenic volatile organic compound emissions in the ORCHIDEE and MEGAN models and sensitivity to key parameters" by P. Messina et al., Atmos. Chem. Phys. Discuss., 15, C11977–C11979, 2016.
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., and Tompkins, A.: The atmospheric general circulation model ECHAM5. Part I: Model description, Tech. Rep. 349, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 2003.
Rosenstiel, T. N., Potosnak, M. J., Griffin, K. L., Fall, R., and Monson, R. K.: Increased CO2 uncouples growth from isoprene emission in an agriforest ecosystem, Nature, 421, 256–259, 2003.
Sindelarova, K., Granier, C., Bouarar, I., Guenther, A., Tilmes, S., Stavrakou, T., Müller, J.-F., Kuhn, U., Stefani, P., and Knorr, W.: Global data set of biogenic VOC emissions calculated by the MEGAN model over the last 30 years, Atmos. Chem. Phys., 14, 9317–9341, https://doi.org/10.5194/acp-14-9317-2014, 2014.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185, 2003.
Stavrakou, T., Müller, J.-F., De Smedt, I., Van Roozendael, M., van der Werf, G. R., Giglio, L., and Guenther, A.: Global emissions of non-methane hydrocarbons deduced from SCIAMACHY formaldehyde columns through 2003–2006, Atmos. Chem. Phys., 9, 3663–3679, https://doi.org/10.5194/acp-9-3663-2009, 2009.
Stavrakou, T., Guenther, A., Razavi, A., Clarisse, L., Clerbaux, C., Coheur, P.-F., Hurtmans, D., Karagulian, F., De Mazière, M., Vigouroux, C., Amelynck, C., Schoon, N., Laffineur, Q., Heinesch, B., Aubinet, M., Rinsland, C., and Müller, J.-F.: First space-based derivation of the global atmospheric methanol emission fluxes, Atmos. Chem. Phys., 11, 4873–4898, https://doi.org/10.5194/acp-11-4873-2011, 2011.
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model. Earth Syst., 5, 146–172, 2013.
Stier, P., Feichter, J., Kinne, S., Kloster, S., Vignati, E., Wilson, J., Ganzeveld, L., Tegen, I., Werner, M., Balkanski, Y., Schulz, M., Boucher, O., Minikin, A., and Petzold, A.: The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 5, 1125–1156, https://doi.org/10.5194/acp-5-1125-2005, 2005.
Tao, Z. and Jain, A. K.: Modeling of global biogenic emissions for key indirect greenhouse gases and their response to atmospheric CO2 increases and changes in land cover and climate, J. Geophys. Res., 110, D21309, https://doi.org/10.1029/2005JD005874, 2005.
Taraborrelli, D., Lawrence, M., Crowley, J., Dillon, T., Gromov, S., Gross, C., Vereecken, L., and Lelieveld, J.: Hydroxyl radical buffered by isoprene oxidation over tropical forests, Nat. Geosci., 5, 190–193, 2012.
Thomson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty, B., Wise, M. A., Clarke, L. E., and Edmonds, J. A.: RCP4.5: A pathway for stabilization of radiative forcing by 2100, Climatic Change, 109, 77–94, 2011.
Tilmes, S., Lamarque, J.-F., Emmons, L. K., Kinnison, D. E., Ma, P.-L., Liu, X., Ghan, S., Bardeen, C., Arnold, S., Deeter, M., Vitt, F., Ryerson, T., Elkins, J. W., Moore, F., Spackman, J. R., and Val Martin, M.: Description and evaluation of tropospheric chemistry and aerosols in the Community Earth System Model (CESM1.2), Geosci. Model Dev., 8, 1395–1426, https://doi.org/10.5194/gmd-8-1395-2015, 2015.
van Donkelaar, A., Martin, R. V., Park, R. J., Heald, C. L., Fu, T.-M., Liao, H., and Guenther, A.: Model evidence for a significant source of secondary organic aerosol from isoprene, Atmos. Environ., 41, 1267–1274, 2007.
Velikova, V., Tsonev, T., Pinelli, P., Alessio, G. A., and Loreto, F.: Localized ozone fumigation system for studying ozone effects on photosynthesis, respiration, electron transport rate and isoprene emission in field-grown Mediterranean oak species, Tree Physiol., 25, 1523–1532, 2005.
Wu, C., Pullinen, I., Andres, S., Carriero, G., Fares, S., Goldbach, H., Hacker, L., Kasal, T., Kiendler-Scharr, A., Kleist, E., Paoletti, E., Wahner, A., Wildt, J., and Mentel, Th. F.: Impacts of soil moisture on de novo monoterpene emissions from European beech, Holm oak, Scots pine, and Norway spruce, Biogeosciences, 12, 177–191, https://doi.org/10.5194/bg-12-177-2015, 2015.
Zhang, K., O'Donnell, D., Kazil, J., Stier, P., Kinne, S., Lohmann, U., Ferrachat, S., Croft, B., Quaas, J., Wan, H., Rast, S., and Feichter, J.: The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations, Atmos. Chem. Phys., 12, 8911–8949, https://doi.org/10.5194/acp-12-8911-2012, 2012.
Zhang, K., Wan, H., Liu, X., Ghan, S. J., Kooperman, G. J., Ma, P.-L., Rasch, P. J., Neubauer, D., and Lohmann, U.: Technical Note: On the use of nudging for aerosol–climate model intercomparison studies, Atmos. Chem. Phys., 14, 8631–8645, https://doi.org/10.5194/acp-14-8631-2014, 2014.
Short summary
This paper describes the basic results of the biogenic emission scheme, based on MEGAN, integrated into the ECHAM6-HAMMOZ chemistry climate model. Sensitivity to vegetation and climate-dependent parameters is also analysed. This version of the model is now suitable for many tropospheric investigations concerning the impact of biogenic volatile organic compound emissions on the ozone budget, secondary aerosol formation, and atmospheric chemistry.
This paper describes the basic results of the biogenic emission scheme, based on MEGAN,...
