Articles | Volume 6, issue 3
Geosci. Model Dev., 6, 783–790, 2013
https://doi.org/10.5194/gmd-6-783-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 6, 783–790, 2013
https://doi.org/10.5194/gmd-6-783-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper 07 Jun 2013
Development and technical paper | 07 Jun 2013
On the parallelization of atmospheric inversions of CO2 surface fluxes within a variational framework
F. Chevallier
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Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Anna Agustí-Panareda, Michail Diamantakis, Sébastien Massart, Frédéric Chevallier, Joaquín Muñoz-Sabater, Jérôme Barré, Roger Curcoll, Richard Engelen, Bavo Langerock, Rachel M. Law, Zoë Loh, Josep Anton Morguí, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Coleen Roehl, Alex T. Vermeulen, Thorsten Warneke, and Debra Wunch
Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, https://doi.org/10.5194/acp-19-7347-2019, 2019
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Felix R. Vogel, Matthias Frey, Johannes Staufer, Frank Hase, Grégoire Broquet, Irène Xueref-Remy, Frédéric Chevallier, Philippe Ciais, Mahesh Kumar Sha, Pascale Chelin, Pascal Jeseck, Christof Janssen, Yao Té, Jochen Groß, Thomas Blumenstock, Qiansi Tu, and Johannes Orphal
Atmos. Chem. Phys., 19, 3271–3285, https://doi.org/10.5194/acp-19-3271-2019, https://doi.org/10.5194/acp-19-3271-2019, 2019
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Providing timely information on greenhouse gas emissions to stakeholders at sub-national scale is an emerging challenge and understanding urban CO2 levels is one key aspect. This study uses atmospheric observations of total column CO2 and compares them to numerical simulations to investigate CO2 levels in the Paris metropolitan area due to natural fluxes and anthropogenic emissions. Our measurements reveal the influence of locally added CO2, which our model is also able to predict.
Benjamin Gaubert, Britton B. Stephens, Sourish Basu, Frédéric Chevallier, Feng Deng, Eric A. Kort, Prabir K. Patra, Wouter Peters, Christian Rödenbeck, Tazu Saeki, David Schimel, Ingrid Van der Laan-Luijkx, Steven Wofsy, and Yi Yin
Biogeosciences, 16, 117–134, https://doi.org/10.5194/bg-16-117-2019, https://doi.org/10.5194/bg-16-117-2019, 2019
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We have compared global carbon budgets calculated from numerical inverse models and CO2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO2 from aircraft measurements. We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.
Christopher W. O'Dell, Annmarie Eldering, Paul O. Wennberg, David Crisp, Michael R. Gunson, Brendan Fisher, Christian Frankenberg, Matthäus Kiel, Hannakaisa Lindqvist, Lukas Mandrake, Aronne Merrelli, Vijay Natraj, Robert R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Drouin, Fabiano Oyafuso, Albert Chang, James McDuffie, Michael Smyth, David F. Baker, Sourish Basu, Frédéric Chevallier, Sean M. R. Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, Coleen M. Roehl, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Osamu Uchino, and Voltaire A. Velazco
Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, https://doi.org/10.5194/amt-11-6539-2018, 2018
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Marine Remaud, Frédéric Chevallier, Anne Cozic, Xin Lin, and Philippe Bousquet
Geosci. Model Dev., 11, 4489–4513, https://doi.org/10.5194/gmd-11-4489-2018, https://doi.org/10.5194/gmd-11-4489-2018, 2018
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We compare several versions of a global atmospheric transport model for the simulation of CO2. The representation of subgrid-scale processes modulates the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere. It has the largest impact over Brazil. Refining the horizontal resolution improves the simulation near emission hotspots or along the coastlines. The sensitivities to the land surface model and to the increase in vertical resolution are marginal.
Maarten Krol, Marco de Bruine, Lars Killaars, Huug Ouwersloot, Andrea Pozzer, Yi Yin, Frederic Chevallier, Philippe Bousquet, Prabir Patra, Dmitry Belikov, Shamil Maksyutov, Sandip Dhomse, Wuhu Feng, and Martyn P. Chipperfield
Geosci. Model Dev., 11, 3109–3130, https://doi.org/10.5194/gmd-11-3109-2018, https://doi.org/10.5194/gmd-11-3109-2018, 2018
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The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced. Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis.
Sourish Basu, David F. Baker, Frédéric Chevallier, Prabir K. Patra, Junjie Liu, and John B. Miller
Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, https://doi.org/10.5194/acp-18-7189-2018, 2018
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CO2 measurements from the global surface network and CO2 estimates from satellites such as the Orbiting Carbon Observatory 2 (OCO-2) are currently used to quantify the surface sources and sinks of CO2, using what we know about atmospheric transport of gases. In this work, we quantify the uncertainties in those surface source/sink estimates that stem from errors in our atmospheric transport models, using an observing system simulation experiment (OSSE).
Yilong Wang, Grégoire Broquet, Philippe Ciais, Frédéric Chevallier, Felix Vogel, Lin Wu, Yi Yin, Rong Wang, and Shu Tao
Atmos. Chem. Phys., 18, 4229–4250, https://doi.org/10.5194/acp-18-4229-2018, https://doi.org/10.5194/acp-18-4229-2018, 2018
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This paper assesses the potential of atmospheric 14CO2 observations and a global inversion system to solve for fossil fuel CO2 (FFCO2) emissions in Europe. The estimate of monthly emission budgets is largely improved in high emitting regions. The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO2 emissions.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
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The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Irène Xueref-Remy, Elsa Dieudonné, Cyrille Vuillemin, Morgan Lopez, Christine Lac, Martina Schmidt, Marc Delmotte, Frédéric Chevallier, François Ravetta, Olivier Perrussel, Philippe Ciais, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, T. Gerard Spain, and Christophe Ampe
Atmos. Chem. Phys., 18, 3335–3362, https://doi.org/10.5194/acp-18-3335-2018, https://doi.org/10.5194/acp-18-3335-2018, 2018
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Urbanized and industrialized areas are the largest source of fossil CO2. This work analyses the atmospheric CO2 variability observed from the first in situ network deployed in the Paris megacity area. Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO2 records.
Grégoire Broquet, François-Marie Bréon, Emmanuel Renault, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Frédéric Chevallier, Lin Wu, and Philippe Ciais
Atmos. Meas. Tech., 11, 681–708, https://doi.org/10.5194/amt-11-681-2018, https://doi.org/10.5194/amt-11-681-2018, 2018
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This study assesses the potential of space-borne imagery of CO2 atmospheric concentrations for monitoring the emissions from the Paris area. Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO2 emissions for urban areas with CO2 observations from satellites, and calls for more technological innovations in the remote sensing of CO2 and in the models that exploit it.
Chao Yue, Philippe Ciais, Ana Bastos, Frederic Chevallier, Yi Yin, Christian Rödenbeck, and Taejin Park
Atmos. Chem. Phys., 17, 13903–13919, https://doi.org/10.5194/acp-17-13903-2017, https://doi.org/10.5194/acp-17-13903-2017, 2017
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The year 2015 appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since 2000 according to satellite observation, but the atmospheric CO2 growth rate is also the highest since 1959. We found that this is due to a only moderate land carbon sink, because high growing-season sink in northern lands has been partly offset by autumn and winter release and the late-year El Niño has led to an abrupt transition to land source in the tropics.
Anna M. Michalak, Nina A. Randazzo, and Frédéric Chevallier
Atmos. Chem. Phys., 17, 7405–7421, https://doi.org/10.5194/acp-17-7405-2017, https://doi.org/10.5194/acp-17-7405-2017, 2017
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The use of inverse modeling for quantifying emissions of greenhouse gases is increasing. Estimates are very difficult to evaluate objectively, however, due to limited atmospheric observations and the lack of direct emissions measurements at compatible scales. Diagnostic tools have been proposed to partially circumvent these limitations. This paper presents the first systematic review of the scope and applicability of these tools for atmospheric inversions of long-lived greenhouse gases.
Jerónimo Escribano, Olivier Boucher, Frédéric Chevallier, and Nicolás Huneeus
Atmos. Chem. Phys., 17, 7111–7126, https://doi.org/10.5194/acp-17-7111-2017, https://doi.org/10.5194/acp-17-7111-2017, 2017
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Top-down estimates of mineral dust flux usually rely on a single observational dataset whose observational errors propagate onto the emission estimates. Aerosol optical depth from five satellites are assimilated one by one into a source inversion system over northern Africa. We find a relatively large dispersion in flux estimates among the five experiments, which can likely be attributed to differences in the assimilated observational datasets and their associated error statistics.
Yi Yin, Frederic Chevallier, Philippe Ciais, Gregoire Broquet, Anne Cozic, Sophie Szopa, and Yilong Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-166, https://doi.org/10.5194/acp-2017-166, 2017
Revised manuscript not accepted
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CO inverse modelling studies have so far reported significant discrepancies between model concentrations optimised with the Measurement of Pollution in the Troposphere (MOPITT) satellite retrievals and surface in-situ measurements. Here, we assess how well a global CTM fits a large variety of independent CO observations before and after assimilating MOPITTv6 retrievals to optimise CO sources/sink and discuss potential sources of errors and their implications for global CO modelling studies.
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
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The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Lamia Ammoura, Irène Xueref-Remy, Felix Vogel, Valérie Gros, Alexia Baudic, Bernard Bonsang, Marc Delmotte, Yao Té, and Frédéric Chevallier
Atmos. Chem. Phys., 16, 15653–15664, https://doi.org/10.5194/acp-16-15653-2016, https://doi.org/10.5194/acp-16-15653-2016, 2016
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We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed. We apply it to estimate monthly ratios between CO2, CO and some VOCs from atmospheric measurement datasets acquired in the centre of Paris between 2010 and 2014. We find that this approach is little sensitive to the regional background level definition. With this new method, we may reveal spatial and seasonal variability in the ratios in Paris.
Johannes Staufer, Grégoire Broquet, François-Marie Bréon, Vincent Puygrenier, Frédéric Chevallier, Irène Xueref-Rémy, Elsa Dieudonné, Morgan Lopez, Martina Schmidt, Michel Ramonet, Olivier Perrussel, Christine Lac, Lin Wu, and Philippe Ciais
Atmos. Chem. Phys., 16, 14703–14726, https://doi.org/10.5194/acp-16-14703-2016, https://doi.org/10.5194/acp-16-14703-2016, 2016
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Natasha MacBean, Philippe Peylin, Frédéric Chevallier, Marko Scholze, and Gregor Schürmann
Geosci. Model Dev., 9, 3569–3588, https://doi.org/10.5194/gmd-9-3569-2016, https://doi.org/10.5194/gmd-9-3569-2016, 2016
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Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model. Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context. This paper demonstrates and discusses the issues involved using toy models and examples from existing literature.
Philippe Peylin, Cédric Bacour, Natasha MacBean, Sébastien Leonard, Peter Rayner, Sylvain Kuppel, Ernest Koffi, Abdou Kane, Fabienne Maignan, Frédéric Chevallier, Philippe Ciais, and Pascal Prunet
Geosci. Model Dev., 9, 3321–3346, https://doi.org/10.5194/gmd-9-3321-2016, https://doi.org/10.5194/gmd-9-3321-2016, 2016
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The study describes a carbon cycle data assimilation system that uses satellite observations of vegetation activity, net ecosystem exchange of carbon and water at many sites and atmospheric CO2 concentrations, in order to optimize the parameters of the ORCHIDEE land surface model. The optimized model is able to fit all three data streams leading to a land carbon uptake similar to independent estimates, which opens new perspectives for better prediction of the land carbon balance.
Anna Agustí-Panareda, Sébastien Massart, Frédéric Chevallier, Gianpaolo Balsamo, Souhail Boussetta, Emanuel Dutra, and Anton Beljaars
Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016, https://doi.org/10.5194/acp-16-10399-2016, 2016
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This paper presents a method to adjust the sinks and sources of CO2 associated with land ecosystems within a global atmospheric CO2 forecasting system in order to reduce the errors in the forecast. This is done by combining information on (1) retrospective fluxes estimated by a global flux inversion system, (2) land-use information, and (3) simulated fluxes from the model. Because the method is simple and flexible, it can easily run in real time as part of a forecasting system.
Cindy Cressot, Isabelle Pison, Peter J. Rayner, Philippe Bousquet, Audrey Fortems-Cheiney, and Frédéric Chevallier
Atmos. Chem. Phys., 16, 9089–9108, https://doi.org/10.5194/acp-16-9089-2016, https://doi.org/10.5194/acp-16-9089-2016, 2016
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Several hypothesis have been made to attribute current trends in atmospheric methane to particular regions. In this context, this work aims at evaluating how well anomalies in methane emissions can be detected at the regional scale with currently available observing systems: two space-borne instruments and a surface network. Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment.
Peter Rayner, Anna M. Michalak, and Frédéric Chevallier
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-148, https://doi.org/10.5194/gmd-2016-148, 2016
Revised manuscript not accepted
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Numerical models are among our most important tools for understanding and prediction. Models include quantities or equations that we cannot verify directly. We learn about these unknowns by comparing model output with observations and using some algorithm to improve the inputs. We show here that the many methods for doing this are special cases of underlying statistics. This provides a unified way of comparing and contrasting such methods.
Christian Frankenberg, Susan S. Kulawik, Steven C. Wofsy, Frédéric Chevallier, Bruce Daube, Eric A. Kort, Christopher O'Dell, Edward T. Olsen, and Gregory Osterman
Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, https://doi.org/10.5194/acp-16-7867-2016, 2016
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We use observations from the HIAPER Pole-to-Pole Observations (HIPPO) flights from January 2009 through September 2011 to validate CO2 measurements from satellites (GOSAT, TES, AIRS) and atmospheric inversion models (CarbonTracker CT2013B, MACC v13r1).
Lin Wu, Grégoire Broquet, Philippe Ciais, Valentin Bellassen, Felix Vogel, Frédéric Chevallier, Irène Xueref-Remy, and Yilong Wang
Atmos. Chem. Phys., 16, 7743–7771, https://doi.org/10.5194/acp-16-7743-2016, https://doi.org/10.5194/acp-16-7743-2016, 2016
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This paper advances atmospheric inversion of city CO2 emissions as follows: (1) illustrate how inversion methodology can be tailored to deal with very large urban networks of sensors measuring CO2 concentrations; (2) demonstrate that atmospheric inversion could be a relevant tool of Monitoring, Reporting and Verification (MRV) of city CO2 emissions; (3) clarify the theoretical potential of inversion for reducing uncertainties in the estimates of citywide total and sectoral CO2 emissions.
Alex Boon, Grégoire Broquet, Deborah J. Clifford, Frédéric Chevallier, David M. Butterfield, Isabelle Pison, Michel Ramonet, Jean-Daniel Paris, and Philippe Ciais
Atmos. Chem. Phys., 16, 6735–6756, https://doi.org/10.5194/acp-16-6735-2016, https://doi.org/10.5194/acp-16-6735-2016, 2016
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We measured carbon dioxide and methane concentrations at four near-ground sites located in London, 2012. We investigated the potential for using these measurements, alongside numerical modelling, to help us to understand urban greenhouse gas emissions. Low-level sites were highly sensitive to local emissions, which questions our ability to use measurements from near-ground sites in cities in some modelling applications. A gradient approach was found to be beneficial to reduce model–data errors.
Sudhanshu Pandey, Sander Houweling, Maarten Krol, Ilse Aben, Frédéric Chevallier, Edward J. Dlugokencky, Luciana V. Gatti, Emanuel Gloor, John B. Miller, Rob Detmers, Toshinobu Machida, and Thomas Röckmann
Atmos. Chem. Phys., 16, 5043–5062, https://doi.org/10.5194/acp-16-5043-2016, https://doi.org/10.5194/acp-16-5043-2016, 2016
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This study investigates the constraint provided by measurements of Xratio (XCH4/XCO2) from space on surface fluxes of CH4 and CO2. We apply the ratio inversion method described in Pandey et al. (2015) to Xratio retrievals from the GOSAT with the TM5-4DVAR inverse modeling system, to constrain the surface fluxes of CH4 and CO2 for 2009 and 2010. The results are compared to proxy CH4 inversions using model-derived-XCO2 mixing ratios from CarbonTracker and MACC.
Antoine Berchet, Philippe Bousquet, Isabelle Pison, Robin Locatelli, Frédéric Chevallier, Jean-Daniel Paris, Ed J. Dlugokencky, Tuomas Laurila, Juha Hatakka, Yrjo Viisanen, Doug E. J. Worthy, Euan Nisbet, Rebecca Fisher, James France, David Lowry, Viktor Ivakhov, and Ove Hermansen
Atmos. Chem. Phys., 16, 4147–4157, https://doi.org/10.5194/acp-16-4147-2016, https://doi.org/10.5194/acp-16-4147-2016, 2016
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We propose insights based on atmospheric observations around the Arctic circle to evaluate estimates of methane emissions to the atmosphere from the East Siberian Arctic Shelf. Based on a comprehensive statistical analysis of the observations and of high-resolution transport simulations, annual methane emissions from ESAS are estimated to range from 0.0 to 4.5 TgCH4 yr−1, with a maximum in summer and very low emissions in winter.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
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To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
Sébastien Massart, Anna Agustí-Panareda, Jens Heymann, Michael Buchwitz, Frédéric Chevallier, Maximilian Reuter, Michael Hilker, John P. Burrows, Nicholas M. Deutscher, Dietrich G. Feist, Frank Hase, Ralf Sussmann, Filip Desmet, Manvendra K. Dubey, David W. T. Griffith, Rigel Kivi, Christof Petri, Matthias Schneider, and Voltaire A. Velazco
Atmos. Chem. Phys., 16, 1653–1671, https://doi.org/10.5194/acp-16-1653-2016, https://doi.org/10.5194/acp-16-1653-2016, 2016
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This study presents the European Centre for Medium-Range Weather Forecasts (ECMWF) monitoring of atmospheric CO2 using measurements from the Greenhouse gases Observing Satellite (GOSAT). We show that the modelled CO2 has a better precision than standard CO2 satellite products compared to ground-based measurements. We also present the CO2 forecast based on our best knowledge of the atmospheric CO2 distribution. We show that it has skill to forecast the largest scale CO2 patterns up to day 5.
Y. Yin, F. Chevallier, P. Ciais, G. Broquet, A. Fortems-Cheiney, I. Pison, and M. Saunois
Atmos. Chem. Phys., 15, 13433–13451, https://doi.org/10.5194/acp-15-13433-2015, https://doi.org/10.5194/acp-15-13433-2015, 2015
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We studied the global CO concentration decline over the recent decade with a sophisticated atmospheric inversion system assimilating MOPITT CO retrievals, surface methane and surface methyl chloroform in situ measurements. The inversion interprets the CO concentration decline as a 23% decrease in the CO emissions from 2002 to 2011, twice the negative trend estimated by emission inventories. In contrast to bottom-up inventories, we find negative trends over China and South-east Asia.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
H. Lindqvist, C. W. O'Dell, S. Basu, H. Boesch, F. Chevallier, N. Deutscher, L. Feng, B. Fisher, F. Hase, M. Inoue, R. Kivi, I. Morino, P. I. Palmer, R. Parker, M. Schneider, R. Sussmann, and Y. Yoshida
Atmos. Chem. Phys., 15, 13023–13040, https://doi.org/10.5194/acp-15-13023-2015, https://doi.org/10.5194/acp-15-13023-2015, 2015
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Atmospheric carbon dioxide concentration varies seasonally mainly due to plant photosynthesis in the Northern Hemisphere. We found that the satellite GOSAT can capture this variability from space to within 1ppm. We also found that models can differ by more than 1ppm. This implies that the satellite measurements could be useful in evaluating models and their prior estimates of carbon dioxide sources and sinks.
N. Kadygrov, G. Broquet, F. Chevallier, L. Rivier, C. Gerbig, and P. Ciais
Atmos. Chem. Phys., 15, 12765–12787, https://doi.org/10.5194/acp-15-12765-2015, https://doi.org/10.5194/acp-15-12765-2015, 2015
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We study the potential of the European Integrated Carbon Observing System (ICOS) atmospheric network for estimating European CO2 ecosystem fluxes. Regional atmospheric inversions with synthetic data are used to derive it in terms of statistical uncertainty. This potential is high in western Europe and future extensions of the network will increase it in eastern Europe. Future improvements of the models underlying the inversion should also significantly decrease uncertainties at high resolution.
R. J. Parker, H. Boesch, K. Byckling, A. J. Webb, P. I. Palmer, L. Feng, P. Bergamaschi, F. Chevallier, J. Notholt, N. Deutscher, T. Warneke, F. Hase, R. Sussmann, S. Kawakami, R. Kivi, D. W. T. Griffith, and V. Velazco
Atmos. Meas. Tech., 8, 4785–4801, https://doi.org/10.5194/amt-8-4785-2015, https://doi.org/10.5194/amt-8-4785-2015, 2015
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Atmospheric CH4 is an important greenhouse gas. Long-term global observations are necessary to understand its behaviour, with satellite observations playing a key role. The "proxy" retrieval method is one of the most successful but relies on the contribution from atmospheric CO2 models. This work assesses the significance of the uncertainty from the model CO2 within the retrieval and determines that despite this uncertainty the data are still valuable for determining sources and sinks of CH4.
F. Chevallier
Atmos. Chem. Phys., 15, 11133–11145, https://doi.org/10.5194/acp-15-11133-2015, https://doi.org/10.5194/acp-15-11133-2015, 2015
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We demonstrate that the current two-step approach to infer the CO2 surface fluxes from satellite measured radiances, with CO2 retrievals as an intermediate product, is not optimal. This suboptimality corrupts the 4D information flow from the radiance measurements to the surface flux estimates. It is amplified by current retrieval strategies where prior errors are much larger than the performance of prior CO2 simulations used in atmospheric inversions.
A. Berchet, I. Pison, F. Chevallier, J.-D. Paris, P. Bousquet, J.-L. Bonne, M. Y. Arshinov, B. D. Belan, C. Cressot, D. K. Davydov, E. J. Dlugokencky, A. V. Fofonov, A. Galanin, J. Lavrič, T. Machida, R. Parker, M. Sasakawa, R. Spahni, B. D. Stocker, and J. Winderlich
Biogeosciences, 12, 5393–5414, https://doi.org/10.5194/bg-12-5393-2015, https://doi.org/10.5194/bg-12-5393-2015, 2015
R. Locatelli, P. Bousquet, M. Saunois, F. Chevallier, and C. Cressot
Atmos. Chem. Phys., 15, 9765–9780, https://doi.org/10.5194/acp-15-9765-2015, https://doi.org/10.5194/acp-15-9765-2015, 2015
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
F. M. Bréon, G. Broquet, V. Puygrenier, F. Chevallier, I. Xueref-Remy, M. Ramonet, E. Dieudonné, M. Lopez, M. Schmidt, O. Perrussel, and P. Ciais
Atmos. Chem. Phys., 15, 1707–1724, https://doi.org/10.5194/acp-15-1707-2015, https://doi.org/10.5194/acp-15-1707-2015, 2015
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
L. Ammoura, I. Xueref-Remy, V. Gros, A. Baudic, B. Bonsang, J.-E. Petit, O. Perrussel, N. Bonnaire, J. Sciare, and F. Chevallier
Atmos. Chem. Phys., 14, 12871–12882, https://doi.org/10.5194/acp-14-12871-2014, https://doi.org/10.5194/acp-14-12871-2014, 2014
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We present the first study of CO2, VOCs and NOx measured all together in a road tunnel around the Paris megacity with the aim to quantify the ratios of these species co-emitted within traffic emissions. It allows us to independently assess some of the ratios provided in the latest Paris emission inventory. It also reveals a large variability of the ratios to CO2, implying that traffic does not have a unique imprint in the urban plume, but rather leaves various signatures.
A. Agustí-Panareda, S. Massart, F. Chevallier, S. Boussetta, G. Balsamo, A. Beljaars, P. Ciais, N. M. Deutscher, R. Engelen, L. Jones, R. Kivi, J.-D. Paris, V.-H. Peuch, V. Sherlock, A. T. Vermeulen, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, https://doi.org/10.5194/acp-14-11959-2014, 2014
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This paper presents a new operational CO2 forecast product as part of the Copernicus Atmospheric Services suite of atmospheric composition products, using the state-of-the-art numerical weather prediction model from the European Centre of Medium-Range Weather Forecasts.
The evaluation with independent observations shows that the forecast has skill in predicting the synoptic variability of CO2. The online simulation of CO2 fluxes from vegetation contributes to this skill.
S. Kuppel, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti
Geosci. Model Dev., 7, 2581–2597, https://doi.org/10.5194/gmd-7-2581-2014, https://doi.org/10.5194/gmd-7-2581-2014, 2014
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A consistent calibration of an advanced land surface model was performed by grouping in situ information on land-atmosphere exchanges of carbon and water using broad ecosystem and climate classes. Signatures of improved carbon cycle simulations were found across spatial and temporal scales, along with insights into current model limitations. These results hold promising perspectives within the ongoing efforts towards building robust model-data fusion frameworks for earth system models.
C. Wilson, M. P. Chipperfield, M. Gloor, and F. Chevallier
Geosci. Model Dev., 7, 2485–2500, https://doi.org/10.5194/gmd-7-2485-2014, https://doi.org/10.5194/gmd-7-2485-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
S. Massart, A. Agusti-Panareda, I. Aben, A. Butz, F. Chevallier, C. Crevoisier, R. Engelen, C. Frankenberg, and O. Hasekamp
Atmos. Chem. Phys., 14, 6139–6158, https://doi.org/10.5194/acp-14-6139-2014, https://doi.org/10.5194/acp-14-6139-2014, 2014
R. L. Thompson, K. Ishijima, E. Saikawa, M. Corazza, U. Karstens, P. K. Patra, P. Bergamaschi, F. Chevallier, E. Dlugokencky, R. G. Prinn, R. F. Weiss, S. O'Doherty, P. J. Fraser, L. P. Steele, P. B. Krummel, A. Vermeulen, Y. Tohjima, A. Jordan, L. Haszpra, M. Steinbacher, S. Van der Laan, T. Aalto, F. Meinhardt, M. E. Popa, J. Moncrieff, and P. Bousquet
Atmos. Chem. Phys., 14, 6177–6194, https://doi.org/10.5194/acp-14-6177-2014, https://doi.org/10.5194/acp-14-6177-2014, 2014
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
R. L. Thompson, F. Chevallier, A. M. Crotwell, G. Dutton, R. L. Langenfelds, R. G. Prinn, R. F. Weiss, Y. Tohjima, T. Nakazawa, P. B. Krummel, L. P. Steele, P. Fraser, S. O'Doherty, K. Ishijima, and S. Aoki
Atmos. Chem. Phys., 14, 1801–1817, https://doi.org/10.5194/acp-14-1801-2014, https://doi.org/10.5194/acp-14-1801-2014, 2014
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
C. Cressot, F. Chevallier, P. Bousquet, C. Crevoisier, E. J. Dlugokencky, A. Fortems-Cheiney, C. Frankenberg, R. Parker, I. Pison, R. A. Scheepmaker, S. A. Montzka, P. B. Krummel, L. P. Steele, and R. L. Langenfelds
Atmos. Chem. Phys., 14, 577–592, https://doi.org/10.5194/acp-14-577-2014, https://doi.org/10.5194/acp-14-577-2014, 2014
P. Peylin, R. M. Law, K. R. Gurney, F. Chevallier, A. R. Jacobson, T. Maki, Y. Niwa, P. K. Patra, W. Peters, P. J. Rayner, C. Rödenbeck, I. T. van der Laan-Luijkx, and X. Zhang
Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, https://doi.org/10.5194/bg-10-6699-2013, 2013
R. Locatelli, P. Bousquet, F. Chevallier, A. Fortems-Cheney, S. Szopa, M. Saunois, A. Agusti-Panareda, D. Bergmann, H. Bian, P. Cameron-Smith, M. P. Chipperfield, E. Gloor, S. Houweling, S. R. Kawa, M. Krol, P. K. Patra, R. G. Prinn, M. Rigby, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 9917–9937, https://doi.org/10.5194/acp-13-9917-2013, https://doi.org/10.5194/acp-13-9917-2013, 2013
G. Broquet, F. Chevallier, F.-M. Bréon, N. Kadygrov, M. Alemanno, F. Apadula, S. Hammer, L. Haszpra, F. Meinhardt, J. A. Morguí, J. Necki, S. Piacentino, M. Ramonet, M. Schmidt, R. L. Thompson, A. T. Vermeulen, C. Yver, and P. Ciais
Atmos. Chem. Phys., 13, 9039–9056, https://doi.org/10.5194/acp-13-9039-2013, https://doi.org/10.5194/acp-13-9039-2013, 2013
A. Berchet, I. Pison, F. Chevallier, P. Bousquet, S. Conil, M. Geever, T. Laurila, J. Lavrič, M. Lopez, J. Moncrieff, J. Necki, M. Ramonet, M. Schmidt, M. Steinbacher, and J. Tarniewicz
Atmos. Chem. Phys., 13, 7115–7132, https://doi.org/10.5194/acp-13-7115-2013, https://doi.org/10.5194/acp-13-7115-2013, 2013
N. Huneeus, O. Boucher, and F. Chevallier
Atmos. Chem. Phys., 13, 6555–6573, https://doi.org/10.5194/acp-13-6555-2013, https://doi.org/10.5194/acp-13-6555-2013, 2013
U. Schuster, G. A. McKinley, N. Bates, F. Chevallier, S. C. Doney, A. R. Fay, M. González-Dávila, N. Gruber, S. Jones, J. Krijnen, P. Landschützer, N. Lefèvre, M. Manizza, J. Mathis, N. Metzl, A. Olsen, A. F. Rios, C. Rödenbeck, J. M. Santana-Casiano, T. Takahashi, R. Wanninkhof, and A. J. Watson
Biogeosciences, 10, 607–627, https://doi.org/10.5194/bg-10-607-2013, https://doi.org/10.5194/bg-10-607-2013, 2013
Marine Remaud, Frédéric Chevallier, Fabienne Maignan, Sauveur Belviso, Antoine Berchet, Alexandra Parouffe, Camille Abadie, Cédric Bacour, Sinikka Lennartz, and Philippe Peylin
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-326, https://doi.org/10.5194/acp-2021-326, 2021
Preprint under review for ACP
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Carbonyl Sulphide (COS) has been recognized as a promising indicator of the plant gross primary production (GPP). Here, we assimilate both COS and CO2 measurements into an atmospheric transport model to obtain information on GPP, plant respiration and COS budget. A possible scenario for the period 2008-2019 leads to a global COS biospheric sink of 800 GgS.yr−1 and higher oceanic emissions between 400 and 600 GgS.yr−1.
Diego Santaren, Grégoire Broquet, François-Marie Bréon, Frédéric Chevallier, Denis Siméoni, Bo Zheng, and Philippe Ciais
Atmos. Meas. Tech., 14, 403–433, https://doi.org/10.5194/amt-14-403-2021, https://doi.org/10.5194/amt-14-403-2021, 2021
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Atmospheric transport inversions with synthetic data are used to assess the potential of new satellite observations of atmospheric CO2 to monitor anthropogenic emissions from regions, cities and large industrial plants. The analysis, applied to a large ensemble of sources in western Europe, shows a strong dependence of the results on different characteristics of the spaceborne instrument, on the source emission budgets and spreads, and on the wind conditions.
Leslie David, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 14, 117–132, https://doi.org/10.5194/amt-14-117-2021, https://doi.org/10.5194/amt-14-117-2021, 2021
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This paper shows that a neural network (NN) approach can be used to process spaceborne observations from the OCO-2 satellite and retrieve both surface pressure and atmospheric CO2 content. The accuracy evaluation indicates that the retrievals have an accuracy that is at least as good as those of the operational approach, which relies on complex algorithms and is computer intensive. The NN approach is therefore a promising alternative for the processing of CO2-monitoring missions.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-407, https://doi.org/10.5194/gmd-2020-407, 2020
Preprint under review for GMD
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We present here a Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Robert J. Parker, Alex Webb, Hartmut Boesch, Peter Somkuti, Rocio Barrio Guillo, Antonio Di Noia, Nikoleta Kalaitzi, Jasdeep S. Anand, Peter Bergamaschi, Frederic Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Coleen Roehl, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch
Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, https://doi.org/10.5194/essd-12-3383-2020, 2020
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This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset. We detail the processing, validation and evaluation involved in producing these data and highlight its many applications. With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Pep Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, A. M. Roxanna Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoli Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-259, https://doi.org/10.5194/gmd-2020-259, 2020
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The phase-2 of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4 and N2O emissions and sinks for ten regions of the globe. In this manuscript, we provide definitions, review different methods and make recommendations to the RECCAP community for estimating different components of the total land-atmosphere carbon exchange for each region in a consistent and complete approach.
Bo Zheng, Frédéric Chevallier, Philippe Ciais, Grégoire Broquet, Yilong Wang, Jinghui Lian, and Yuanhong Zhao
Atmos. Chem. Phys., 20, 8501–8510, https://doi.org/10.5194/acp-20-8501-2020, https://doi.org/10.5194/acp-20-8501-2020, 2020
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The Paris Climate Agreement requires all parties to report CO2 emissions regularly. Given the self-reporting nature of this system, it is critical to evaluate the emission reports with independent observation systems. Here we present the direct observations of city CO2 plumes from space and the quantification of CO2 emissions from these observations over the largest emitter country China. The emissions from 46 hot-spot regions representing 13 % of China's total emissions can be well constrained.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert Parker, Daniel Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-649, https://doi.org/10.5194/acp-2020-649, 2020
Revised manuscript accepted for ACP
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The growth of methane, the second most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in the atmosphere in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year over 2010–2017, with leading contributions from the tropics and East Asia.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Frédéric Chevallier, Marine Remaud, Christopher W. O'Dell, David Baker, Philippe Peylin, and Anne Cozic
Atmos. Chem. Phys., 19, 14233–14251, https://doi.org/10.5194/acp-19-14233-2019, https://doi.org/10.5194/acp-19-14233-2019, 2019
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We present a way to rate the CO2 flux estimates made from inversion of a global atmospheric transport model. Our approach relies on accurate aircraft measurements in the free troposphere. It shows that some satellite soundings can now provide inversion results that are, despite their uncertainty, comparable in credibility to traditional inversions using the accurate but sparse surface network and that these inversions are, therefore, complementary for studies of the global carbon budget.
Peter J. Rayner, Anna M. Michalak, and Frédéric Chevallier
Atmos. Chem. Phys., 19, 13911–13932, https://doi.org/10.5194/acp-19-13911-2019, https://doi.org/10.5194/acp-19-13911-2019, 2019
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This paper describes the methods for combining models and data to understand how nutrients and pollutants move through natural systems. The methods are analogous to the process of weather forecasting in which previous information is combined with new observations and a model to improve our knowledge of the internal state of the physical system. The methods appear highly diverse but the paper shows that they are all examples of a single underlying formalism.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Bo Zheng, Frederic Chevallier, Yi Yin, Philippe Ciais, Audrey Fortems-Cheiney, Merritt N. Deeter, Robert J. Parker, Yilong Wang, Helen M. Worden, and Yuanhong Zhao
Earth Syst. Sci. Data, 11, 1411–1436, https://doi.org/10.5194/essd-11-1411-2019, https://doi.org/10.5194/essd-11-1411-2019, 2019
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We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric carbon monoxide (CO) variations to its sources and sinks in order to achieve a full closure of the global CO budget during 2000–2017. We identify a declining trend in the global CO budget since 2000, driven by reduced anthropogenic emissions in the US, Europe, and China, as well as by reduced biomass burning emissions globally, especially in equatorial Africa.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Anna Agustí-Panareda, Michail Diamantakis, Sébastien Massart, Frédéric Chevallier, Joaquín Muñoz-Sabater, Jérôme Barré, Roger Curcoll, Richard Engelen, Bavo Langerock, Rachel M. Law, Zoë Loh, Josep Anton Morguí, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Coleen Roehl, Alex T. Vermeulen, Thorsten Warneke, and Debra Wunch
Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, https://doi.org/10.5194/acp-19-7347-2019, 2019
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This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO2 patterns associated with evolving weather. The modelling of CO2 weather is crucial to interpret the variability from ground-based and satellite CO2 observations, which can then be used to infer CO2 fluxes in atmospheric inversions. The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO2 flux distribution.
Felix R. Vogel, Matthias Frey, Johannes Staufer, Frank Hase, Grégoire Broquet, Irène Xueref-Remy, Frédéric Chevallier, Philippe Ciais, Mahesh Kumar Sha, Pascale Chelin, Pascal Jeseck, Christof Janssen, Yao Té, Jochen Groß, Thomas Blumenstock, Qiansi Tu, and Johannes Orphal
Atmos. Chem. Phys., 19, 3271–3285, https://doi.org/10.5194/acp-19-3271-2019, https://doi.org/10.5194/acp-19-3271-2019, 2019
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Providing timely information on greenhouse gas emissions to stakeholders at sub-national scale is an emerging challenge and understanding urban CO2 levels is one key aspect. This study uses atmospheric observations of total column CO2 and compares them to numerical simulations to investigate CO2 levels in the Paris metropolitan area due to natural fluxes and anthropogenic emissions. Our measurements reveal the influence of locally added CO2, which our model is also able to predict.
Benjamin Gaubert, Britton B. Stephens, Sourish Basu, Frédéric Chevallier, Feng Deng, Eric A. Kort, Prabir K. Patra, Wouter Peters, Christian Rödenbeck, Tazu Saeki, David Schimel, Ingrid Van der Laan-Luijkx, Steven Wofsy, and Yi Yin
Biogeosciences, 16, 117–134, https://doi.org/10.5194/bg-16-117-2019, https://doi.org/10.5194/bg-16-117-2019, 2019
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We have compared global carbon budgets calculated from numerical inverse models and CO2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO2 from aircraft measurements. We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.
Christopher W. O'Dell, Annmarie Eldering, Paul O. Wennberg, David Crisp, Michael R. Gunson, Brendan Fisher, Christian Frankenberg, Matthäus Kiel, Hannakaisa Lindqvist, Lukas Mandrake, Aronne Merrelli, Vijay Natraj, Robert R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Drouin, Fabiano Oyafuso, Albert Chang, James McDuffie, Michael Smyth, David F. Baker, Sourish Basu, Frédéric Chevallier, Sean M. R. Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, Coleen M. Roehl, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Osamu Uchino, and Voltaire A. Velazco
Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, https://doi.org/10.5194/amt-11-6539-2018, 2018
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Marine Remaud, Frédéric Chevallier, Anne Cozic, Xin Lin, and Philippe Bousquet
Geosci. Model Dev., 11, 4489–4513, https://doi.org/10.5194/gmd-11-4489-2018, https://doi.org/10.5194/gmd-11-4489-2018, 2018
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We compare several versions of a global atmospheric transport model for the simulation of CO2. The representation of subgrid-scale processes modulates the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere. It has the largest impact over Brazil. Refining the horizontal resolution improves the simulation near emission hotspots or along the coastlines. The sensitivities to the land surface model and to the increase in vertical resolution are marginal.
Maarten Krol, Marco de Bruine, Lars Killaars, Huug Ouwersloot, Andrea Pozzer, Yi Yin, Frederic Chevallier, Philippe Bousquet, Prabir Patra, Dmitry Belikov, Shamil Maksyutov, Sandip Dhomse, Wuhu Feng, and Martyn P. Chipperfield
Geosci. Model Dev., 11, 3109–3130, https://doi.org/10.5194/gmd-11-3109-2018, https://doi.org/10.5194/gmd-11-3109-2018, 2018
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The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced. Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis.
Sourish Basu, David F. Baker, Frédéric Chevallier, Prabir K. Patra, Junjie Liu, and John B. Miller
Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, https://doi.org/10.5194/acp-18-7189-2018, 2018
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CO2 measurements from the global surface network and CO2 estimates from satellites such as the Orbiting Carbon Observatory 2 (OCO-2) are currently used to quantify the surface sources and sinks of CO2, using what we know about atmospheric transport of gases. In this work, we quantify the uncertainties in those surface source/sink estimates that stem from errors in our atmospheric transport models, using an observing system simulation experiment (OSSE).
Yilong Wang, Grégoire Broquet, Philippe Ciais, Frédéric Chevallier, Felix Vogel, Lin Wu, Yi Yin, Rong Wang, and Shu Tao
Atmos. Chem. Phys., 18, 4229–4250, https://doi.org/10.5194/acp-18-4229-2018, https://doi.org/10.5194/acp-18-4229-2018, 2018
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This paper assesses the potential of atmospheric 14CO2 observations and a global inversion system to solve for fossil fuel CO2 (FFCO2) emissions in Europe. The estimate of monthly emission budgets is largely improved in high emitting regions. The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO2 emissions.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
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The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Irène Xueref-Remy, Elsa Dieudonné, Cyrille Vuillemin, Morgan Lopez, Christine Lac, Martina Schmidt, Marc Delmotte, Frédéric Chevallier, François Ravetta, Olivier Perrussel, Philippe Ciais, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, T. Gerard Spain, and Christophe Ampe
Atmos. Chem. Phys., 18, 3335–3362, https://doi.org/10.5194/acp-18-3335-2018, https://doi.org/10.5194/acp-18-3335-2018, 2018
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Urbanized and industrialized areas are the largest source of fossil CO2. This work analyses the atmospheric CO2 variability observed from the first in situ network deployed in the Paris megacity area. Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO2 records.
Grégoire Broquet, François-Marie Bréon, Emmanuel Renault, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Frédéric Chevallier, Lin Wu, and Philippe Ciais
Atmos. Meas. Tech., 11, 681–708, https://doi.org/10.5194/amt-11-681-2018, https://doi.org/10.5194/amt-11-681-2018, 2018
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This study assesses the potential of space-borne imagery of CO2 atmospheric concentrations for monitoring the emissions from the Paris area. Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO2 emissions for urban areas with CO2 observations from satellites, and calls for more technological innovations in the remote sensing of CO2 and in the models that exploit it.
Chao Yue, Philippe Ciais, Ana Bastos, Frederic Chevallier, Yi Yin, Christian Rödenbeck, and Taejin Park
Atmos. Chem. Phys., 17, 13903–13919, https://doi.org/10.5194/acp-17-13903-2017, https://doi.org/10.5194/acp-17-13903-2017, 2017
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The year 2015 appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since 2000 according to satellite observation, but the atmospheric CO2 growth rate is also the highest since 1959. We found that this is due to a only moderate land carbon sink, because high growing-season sink in northern lands has been partly offset by autumn and winter release and the late-year El Niño has led to an abrupt transition to land source in the tropics.
Anna M. Michalak, Nina A. Randazzo, and Frédéric Chevallier
Atmos. Chem. Phys., 17, 7405–7421, https://doi.org/10.5194/acp-17-7405-2017, https://doi.org/10.5194/acp-17-7405-2017, 2017
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The use of inverse modeling for quantifying emissions of greenhouse gases is increasing. Estimates are very difficult to evaluate objectively, however, due to limited atmospheric observations and the lack of direct emissions measurements at compatible scales. Diagnostic tools have been proposed to partially circumvent these limitations. This paper presents the first systematic review of the scope and applicability of these tools for atmospheric inversions of long-lived greenhouse gases.
Jerónimo Escribano, Olivier Boucher, Frédéric Chevallier, and Nicolás Huneeus
Atmos. Chem. Phys., 17, 7111–7126, https://doi.org/10.5194/acp-17-7111-2017, https://doi.org/10.5194/acp-17-7111-2017, 2017
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Top-down estimates of mineral dust flux usually rely on a single observational dataset whose observational errors propagate onto the emission estimates. Aerosol optical depth from five satellites are assimilated one by one into a source inversion system over northern Africa. We find a relatively large dispersion in flux estimates among the five experiments, which can likely be attributed to differences in the assimilated observational datasets and their associated error statistics.
Yi Yin, Frederic Chevallier, Philippe Ciais, Gregoire Broquet, Anne Cozic, Sophie Szopa, and Yilong Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-166, https://doi.org/10.5194/acp-2017-166, 2017
Revised manuscript not accepted
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CO inverse modelling studies have so far reported significant discrepancies between model concentrations optimised with the Measurement of Pollution in the Troposphere (MOPITT) satellite retrievals and surface in-situ measurements. Here, we assess how well a global CTM fits a large variety of independent CO observations before and after assimilating MOPITTv6 retrievals to optimise CO sources/sink and discuss potential sources of errors and their implications for global CO modelling studies.
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
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The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Lamia Ammoura, Irène Xueref-Remy, Felix Vogel, Valérie Gros, Alexia Baudic, Bernard Bonsang, Marc Delmotte, Yao Té, and Frédéric Chevallier
Atmos. Chem. Phys., 16, 15653–15664, https://doi.org/10.5194/acp-16-15653-2016, https://doi.org/10.5194/acp-16-15653-2016, 2016
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We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed. We apply it to estimate monthly ratios between CO2, CO and some VOCs from atmospheric measurement datasets acquired in the centre of Paris between 2010 and 2014. We find that this approach is little sensitive to the regional background level definition. With this new method, we may reveal spatial and seasonal variability in the ratios in Paris.
Johannes Staufer, Grégoire Broquet, François-Marie Bréon, Vincent Puygrenier, Frédéric Chevallier, Irène Xueref-Rémy, Elsa Dieudonné, Morgan Lopez, Martina Schmidt, Michel Ramonet, Olivier Perrussel, Christine Lac, Lin Wu, and Philippe Ciais
Atmos. Chem. Phys., 16, 14703–14726, https://doi.org/10.5194/acp-16-14703-2016, https://doi.org/10.5194/acp-16-14703-2016, 2016
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Natasha MacBean, Philippe Peylin, Frédéric Chevallier, Marko Scholze, and Gregor Schürmann
Geosci. Model Dev., 9, 3569–3588, https://doi.org/10.5194/gmd-9-3569-2016, https://doi.org/10.5194/gmd-9-3569-2016, 2016
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Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model. Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context. This paper demonstrates and discusses the issues involved using toy models and examples from existing literature.
Philippe Peylin, Cédric Bacour, Natasha MacBean, Sébastien Leonard, Peter Rayner, Sylvain Kuppel, Ernest Koffi, Abdou Kane, Fabienne Maignan, Frédéric Chevallier, Philippe Ciais, and Pascal Prunet
Geosci. Model Dev., 9, 3321–3346, https://doi.org/10.5194/gmd-9-3321-2016, https://doi.org/10.5194/gmd-9-3321-2016, 2016
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The study describes a carbon cycle data assimilation system that uses satellite observations of vegetation activity, net ecosystem exchange of carbon and water at many sites and atmospheric CO2 concentrations, in order to optimize the parameters of the ORCHIDEE land surface model. The optimized model is able to fit all three data streams leading to a land carbon uptake similar to independent estimates, which opens new perspectives for better prediction of the land carbon balance.
Anna Agustí-Panareda, Sébastien Massart, Frédéric Chevallier, Gianpaolo Balsamo, Souhail Boussetta, Emanuel Dutra, and Anton Beljaars
Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016, https://doi.org/10.5194/acp-16-10399-2016, 2016
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This paper presents a method to adjust the sinks and sources of CO2 associated with land ecosystems within a global atmospheric CO2 forecasting system in order to reduce the errors in the forecast. This is done by combining information on (1) retrospective fluxes estimated by a global flux inversion system, (2) land-use information, and (3) simulated fluxes from the model. Because the method is simple and flexible, it can easily run in real time as part of a forecasting system.
Cindy Cressot, Isabelle Pison, Peter J. Rayner, Philippe Bousquet, Audrey Fortems-Cheiney, and Frédéric Chevallier
Atmos. Chem. Phys., 16, 9089–9108, https://doi.org/10.5194/acp-16-9089-2016, https://doi.org/10.5194/acp-16-9089-2016, 2016
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Several hypothesis have been made to attribute current trends in atmospheric methane to particular regions. In this context, this work aims at evaluating how well anomalies in methane emissions can be detected at the regional scale with currently available observing systems: two space-borne instruments and a surface network. Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment.
Peter Rayner, Anna M. Michalak, and Frédéric Chevallier
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-148, https://doi.org/10.5194/gmd-2016-148, 2016
Revised manuscript not accepted
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Numerical models are among our most important tools for understanding and prediction. Models include quantities or equations that we cannot verify directly. We learn about these unknowns by comparing model output with observations and using some algorithm to improve the inputs. We show here that the many methods for doing this are special cases of underlying statistics. This provides a unified way of comparing and contrasting such methods.
Christian Frankenberg, Susan S. Kulawik, Steven C. Wofsy, Frédéric Chevallier, Bruce Daube, Eric A. Kort, Christopher O'Dell, Edward T. Olsen, and Gregory Osterman
Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, https://doi.org/10.5194/acp-16-7867-2016, 2016
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We use observations from the HIAPER Pole-to-Pole Observations (HIPPO) flights from January 2009 through September 2011 to validate CO2 measurements from satellites (GOSAT, TES, AIRS) and atmospheric inversion models (CarbonTracker CT2013B, MACC v13r1).
Lin Wu, Grégoire Broquet, Philippe Ciais, Valentin Bellassen, Felix Vogel, Frédéric Chevallier, Irène Xueref-Remy, and Yilong Wang
Atmos. Chem. Phys., 16, 7743–7771, https://doi.org/10.5194/acp-16-7743-2016, https://doi.org/10.5194/acp-16-7743-2016, 2016
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This paper advances atmospheric inversion of city CO2 emissions as follows: (1) illustrate how inversion methodology can be tailored to deal with very large urban networks of sensors measuring CO2 concentrations; (2) demonstrate that atmospheric inversion could be a relevant tool of Monitoring, Reporting and Verification (MRV) of city CO2 emissions; (3) clarify the theoretical potential of inversion for reducing uncertainties in the estimates of citywide total and sectoral CO2 emissions.
Alex Boon, Grégoire Broquet, Deborah J. Clifford, Frédéric Chevallier, David M. Butterfield, Isabelle Pison, Michel Ramonet, Jean-Daniel Paris, and Philippe Ciais
Atmos. Chem. Phys., 16, 6735–6756, https://doi.org/10.5194/acp-16-6735-2016, https://doi.org/10.5194/acp-16-6735-2016, 2016
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We measured carbon dioxide and methane concentrations at four near-ground sites located in London, 2012. We investigated the potential for using these measurements, alongside numerical modelling, to help us to understand urban greenhouse gas emissions. Low-level sites were highly sensitive to local emissions, which questions our ability to use measurements from near-ground sites in cities in some modelling applications. A gradient approach was found to be beneficial to reduce model–data errors.
Sudhanshu Pandey, Sander Houweling, Maarten Krol, Ilse Aben, Frédéric Chevallier, Edward J. Dlugokencky, Luciana V. Gatti, Emanuel Gloor, John B. Miller, Rob Detmers, Toshinobu Machida, and Thomas Röckmann
Atmos. Chem. Phys., 16, 5043–5062, https://doi.org/10.5194/acp-16-5043-2016, https://doi.org/10.5194/acp-16-5043-2016, 2016
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This study investigates the constraint provided by measurements of Xratio (XCH4/XCO2) from space on surface fluxes of CH4 and CO2. We apply the ratio inversion method described in Pandey et al. (2015) to Xratio retrievals from the GOSAT with the TM5-4DVAR inverse modeling system, to constrain the surface fluxes of CH4 and CO2 for 2009 and 2010. The results are compared to proxy CH4 inversions using model-derived-XCO2 mixing ratios from CarbonTracker and MACC.
Antoine Berchet, Philippe Bousquet, Isabelle Pison, Robin Locatelli, Frédéric Chevallier, Jean-Daniel Paris, Ed J. Dlugokencky, Tuomas Laurila, Juha Hatakka, Yrjo Viisanen, Doug E. J. Worthy, Euan Nisbet, Rebecca Fisher, James France, David Lowry, Viktor Ivakhov, and Ove Hermansen
Atmos. Chem. Phys., 16, 4147–4157, https://doi.org/10.5194/acp-16-4147-2016, https://doi.org/10.5194/acp-16-4147-2016, 2016
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We propose insights based on atmospheric observations around the Arctic circle to evaluate estimates of methane emissions to the atmosphere from the East Siberian Arctic Shelf. Based on a comprehensive statistical analysis of the observations and of high-resolution transport simulations, annual methane emissions from ESAS are estimated to range from 0.0 to 4.5 TgCH4 yr−1, with a maximum in summer and very low emissions in winter.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
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To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
Sébastien Massart, Anna Agustí-Panareda, Jens Heymann, Michael Buchwitz, Frédéric Chevallier, Maximilian Reuter, Michael Hilker, John P. Burrows, Nicholas M. Deutscher, Dietrich G. Feist, Frank Hase, Ralf Sussmann, Filip Desmet, Manvendra K. Dubey, David W. T. Griffith, Rigel Kivi, Christof Petri, Matthias Schneider, and Voltaire A. Velazco
Atmos. Chem. Phys., 16, 1653–1671, https://doi.org/10.5194/acp-16-1653-2016, https://doi.org/10.5194/acp-16-1653-2016, 2016
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This study presents the European Centre for Medium-Range Weather Forecasts (ECMWF) monitoring of atmospheric CO2 using measurements from the Greenhouse gases Observing Satellite (GOSAT). We show that the modelled CO2 has a better precision than standard CO2 satellite products compared to ground-based measurements. We also present the CO2 forecast based on our best knowledge of the atmospheric CO2 distribution. We show that it has skill to forecast the largest scale CO2 patterns up to day 5.
Y. Yin, F. Chevallier, P. Ciais, G. Broquet, A. Fortems-Cheiney, I. Pison, and M. Saunois
Atmos. Chem. Phys., 15, 13433–13451, https://doi.org/10.5194/acp-15-13433-2015, https://doi.org/10.5194/acp-15-13433-2015, 2015
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We studied the global CO concentration decline over the recent decade with a sophisticated atmospheric inversion system assimilating MOPITT CO retrievals, surface methane and surface methyl chloroform in situ measurements. The inversion interprets the CO concentration decline as a 23% decrease in the CO emissions from 2002 to 2011, twice the negative trend estimated by emission inventories. In contrast to bottom-up inventories, we find negative trends over China and South-east Asia.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
H. Lindqvist, C. W. O'Dell, S. Basu, H. Boesch, F. Chevallier, N. Deutscher, L. Feng, B. Fisher, F. Hase, M. Inoue, R. Kivi, I. Morino, P. I. Palmer, R. Parker, M. Schneider, R. Sussmann, and Y. Yoshida
Atmos. Chem. Phys., 15, 13023–13040, https://doi.org/10.5194/acp-15-13023-2015, https://doi.org/10.5194/acp-15-13023-2015, 2015
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Atmospheric carbon dioxide concentration varies seasonally mainly due to plant photosynthesis in the Northern Hemisphere. We found that the satellite GOSAT can capture this variability from space to within 1ppm. We also found that models can differ by more than 1ppm. This implies that the satellite measurements could be useful in evaluating models and their prior estimates of carbon dioxide sources and sinks.
N. Kadygrov, G. Broquet, F. Chevallier, L. Rivier, C. Gerbig, and P. Ciais
Atmos. Chem. Phys., 15, 12765–12787, https://doi.org/10.5194/acp-15-12765-2015, https://doi.org/10.5194/acp-15-12765-2015, 2015
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We study the potential of the European Integrated Carbon Observing System (ICOS) atmospheric network for estimating European CO2 ecosystem fluxes. Regional atmospheric inversions with synthetic data are used to derive it in terms of statistical uncertainty. This potential is high in western Europe and future extensions of the network will increase it in eastern Europe. Future improvements of the models underlying the inversion should also significantly decrease uncertainties at high resolution.
R. J. Parker, H. Boesch, K. Byckling, A. J. Webb, P. I. Palmer, L. Feng, P. Bergamaschi, F. Chevallier, J. Notholt, N. Deutscher, T. Warneke, F. Hase, R. Sussmann, S. Kawakami, R. Kivi, D. W. T. Griffith, and V. Velazco
Atmos. Meas. Tech., 8, 4785–4801, https://doi.org/10.5194/amt-8-4785-2015, https://doi.org/10.5194/amt-8-4785-2015, 2015
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Atmospheric CH4 is an important greenhouse gas. Long-term global observations are necessary to understand its behaviour, with satellite observations playing a key role. The "proxy" retrieval method is one of the most successful but relies on the contribution from atmospheric CO2 models. This work assesses the significance of the uncertainty from the model CO2 within the retrieval and determines that despite this uncertainty the data are still valuable for determining sources and sinks of CH4.
F. Chevallier
Atmos. Chem. Phys., 15, 11133–11145, https://doi.org/10.5194/acp-15-11133-2015, https://doi.org/10.5194/acp-15-11133-2015, 2015
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We demonstrate that the current two-step approach to infer the CO2 surface fluxes from satellite measured radiances, with CO2 retrievals as an intermediate product, is not optimal. This suboptimality corrupts the 4D information flow from the radiance measurements to the surface flux estimates. It is amplified by current retrieval strategies where prior errors are much larger than the performance of prior CO2 simulations used in atmospheric inversions.
A. Berchet, I. Pison, F. Chevallier, J.-D. Paris, P. Bousquet, J.-L. Bonne, M. Y. Arshinov, B. D. Belan, C. Cressot, D. K. Davydov, E. J. Dlugokencky, A. V. Fofonov, A. Galanin, J. Lavrič, T. Machida, R. Parker, M. Sasakawa, R. Spahni, B. D. Stocker, and J. Winderlich
Biogeosciences, 12, 5393–5414, https://doi.org/10.5194/bg-12-5393-2015, https://doi.org/10.5194/bg-12-5393-2015, 2015
R. Locatelli, P. Bousquet, M. Saunois, F. Chevallier, and C. Cressot
Atmos. Chem. Phys., 15, 9765–9780, https://doi.org/10.5194/acp-15-9765-2015, https://doi.org/10.5194/acp-15-9765-2015, 2015
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
F. M. Bréon, G. Broquet, V. Puygrenier, F. Chevallier, I. Xueref-Remy, M. Ramonet, E. Dieudonné, M. Lopez, M. Schmidt, O. Perrussel, and P. Ciais
Atmos. Chem. Phys., 15, 1707–1724, https://doi.org/10.5194/acp-15-1707-2015, https://doi.org/10.5194/acp-15-1707-2015, 2015
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
L. Ammoura, I. Xueref-Remy, V. Gros, A. Baudic, B. Bonsang, J.-E. Petit, O. Perrussel, N. Bonnaire, J. Sciare, and F. Chevallier
Atmos. Chem. Phys., 14, 12871–12882, https://doi.org/10.5194/acp-14-12871-2014, https://doi.org/10.5194/acp-14-12871-2014, 2014
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We present the first study of CO2, VOCs and NOx measured all together in a road tunnel around the Paris megacity with the aim to quantify the ratios of these species co-emitted within traffic emissions. It allows us to independently assess some of the ratios provided in the latest Paris emission inventory. It also reveals a large variability of the ratios to CO2, implying that traffic does not have a unique imprint in the urban plume, but rather leaves various signatures.
A. Agustí-Panareda, S. Massart, F. Chevallier, S. Boussetta, G. Balsamo, A. Beljaars, P. Ciais, N. M. Deutscher, R. Engelen, L. Jones, R. Kivi, J.-D. Paris, V.-H. Peuch, V. Sherlock, A. T. Vermeulen, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, https://doi.org/10.5194/acp-14-11959-2014, 2014
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This paper presents a new operational CO2 forecast product as part of the Copernicus Atmospheric Services suite of atmospheric composition products, using the state-of-the-art numerical weather prediction model from the European Centre of Medium-Range Weather Forecasts.
The evaluation with independent observations shows that the forecast has skill in predicting the synoptic variability of CO2. The online simulation of CO2 fluxes from vegetation contributes to this skill.
S. Kuppel, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti
Geosci. Model Dev., 7, 2581–2597, https://doi.org/10.5194/gmd-7-2581-2014, https://doi.org/10.5194/gmd-7-2581-2014, 2014
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A consistent calibration of an advanced land surface model was performed by grouping in situ information on land-atmosphere exchanges of carbon and water using broad ecosystem and climate classes. Signatures of improved carbon cycle simulations were found across spatial and temporal scales, along with insights into current model limitations. These results hold promising perspectives within the ongoing efforts towards building robust model-data fusion frameworks for earth system models.
C. Wilson, M. P. Chipperfield, M. Gloor, and F. Chevallier
Geosci. Model Dev., 7, 2485–2500, https://doi.org/10.5194/gmd-7-2485-2014, https://doi.org/10.5194/gmd-7-2485-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
S. Massart, A. Agusti-Panareda, I. Aben, A. Butz, F. Chevallier, C. Crevoisier, R. Engelen, C. Frankenberg, and O. Hasekamp
Atmos. Chem. Phys., 14, 6139–6158, https://doi.org/10.5194/acp-14-6139-2014, https://doi.org/10.5194/acp-14-6139-2014, 2014
R. L. Thompson, K. Ishijima, E. Saikawa, M. Corazza, U. Karstens, P. K. Patra, P. Bergamaschi, F. Chevallier, E. Dlugokencky, R. G. Prinn, R. F. Weiss, S. O'Doherty, P. J. Fraser, L. P. Steele, P. B. Krummel, A. Vermeulen, Y. Tohjima, A. Jordan, L. Haszpra, M. Steinbacher, S. Van der Laan, T. Aalto, F. Meinhardt, M. E. Popa, J. Moncrieff, and P. Bousquet
Atmos. Chem. Phys., 14, 6177–6194, https://doi.org/10.5194/acp-14-6177-2014, https://doi.org/10.5194/acp-14-6177-2014, 2014
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
R. L. Thompson, F. Chevallier, A. M. Crotwell, G. Dutton, R. L. Langenfelds, R. G. Prinn, R. F. Weiss, Y. Tohjima, T. Nakazawa, P. B. Krummel, L. P. Steele, P. Fraser, S. O'Doherty, K. Ishijima, and S. Aoki
Atmos. Chem. Phys., 14, 1801–1817, https://doi.org/10.5194/acp-14-1801-2014, https://doi.org/10.5194/acp-14-1801-2014, 2014
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
C. Cressot, F. Chevallier, P. Bousquet, C. Crevoisier, E. J. Dlugokencky, A. Fortems-Cheiney, C. Frankenberg, R. Parker, I. Pison, R. A. Scheepmaker, S. A. Montzka, P. B. Krummel, L. P. Steele, and R. L. Langenfelds
Atmos. Chem. Phys., 14, 577–592, https://doi.org/10.5194/acp-14-577-2014, https://doi.org/10.5194/acp-14-577-2014, 2014
P. Peylin, R. M. Law, K. R. Gurney, F. Chevallier, A. R. Jacobson, T. Maki, Y. Niwa, P. K. Patra, W. Peters, P. J. Rayner, C. Rödenbeck, I. T. van der Laan-Luijkx, and X. Zhang
Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, https://doi.org/10.5194/bg-10-6699-2013, 2013
R. Locatelli, P. Bousquet, F. Chevallier, A. Fortems-Cheney, S. Szopa, M. Saunois, A. Agusti-Panareda, D. Bergmann, H. Bian, P. Cameron-Smith, M. P. Chipperfield, E. Gloor, S. Houweling, S. R. Kawa, M. Krol, P. K. Patra, R. G. Prinn, M. Rigby, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 9917–9937, https://doi.org/10.5194/acp-13-9917-2013, https://doi.org/10.5194/acp-13-9917-2013, 2013
G. Broquet, F. Chevallier, F.-M. Bréon, N. Kadygrov, M. Alemanno, F. Apadula, S. Hammer, L. Haszpra, F. Meinhardt, J. A. Morguí, J. Necki, S. Piacentino, M. Ramonet, M. Schmidt, R. L. Thompson, A. T. Vermeulen, C. Yver, and P. Ciais
Atmos. Chem. Phys., 13, 9039–9056, https://doi.org/10.5194/acp-13-9039-2013, https://doi.org/10.5194/acp-13-9039-2013, 2013
A. Berchet, I. Pison, F. Chevallier, P. Bousquet, S. Conil, M. Geever, T. Laurila, J. Lavrič, M. Lopez, J. Moncrieff, J. Necki, M. Ramonet, M. Schmidt, M. Steinbacher, and J. Tarniewicz
Atmos. Chem. Phys., 13, 7115–7132, https://doi.org/10.5194/acp-13-7115-2013, https://doi.org/10.5194/acp-13-7115-2013, 2013
N. Huneeus, O. Boucher, and F. Chevallier
Atmos. Chem. Phys., 13, 6555–6573, https://doi.org/10.5194/acp-13-6555-2013, https://doi.org/10.5194/acp-13-6555-2013, 2013
U. Schuster, G. A. McKinley, N. Bates, F. Chevallier, S. C. Doney, A. R. Fay, M. González-Dávila, N. Gruber, S. Jones, J. Krijnen, P. Landschützer, N. Lefèvre, M. Manizza, J. Mathis, N. Metzl, A. Olsen, A. F. Rios, C. Rödenbeck, J. M. Santana-Casiano, T. Takahashi, R. Wanninkhof, and A. J. Watson
Biogeosciences, 10, 607–627, https://doi.org/10.5194/bg-10-607-2013, https://doi.org/10.5194/bg-10-607-2013, 2013
Related subject area
Atmospheric sciences
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
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
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
Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0
Evaluation of ECMWF IFS-AER (CAMS) operational forecasts during cycle 41r1–46r1 with calibrated ceilometer profiles over Germany
Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50
Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates
MLAir (v1.0) – a tool to enable fast and flexible machine learning on air data time series
snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation
Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya
On the suitability of second-order accurate finite-volume solvers for the simulation of atmospheric boundary layer flow
An urban large-eddy-simulation-based dispersion model for marginal grid resolutions: CAIRDIO v1.0
Applying a new integrated mass-flux adjustment filter in rapid update cycling of convective-scale data assimilation for the COSMO model (v5.07)
On the model uncertainties in Bayesian source reconstruction using an ensemble of weather predictions, the emission inverse modelling system FREAR v1.0, and the Lagrangian transport and dispersion model Flexpart v9.0.2
Evaluation of the interactive stratospheric ozone (O3v2) module in the E3SM version 1 Earth system model
Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications
The Vertical City Weather Generator (VCWG v1.3.2)
A zero-dimensional view of atmospheric degradation of levoglucosan (LEVCHEM_v1) using numerical chamber simulations
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
The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates
Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1
Development of WRF/CUACE v1.0 model and its preliminary application in simulating air quality in China
PyCHAM (v2.1.1): a Python box model for simulating aerosol chambers
Surface representation impacts on turbulent heat fluxes in WRF (v.4.1.3)
A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54
Investigating the importance of sub-grid particle formation in point source plumes over eastern China using IAP-AACM with a sub-grid parameterization
Improving dust simulations in WRF-Chem v4.1.3 coupled with the GOCART aerosol module
FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 2: Model validation
Implementation of a synthetic inflow turbulence generator in idealised WRF v3.6.1 large eddy simulations under neutral atmospheric conditions
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.
Sara M. Blichner, Moa K. Sporre, Risto Makkonen, and Terje K. Berntsen
Geosci. Model Dev., 14, 3335–3359, https://doi.org/10.5194/gmd-14-3335-2021, https://doi.org/10.5194/gmd-14-3335-2021, 2021
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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 %.
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.
Dana L. McGuffin, Yuanlong Huang, Richard C. Flagan, Tuukka Petäjä, B. Erik Ydstie, and Peter J. Adams
Geosci. Model Dev., 14, 1821–1839, https://doi.org/10.5194/gmd-14-1821-2021, https://doi.org/10.5194/gmd-14-1821-2021, 2021
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Atmospheric particle formation, emissions, and growth process rates are significant sources of uncertainty in predicting climate change. We aim to reduce that uncertainty by using measurements from several ground-based sites across Europe. We developed an estimation technique to adapt the governing process rates so model–measurement bias decays. The estimation framework developed has potential to improve model predictions while providing insight into the underlying atmospheric particle physics.
Harald Flentje, Ina Mattis, Zak Kipling, Samuel Rémy, and Werner Thomas
Geosci. Model Dev., 14, 1721–1751, https://doi.org/10.5194/gmd-14-1721-2021, https://doi.org/10.5194/gmd-14-1721-2021, 2021
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Atmospheric aerosols crucially impact air quality, climate and weather. Thus, global model forecasts of atmospheric constituents are published daily on the ECMWF website and are regularly verified by the CAMS service team. The IFS-AER model is largely able to reproduce observed 3-D distributions of the important particle types over Germany. The particle concentration is mostly captured within several tens of percent, but quantification of some specific processes still remains a challenge.
Jianhui Jiang, Imad El Haddad, Sebnem Aksoyoglu, Giulia Stefenelli, Amelie Bertrand, Nicolas Marchand, Francesco Canonaco, Jean-Eudes Petit, Olivier Favez, Stefania Gilardoni, Urs Baltensperger, and André S. H. Prévôt
Geosci. Model Dev., 14, 1681–1697, https://doi.org/10.5194/gmd-14-1681-2021, https://doi.org/10.5194/gmd-14-1681-2021, 2021
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We developed a box model with a volatility basis set to simulate organic aerosol (OA) from biomass burning and optimized the vapor-wall-loss-corrected OA yields with a genetic algorithm. The optimized parameterizations were then implemented in the air quality model CAMx v6.5. Comparisons with ambient measurements indicate that the vapor-wall-loss-corrected parameterization effectively improves the model performance in predicting OA, which reduced the mean fractional bias from −72.9 % to −1.6 %.
Oliver Branch, Thomas Schwitalla, Marouane Temimi, Ricardo Fonseca, Narendra Nelli, Michael Weston, Josipa Milovac, and Volker Wulfmeyer
Geosci. Model Dev., 14, 1615–1637, https://doi.org/10.5194/gmd-14-1615-2021, https://doi.org/10.5194/gmd-14-1615-2021, 2021
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Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates where extreme events like heat waves, flash floods, and dust storms are becoming more severe. This study employs a high-resolution simulation with the WRF-NOAHMP model, and the output is compared with seasonal observation data from 50 weather stations. This type of verification is vital to identify model deficiencies and improve forecasting systems for arid regions.
Lukas Hubert Leufen, Felix Kleinert, and Martin G. Schultz
Geosci. Model Dev., 14, 1553–1574, https://doi.org/10.5194/gmd-14-1553-2021, https://doi.org/10.5194/gmd-14-1553-2021, 2021
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MLAir provides a coherent end-to-end structure for a typical time series analysis workflow using machine learning (ML). MLAir is adaptable to a wide range of ML use cases, focusing in particular on deep learning. The user has a free hand with the ML model itself and can select from different methods during preprocessing, training, and postprocessing. MLAir offers tools to track the experiment conduction, documents necessary ML parameters, and creates a variety of publication-ready plots.
Davide Ori, Leonie von Terzi, Markus Karrer, and Stefan Kneifel
Geosci. Model Dev., 14, 1511–1531, https://doi.org/10.5194/gmd-14-1511-2021, https://doi.org/10.5194/gmd-14-1511-2021, 2021
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Snowflakes have very complex shapes, and modeling their properties requires vast computing power. We produced a large number of realistic snowflakes and modeled their average properties by leveraging their fractal structure. Our approach allows modeling the properties of big ensembles of snowflakes, taking into account their natural variability, at a much lower cost. This enables the usage of remote sensing instruments, such as radars, to monitor the evolution of clouds and precipitation.
Jaydeep Singh, Narendra Singh, Narendra Ojha, Amit Sharma, Andrea Pozzer, Nadimpally Kiran Kumar, Kunjukrishnapillai Rajeev, Sachin S. Gunthe, and V. Rao Kotamarthi
Geosci. Model Dev., 14, 1427–1443, https://doi.org/10.5194/gmd-14-1427-2021, https://doi.org/10.5194/gmd-14-1427-2021, 2021
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Atmospheric models often have limitations in simulating the geographically complex and climatically important central Himalayan region. In this direction, we have performed regional modeling at high resolutions to improve the simulation of meteorology and dynamics through a better representation of the topography. The study has implications for further model applications to investigate the effects of anthropogenic pressure over the Himalaya.
Beatrice Giacomini and Marco G. Giometto
Geosci. Model Dev., 14, 1409–1426, https://doi.org/10.5194/gmd-14-1409-2021, https://doi.org/10.5194/gmd-14-1409-2021, 2021
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The present work evaluates the suitability of an important class of second-order finite-volume solvers for the large-eddy simulation of atmospheric boundary- layer flows. Results show that these solvers do not capture the dominant mechanisms responsible for momentum transport in boundary layers, leading to a misprediction of relevant flow statistics and to an enhanced sensitivity of the solution to variations in grid resolution.
Michael Weger, Oswald Knoth, and Bernd Heinold
Geosci. Model Dev., 14, 1469–1492, https://doi.org/10.5194/gmd-14-1469-2021, https://doi.org/10.5194/gmd-14-1469-2021, 2021
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A new numerical air-quality transport model for cities is presented, in which buildings are described diffusively. The used diffusive-obstacles approach helps to reduce the computational costs for high-resolution simulations as the grid spacing can be more coarse than in traditional approaches. The research which led to this model development was primarily motivated by the need for a computationally feasible downscaling tool for urban wind and pollution fields from meteorological model output.
Yuefei Zeng, Alberto de Lozar, Tijana Janjic, and Axel Seifert
Geosci. Model Dev., 14, 1295–1307, https://doi.org/10.5194/gmd-14-1295-2021, https://doi.org/10.5194/gmd-14-1295-2021, 2021
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A new integrated mass-flux adjustment filter is introduced and examined with an idealized setup for convective-scale radar data assimilation. It is found that the new filter slightly reduces the accuracy of background and analysis states; however, it preserves the main structure of cold pools and primary mesocyclone properties of supercells. More importantly, it successfully diminishes the imbalance in the analysis considerably and improves the forecasts.
Pieter De Meutter, Ian Hoffman, and Kurt Ungar
Geosci. Model Dev., 14, 1237–1252, https://doi.org/10.5194/gmd-14-1237-2021, https://doi.org/10.5194/gmd-14-1237-2021, 2021
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Inverse atmospheric transport modelling is an important tool in several disciplines. However, the specification of atmospheric transport model error remains challenging. In this paper, we employ a state-of-the-art ensemble technique combined with a state-of-the-art Bayesian inference algorithm to infer point sources. Our research helps to fill the gap in our understanding of model error in the context of inverse atmospheric transport modelling.
Qi Tang, Michael J. Prather, Juno Hsu, Daniel J. Ruiz, Philip J. Cameron-Smith, Shaocheng Xie, and Jean-Christophe Golaz
Geosci. Model Dev., 14, 1219–1236, https://doi.org/10.5194/gmd-14-1219-2021, https://doi.org/10.5194/gmd-14-1219-2021, 2021
Basit Khan, Sabine Banzhaf, Edward C. Chan, Renate Forkel, Farah Kanani-Sühring, Klaus Ketelsen, Mona Kurppa, Björn Maronga, Matthias Mauder, Siegfried Raasch, Emmanuele Russo, Martijn Schaap, and Matthias Sühring
Geosci. Model Dev., 14, 1171–1193, https://doi.org/10.5194/gmd-14-1171-2021, https://doi.org/10.5194/gmd-14-1171-2021, 2021
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An atmospheric chemistry model has been implemented in the microscale PALM model system 6.0. This article provides a detailed description of the model, its structure, input requirements, various features and limitations. Several pre-compiled ready-to-use chemical mechanisms are included in the chemistry model code; however, users can also easily implement other mechanisms. A case study is presented to demonstrate the application of the new chemistry model in the urban environment.
Mohsen Moradi, Benjamin Dyer, Amir Nazem, Manoj K. Nambiar, M. Rafsan Nahian, Bruno Bueno, Chris Mackey, Saeran Vasanthakumar, Negin Nazarian, E. Scott Krayenhoff, Leslie K. Norford, and Amir A. Aliabadi
Geosci. Model Dev., 14, 961–984, https://doi.org/10.5194/gmd-14-961-2021, https://doi.org/10.5194/gmd-14-961-2021, 2021
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The Vertical City Weather Generator (VCWG) is an urban microclimate model developed to predict temporal and vertical variation of potential temperature, wind speed, and specific humidity. VCWG is forced by climate variables at a nearby rural site and coupled to radiation and building energy models. VCWG is evaluated against field observations of the BUBBLE campaign. It is run under exploration mode to assess its performance given urban characteristics, seasonal variations, and climate zones.
Loredana G. Suciu, Robert J. Griffin, and Caroline A. Masiello
Geosci. Model Dev., 14, 907–921, https://doi.org/10.5194/gmd-14-907-2021, https://doi.org/10.5194/gmd-14-907-2021, 2021
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Understanding the atmospheric degradation of biomass burning tracers such as levoglucosan is essential to decreasing uncertainties in the role of biomass burning in air quality, carbon cycling and paleoclimate. Using a 0-D modeling approach and numerical chamber simulations, we found that the multiphase atmospheric degradation of levoglucosan occurs over timescales of hours to days, can form secondary organic aerosols and affects other key tropospheric gases, such as ozone.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, and Qi Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-441, https://doi.org/10.5194/gmd-2020-441, 2021
Revised manuscript accepted for GMD
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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.
Chihiro Kodama, Tomoki Ohno, Tatsuya Seiki, Hisashi Yashiro, Akira T. Noda, Masuo Nakano, Yohei Yamada, Woosub Roh, Masaki Satoh, Tomoko Nitta, Daisuke Goto, Hiroaki Miura, Tomoe Nasuno, Tomoki Miyakawa, Ying-Wen Chen, and Masato Sugi
Geosci. Model Dev., 14, 795–820, https://doi.org/10.5194/gmd-14-795-2021, https://doi.org/10.5194/gmd-14-795-2021, 2021
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This paper describes the latest stable version of NICAM, a global atmospheric model, developed for high-resolution climate simulations toward the IPCC Assessment Report. Our model explicitly treats convection, clouds, and precipitation and could reduce the uncertainty of climate change projection. A series of test simulations demonstrated improvements (e.g., high cloud) and issues (e.g., low cloud, precipitation pattern), suggesting further necessity for model improvement and higher resolutions.
Jingyu Wang, Jiwen Fan, Robert A. Houze Jr., Stella R. Brodzik, Kai Zhang, Guang J. Zhang, and Po-Lun Ma
Geosci. Model Dev., 14, 719–734, https://doi.org/10.5194/gmd-14-719-2021, https://doi.org/10.5194/gmd-14-719-2021, 2021
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This paper presents an evaluation of the E3SM model against NEXRAD radar observations for the warm seasons during 2014–2016. The COSP forward simulator package is implemented in the model to generate radar reflectivity, and the NEXRAD observations are coarsened to the model resolution for comparison. The model severely underestimates the reflectivity above 4 km. Sensitivity tests on the parameters from cumulus parameterization and cloud microphysics do not improve this model bias.
Lei Zhang, Sunling Gong, Tianliang Zhao, Chunhong Zhou, Yuesi Wang, Jiawei Li, Dongsheng Ji, Jianjun He, Hongli Liu, Ke Gui, Xiaomei Guo, Jinhui Gao, Yunpeng Shan, Hong Wang, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 14, 703–718, https://doi.org/10.5194/gmd-14-703-2021, https://doi.org/10.5194/gmd-14-703-2021, 2021
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Development of chemical transport models with advanced physics and chemical schemes is important for improving air-quality forecasts. This study develops the chemical module CUACE by updating with a new particle dry deposition scheme and adding heterogenous chemical reactions and couples it with the WRF model. The coupled model (WRF/CUACE) was able to capture well the variations of PM2.5, O3, NO2, and secondary inorganic aerosols in eastern China.
Simon Patrick O'Meara, Shuxuan Xu, David Topping, M. Rami Alfarra, Gerard Capes, Douglas Lowe, Yunqi Shao, and Gordon McFiggans
Geosci. Model Dev., 14, 675–702, https://doi.org/10.5194/gmd-14-675-2021, https://doi.org/10.5194/gmd-14-675-2021, 2021
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User-friendly and open-source software for simulating aerosol chambers is a valuable tool for research scientists in designing and analysing their experiments. This paper describes a new version of such software and will therefore provide a useful reference for those applying it. Central to the paper is an assessment of the software's accuracy through comparison against previously published simulations.
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. Discuss., https://doi.org/10.5194/gmd-2020-371, https://doi.org/10.5194/gmd-2020-371, 2021
Revised manuscript accepted for GMD
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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.
Tamara Emmerichs, Astrid Kerkweg, Huug Ouwersloot, Silvano Fares, Ivan Mammarella, and Domenico Taraborrelli
Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021, https://doi.org/10.5194/gmd-14-495-2021, 2021
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Dry deposition to vegetation is a major sink of ground-level ozone. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for global tropospheric ozone. We extended the current model parameterization with a relevant pathway and important meteorological adjustment factors. The comparison with measurements shows that this enables a more realistic model representation of ozone dry deposition velocity. Globally, annual dry deposition loss increases.
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. Discuss., https://doi.org/10.5194/gmd-2020-430, https://doi.org/10.5194/gmd-2020-430, 2021
Revised manuscript accepted for GMD
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The sub-grid particle formation (SGPF) in plume plays an important role in air pollution and climate effect. We coupled a SGPF scheme into a chemical transport model with 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.
Alexander Ukhov, Ravan Ahmadov, Georg Grell, and Georgiy Stenchikov
Geosci. Model Dev., 14, 473–493, https://doi.org/10.5194/gmd-14-473-2021, https://doi.org/10.5194/gmd-14-473-2021, 2021
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We discuss and evaluate the effects of inconsistencies found in the WRF-Chem code when using the GOCART module. First, PM surface concentrations were miscalculated. Second, dust optical depth was underestimated by 25 %–30 %. Third, an inconsistency in the process of gravitational settling led to the overestimation of dust column loadings by 4 %–6 %, PM10 by 2 %–4 %, and the rate of gravitational dust settling by 5 %–10 %. We also presented diagnostics that can be used to estimate these effects.
Andrew T. Prata, Leonardo Mingari, Arnau Folch, Giovanni Macedonio, and Antonio Costa
Geosci. Model Dev., 14, 409–436, https://doi.org/10.5194/gmd-14-409-2021, https://doi.org/10.5194/gmd-14-409-2021, 2021
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This paper presents FALL3D-8.0, the latest version release of an open-source code with a track record of 15+ years and a growing number of users in the volcanological and atmospheric communities. The code, originally conceived for atmospheric dispersal and deposition of tephra particles, has been extended to model other types of particles, aerosols and radionuclides. This paper details new model applications and validation of FALL3D-8.0 using satellite, ground-deposit load and radionuclide data.
Jian Zhong, Xiaoming Cai, and Zheng-Tong Xie
Geosci. Model Dev., 14, 323–336, https://doi.org/10.5194/gmd-14-323-2021, https://doi.org/10.5194/gmd-14-323-2021, 2021
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A synthetic inflow turbulence generator was implemented in the idealised Weather Research and Forecasting large eddy simulation. The inflow case yielded a mean velocity profile and second-moment profiles that agreed well with those generated using periodic boundary conditions, after a short adjustment distance. This implementation can be extended to a multi-scale seamless nesting simulation from a meso-scale domain with a kilometre-scale resolution to LES domains with metre-scale resolutions.
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