Articles | Volume 10, issue 12
https://doi.org/10.5194/gmd-10-4405-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-10-4405-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
05 Dec 2017
Model experiment description paper |
| 05 Dec 2017
| 05 Dec 2017
Compiled records of carbon isotopes in atmospheric CO2 for historical simulations in CMIP6
Heather Graven
CORRESPONDING AUTHOR
Department of Physics, Imperial College London, London, UK
Colin E. Allison
CSIRO Climate Science Centre, Oceans and Atmosphere, Aspendale, Australia
David M. Etheridge
CSIRO Climate Science Centre, Oceans and Atmosphere, Aspendale, Australia
Samuel Hammer
Institut für Umweltphysik, Heidelberg University, Heidelberg, Germany
Ralph F. Keeling
Scripps Institution of Oceanography, University of California, San Diego, USA
Ingeborg Levin
Institut für Umweltphysik, Heidelberg University, Heidelberg, Germany
Harro A. J. Meijer
Centre for Isotope Research, University of Groningen, Groningen, the Netherlands
Mauro Rubino
Dipartimento di Matematica e Fisica, Università della Campania “Luigi Vanvitelli”, Caserta, Italy
Pieter P. Tans
National Oceanic and Atmospheric Administration, Boulder, USA
Cathy M. Trudinger
CSIRO Climate Science Centre, Oceans and Atmosphere, Aspendale, Australia
Bruce H. Vaughn
Institute of Arctic and Alpine Research, University of Colorado, Boulder, USA
James W. C. White
Institute of Arctic and Alpine Research, University of Colorado, Boulder, USA
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Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
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Hannah Chawner, Karina E. Adcock, Tim Arnold, Yuri Artioli, Caroline Dylag, Grant L. Forster, Anita Ganesan, Heather Graven, Gennadi Lessin, Peter Levy, Ingrid T. Luijx, Alistair Manning, Penelope A. Pickers, Chris Rennick, Christian Rödenbeck, and Matthew Rigby
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Douglas E. J. Worthy, Michele K. Rauh, Lin Huang, Felix R. Vogel, Alina Chivulescu, Kenneth A. Masarie, Ray L. Langenfelds, Paul B. Krummel, Colin E. Allison, Andrew M. Crotwell, Monica Madronich, Gabrielle Pétron, Ingeborg Levin, Samuel Hammer, Sylvia Michel, Michel Ramonet, Martina Schmidt, Armin Jordan, Heiko Moossen, Michael Rothe, Ralph Keeling, and Eric J. Morgan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-99, https://doi.org/10.5194/amt-2023-99, 2023
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Benjamin Birner, Eric Morgan, and Ralph F. Keeling
Atmos. Meas. Tech., 16, 1551–1561, https://doi.org/10.5194/amt-16-1551-2023, https://doi.org/10.5194/amt-16-1551-2023, 2023
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Christo Buizert, Sarah Shackleton, Jeffrey P. Severinghaus, William H. G. Roberts, Alan Seltzer, Bernhard Bereiter, Kenji Kawamura, Daniel Baggenstos, Anaïs J. Orsi, Ikumi Oyabu, Benjamin Birner, Jacob D. Morgan, Edward J. Brook, David M. Etheridge, David Thornton, Nancy Bertler, Rebecca L. Pyne, Robert Mulvaney, Ellen Mosley-Thompson, Peter D. Neff, and Vasilii V. Petrenko
Clim. Past, 19, 579–606, https://doi.org/10.5194/cp-19-579-2023, https://doi.org/10.5194/cp-19-579-2023, 2023
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Mark O. Battle, Raine Raynor, Stephen Kesler, and Ralph Keeling
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-765, https://doi.org/10.5194/acp-2022-765, 2023
Preprint withdrawn
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Auke M. van der Woude, Remco de Kok, Naomi Smith, Ingrid T. Luijkx, Santiago Botía, Ute Karstens, Linda M. J. Kooijmans, Gerbrand Koren, Harro A. J. Meijer, Gert-Jan Steeneveld, Ida Storm, Ingrid Super, Hubertus A. Scheeren, Alex Vermeulen, and Wouter Peters
Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, https://doi.org/10.5194/essd-15-579-2023, 2023
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Kim A. P. Faassen, Linh N. T. Nguyen, Eadin R. Broekema, Bert A. M. Kers, Ivan Mammarella, Timo Vesala, Penelope A. Pickers, Andrew C. Manning, Jordi Vilà-Guerau de Arellano, Harro A. J. Meijer, Wouter Peters, and Ingrid T. Luijkx
Atmos. Chem. Phys., 23, 851–876, https://doi.org/10.5194/acp-23-851-2023, https://doi.org/10.5194/acp-23-851-2023, 2023
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Sourish Basu, Xin Lan, Edward Dlugokencky, Sylvia Michel, Stefan Schwietzke, John B. Miller, Lori Bruhwiler, Youmi Oh, Pieter P. Tans, Francesco Apadula, Luciana V. Gatti, Armin Jordan, Jaroslaw Necki, Motoki Sasakawa, Shinji Morimoto, Tatiana Di Iorio, Haeyoung Lee, Jgor Arduini, and Giovanni Manca
Atmos. Chem. Phys., 22, 15351–15377, https://doi.org/10.5194/acp-22-15351-2022, https://doi.org/10.5194/acp-22-15351-2022, 2022
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Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Luke M. Western, Alison L. Redington, Alistair J. Manning, Cathy M. Trudinger, Lei Hu, Stephan Henne, Xuekun Fang, Lambert J. M. Kuijpers, Christina Theodoridi, David S. Godwin, Jgor Arduini, Bronwyn Dunse, Andreas Engel, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Michela Maione, Jens Mühle, Simon O'Doherty, Hyeri Park, Sunyoung Park, Stefan Reimann, Peter K. Salameh, Daniel Say, Roland Schmidt, Tanja Schuck, Carolina Siso, Kieran M. Stanley, Isaac Vimont, Martin K. Vollmer, Dickon Young, Ronald G. Prinn, Ray F. Weiss, Stephen A. Montzka, and Matthew Rigby
Atmos. Chem. Phys., 22, 9601–9616, https://doi.org/10.5194/acp-22-9601-2022, https://doi.org/10.5194/acp-22-9601-2022, 2022
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The production of ozone-destroying gases is being phased out. Even though production of one of the main ozone-depleting gases, called HCFC-141b, has been declining for many years, the amount that is being released to the atmosphere has been increasing since 2017. We do not know for sure why this is. A possible explanation is that HCFC-141b that was used to make insulating foams many years ago is only now escaping to the atmosphere, or a large part of its production is not being reported.
Jacob D. Morgan, Christo Buizert, Tyler J. Fudge, Kenji Kawamura, Jeffrey P. Severinghaus, and Cathy M. Trudinger
The Cryosphere, 16, 2947–2966, https://doi.org/10.5194/tc-16-2947-2022, https://doi.org/10.5194/tc-16-2947-2022, 2022
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The composition of air bubbles in Antarctic ice cores records information about past changes in properties of the snowpack. We find that, near the South Pole, thinner snowpack in the past is often due to steeper surface topography, in which faster winds erode the snow and deposit it in flatter areas. The slope and wind seem to also cause a seasonal bias in the composition of air bubbles in the ice core. These findings will improve interpretation of other ice cores from places with steep slopes.
Fabian Maier, Christoph Gerbig, Ingeborg Levin, Ingrid Super, Julia Marshall, and Samuel Hammer
Geosci. Model Dev., 15, 5391–5406, https://doi.org/10.5194/gmd-15-5391-2022, https://doi.org/10.5194/gmd-15-5391-2022, 2022
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We show that the default representation of point source emissions in WRF–STILT leads to large overestimations when modelling fossil fuel CO2 concentrations for a 30 m high observation site during stable atmospheric conditions. We therefore introduce a novel point source modelling approach in WRF-STILT that takes into account their effective emission heights and results in a much better agreement with observations.
Joël Thanwerdas, Marielle Saunois, Antoine Berchet, Isabelle Pison, Bruce H. Vaughn, Sylvia Englund Michel, and Philippe Bousquet
Geosci. Model Dev., 15, 4831–4851, https://doi.org/10.5194/gmd-15-4831-2022, https://doi.org/10.5194/gmd-15-4831-2022, 2022
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Estimating CH4 sources by exploiting observations within an inverse modeling framework is a powerful approach. Here, a new system designed to assimilate δ13C(CH4) observations together with CH4 observations is presented. By optimizing both the emissions and associated source signatures of multiple emission categories, this new system can efficiently differentiate the co-located emission categories and provide estimates of CH4 sources that are consistent with isotopic data.
Christian Rödenbeck, Tim DeVries, Judith Hauck, Corinne Le Quéré, and Ralph F. Keeling
Biogeosciences, 19, 2627–2652, https://doi.org/10.5194/bg-19-2627-2022, https://doi.org/10.5194/bg-19-2627-2022, 2022
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The ocean is an important part of the global carbon cycle, taking up about a quarter of the anthropogenic CO2 emitted by burning of fossil fuels and thus slowing down climate change. However, the CO2 uptake by the ocean is, in turn, affected by variability and trends in climate. Here we use carbon measurements in the surface ocean to quantify the response of the oceanic CO2 exchange to environmental conditions and discuss possible mechanisms underlying this response.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 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.
Pieter Tans
Atmos. Meas. Tech., 15, 1903–1916, https://doi.org/10.5194/amt-15-1903-2022, https://doi.org/10.5194/amt-15-1903-2022, 2022
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The AirCore collects a continuous air sample in a long tube that can be read later when the captured air is slowly pushed through an analyzer. Much of the variation of gas composition encountered during collection is preserved, like having up to ~ 100 separate air samples. This is illustrated through examples of actual flights, and the analysis algorithm is described. The AirCore provides access to air as high as the mid stratosphere, enabling validation for satellite air composition soundings.
Eric Saboya, Giulia Zazzeri, Heather Graven, Alistair J. Manning, and Sylvia Englund Michel
Atmos. Chem. Phys., 22, 3595–3613, https://doi.org/10.5194/acp-22-3595-2022, https://doi.org/10.5194/acp-22-3595-2022, 2022
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Continuous measurements of atmospheric methane concentrations and its carbon-13 isotope have been made in central London since early 2018. These measurements were used to evaluate methane emissions reported in global and UK-specific emission inventories for the London area. Compared to atmospheric methane measurements from March 2018 to October 2020, both inventories are under-reporting natural gas leakage for the London area.
Linh N. T. Nguyen, Harro A. J. Meijer, Charlotte van Leeuwen, Bert A. M. Kers, Hubertus A. Scheeren, Anna E. Jones, Neil Brough, Thomas Barningham, Penelope A. Pickers, Andrew C. Manning, and Ingrid T. Luijkx
Earth Syst. Sci. Data, 14, 991–1014, https://doi.org/10.5194/essd-14-991-2022, https://doi.org/10.5194/essd-14-991-2022, 2022
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We present 20-year flask sample records of atmospheric CO2, O2, and APO from the stations Lutjewad (the Netherlands), Mace Head (Ireland), and Halley (Antarctica). Data from Lutjewad and Mace Head show similar long-term trends and seasonal cycles, agreeing with measurements from another station (Weybourne, UK). Measurements from Halley agree partly with those conducted by other institutes. From our 2002–2018 Lutjewad and Mace Head records, we find good agreement for global ocean carbon uptake.
Ingeborg Levin, Ute Karstens, Samuel Hammer, Julian DellaColetta, Fabian Maier, and Maksym Gachkivskyi
Atmos. Chem. Phys., 21, 17907–17926, https://doi.org/10.5194/acp-21-17907-2021, https://doi.org/10.5194/acp-21-17907-2021, 2021
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The radon tracer method is applied to atmospheric methane and radon observations from the upper Rhine valley to independently estimate methane emissions from the region. Comparison of our top-down results with bottom-up inventory data requires high-resolution footprint modelling and representative radon flux data. In agreement with inventories, observed emissions decreased, but only until 2005. A limitation of this method is that point-source emissions are not captured or not fully captured.
Vilma Kangasaho, Aki Tsuruta, Leif Backman, Pyry Mäkinen, Sander Houweling, Arjo Segers, Maarten Krol, Ed Dlugokencky, Sylvia Michel, James White, and Tuula Aalto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-843, https://doi.org/10.5194/acp-2021-843, 2021
Revised manuscript not accepted
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Understanding the composition of carbon isotopes can help to better understand the changes in methane budgets. This study investigates how methane sources affect the seasonal cycle of the methane carbon-13 isotope during 2000–2012 using an atmospheric transport model. We found that emissions from both anthropogenic and natural sources contribute. The findings raise a need to revise the magnitudes, proportion, and seasonal cycles of anthropogenic sources and northern wetland emissions.
Kevin S. Rozmiarek, Bruce H. Vaughn, Tyler R. Jones, Valerie Morris, William B. Skorski, Abigail G. Hughes, Jack Elston, Sonja Wahl, Anne-Katrine Faber, and Hans Christian Steen-Larsen
Atmos. Meas. Tech., 14, 7045–7067, https://doi.org/10.5194/amt-14-7045-2021, https://doi.org/10.5194/amt-14-7045-2021, 2021
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We have designed an unmanned aerial vehicle (UAV) sampling platform for operation in extreme polar environments that is capable of sampling atmospheric water vapor for subsequent measurement of water isotopes. During flight, we measure location, temperature, humidity, and pressure to determine the height of the planetary boundary layer (PBL) using algorithms, allowing for strategic decision-making by the pilot to collect samples in glass flasks contained in the nose cone of the UAV.
Abigail G. Hughes, Sonja Wahl, Tyler R. Jones, Alexandra Zuhr, Maria Hörhold, James W. C. White, and Hans Christian Steen-Larsen
The Cryosphere, 15, 4949–4974, https://doi.org/10.5194/tc-15-4949-2021, https://doi.org/10.5194/tc-15-4949-2021, 2021
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Water isotope records in Greenland and Antarctic ice cores are a valuable proxy for paleoclimate reconstruction and are traditionally thought to primarily reflect precipitation input. However,
post-depositional processes are hypothesized to contribute to the isotope climate signal. In this study we use laboratory experiments, field experiments, and modeling to show that sublimation and vapor–snow isotope exchange can rapidly influence the isotopic composition of the snowpack.
Nobuyuki Aoki, Shigeyuki Ishidoya, Yasunori Tohjima, Shinji Morimoto, Ralph F. Keeling, Adam Cox, Shuichiro Takebayashi, and Shohei Murayama
Atmos. Meas. Tech., 14, 6181–6193, https://doi.org/10.5194/amt-14-6181-2021, https://doi.org/10.5194/amt-14-6181-2021, 2021
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Observing the minimal long-term change in atmospheric O2 molar fraction combined with CO2 observation enables us to estimate terrestrial biospheric and oceanic CO2 uptakes separately. In this study, we firstly identified the span offset between the laboratory O2 scales using our developed high-precision standard mixtures, suggesting that the result may allow us to estimate terrestrial biospheric and oceanic CO2 uptakes precisely.
Pharahilda M. Steur, Hubertus A. Scheeren, Dave D. Nelson, J. Barry McManus, and Harro A. J. Meijer
Atmos. Meas. Tech., 14, 4279–4304, https://doi.org/10.5194/amt-14-4279-2021, https://doi.org/10.5194/amt-14-4279-2021, 2021
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For understanding the sources and sinks of atmospheric CO2, measurement of stable isotopes has proven to be highly valuable. We present a new method using laser absorption spectroscopy to simultaneously conduct measurements of three CO2 isotopes, directly on dry-air samples. This new method reduces sample preparation time significantly, compared to the conventional method in which measurements are conducted on pure CO2, and avoids measurement biases introduced by CO2 extraction.
Bradley D. Hall, Andrew M. Crotwell, Duane R. Kitzis, Thomas Mefford, Benjamin R. Miller, Michael F. Schibig, and Pieter P. Tans
Atmos. Meas. Tech., 14, 3015–3032, https://doi.org/10.5194/amt-14-3015-2021, https://doi.org/10.5194/amt-14-3015-2021, 2021
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We have recently revised the carbon dioxide calibration scale used by numerous laboratories that measure atmospheric CO2. The revision follows from an improved understanding of the manometric method used to determine the absolute amount of CO2 in an atmospheric air sample. The new scale is 0.18 μmol mol−1 (ppm) greater than the previous scale at 400 ppm CO2. While this difference is small in relative terms (0.045 %), it is significant in terms of atmospheric monitoring.
Britton B. Stephens, Eric J. Morgan, Jonathan D. Bent, Ralph F. Keeling, Andrew S. Watt, Stephen R. Shertz, and Bruce C. Daube
Atmos. Meas. Tech., 14, 2543–2574, https://doi.org/10.5194/amt-14-2543-2021, https://doi.org/10.5194/amt-14-2543-2021, 2021
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We describe methods used to make high-precision global-scale airborne measurements of atmospheric oxygen concentrations over a period of 20 years in order to study the global carbon cycle. Our techniques include an in situ vacuum ultraviolet absorption instrument and a pressure- and flow-controlled, cryogenically dried, glass flask sampler. We have deployed these instruments in 15 airborne research campaigns spanning from the Earth’s surface to the lower stratosphere and from pole to pole.
Benjamin Birner, William Paplawsky, Jeffrey Severinghaus, and Ralph F. Keeling
Atmos. Meas. Tech., 14, 2515–2527, https://doi.org/10.5194/amt-14-2515-2021, https://doi.org/10.5194/amt-14-2515-2021, 2021
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The atmospheric helium-to-nitrogen ratio is a promising indicator for circulation changes in the upper atmosphere and fossil fuel burning by humans. We present a very precise analysis method to determine changes in the helium-to-nitrogen ratio of air samples. The method relies on stabilizing the gas flow to a mass spectrometer and continuous removal of reactive gases. These advances enable new insights and monitoring possibilities for anthropogenic and natural processes.
Yuming Jin, Ralph F. Keeling, Eric J. Morgan, Eric Ray, Nicholas C. Parazoo, and Britton B. Stephens
Atmos. Chem. Phys., 21, 217–238, https://doi.org/10.5194/acp-21-217-2021, https://doi.org/10.5194/acp-21-217-2021, 2021
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We propose a new atmospheric coordinate (Mθe) based on equivalent potential temperature (θe) but with mass as the unit. This coordinate is useful in studying the spatial and temporal distribution of long-lived chemical tracers (CO2, CH4, O2 / N2, etc.) from sparse data, like airborne observation. Using this coordinate and sparse airborne observation (HIPPO and ATom), we resolve the Northern Hemisphere mass-weighted average CO2 seasonal cycle with high accuracy.
Ashok K. Luhar, David M. Etheridge, Zoë M. Loh, Julie Noonan, Darren Spencer, Lisa Smith, and Cindy Ong
Atmos. Chem. Phys., 20, 15487–15511, https://doi.org/10.5194/acp-20-15487-2020, https://doi.org/10.5194/acp-20-15487-2020, 2020
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With the sharp rise in coal seam gas (CSG) production in Queensland’s Surat Basin, there is much interest in quantifying methane emissions from this area and from unconventional gas production in general. We develop and apply a regional Bayesian inverse model that uses hourly methane concentration data from two sites and modelled backward dispersion to quantify emissions. The model requires a narrow prior and suggests that the emissions from the CSG areas are 33% larger than bottom-up estimates.
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.
Benjamin Birner, Martyn P. Chipperfield, Eric J. Morgan, Britton B. Stephens, Marianna Linz, Wuhu Feng, Chris Wilson, Jonathan D. Bent, Steven C. Wofsy, Jeffrey Severinghaus, and Ralph F. Keeling
Atmos. Chem. Phys., 20, 12391–12408, https://doi.org/10.5194/acp-20-12391-2020, https://doi.org/10.5194/acp-20-12391-2020, 2020
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With new high-precision observations from nine aircraft campaigns and 3-D chemical transport modeling, we show that the argon-to-nitrogen ratio (Ar / N2) in the lowermost stratosphere provides a useful constraint on the “age of air” (the time elapsed since entry of an air parcel into the stratosphere). Therefore, Ar / N2 in combination with traditional age-of-air indicators, such as CO2 and N2O, could provide new insights into atmospheric mixing and transport.
Ingeborg Levin, Ute Karstens, Markus Eritt, Fabian Maier, Sabrina Arnold, Daniel Rzesanke, Samuel Hammer, Michel Ramonet, Gabriela Vítková, Sebastien Conil, Michal Heliasz, Dagmar Kubistin, and Matthias Lindauer
Atmos. Chem. Phys., 20, 11161–11180, https://doi.org/10.5194/acp-20-11161-2020, https://doi.org/10.5194/acp-20-11161-2020, 2020
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Based on observations and Stochastic Time-Inverted Lagrangian Transport (STILT) footprint modelling, a sampling strategy has been developed for tall tower stations of the Integrated Carbon Observation System (ICOS) research infrastructure atmospheric station network. This strategy allows independent quality control of in situ measurements, provides representative coverage of the influence area of the sites, and is capable of automated targeted sampling of fossil fuel CO2 emission hotspots.
Abigail G. Hughes, Tyler R. Jones, Bo M. Vinther, Vasileios Gkinis, C. Max Stevens, Valerie Morris, Bruce H. Vaughn, Christian Holme, Bradley R. Markle, and James W. C. White
Clim. Past, 16, 1369–1386, https://doi.org/10.5194/cp-16-1369-2020, https://doi.org/10.5194/cp-16-1369-2020, 2020
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An ice core drilled on the Renland ice cap (RECAP) in east-central Greenland contains a continuous climate record dating through the last glacial period. Here we present the water isotope record for the Holocene, in which high-resolution climate information is retained for the last 8 kyr. We find that the RECAP water isotope record exhibits seasonal and decadal variability which may reflect sea surface conditions and regional climate variability.
Dipayan Paul, Hubertus A. Scheeren, Henk G. Jansen, Bert A. M. Kers, John B. Miller, Andrew M. Crotwell, Sylvia E. Michel, Luciana V. Gatti, Lucas G. Domingues, Caio S. C. Correia, Raiane A. L. Neves, Harro A. J. Meijer, and Wouter Peters
Atmos. Meas. Tech., 13, 4051–4064, https://doi.org/10.5194/amt-13-4051-2020, https://doi.org/10.5194/amt-13-4051-2020, 2020
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For reliable measurements of CO2 mole fractions and its stable isotope composition in air samples, one needs to carefully dry them during collection. Here we describe evaluation of a portable, consumable-free and power-free Nafion-based drying system that is currently being used for sample collection over the Amazon. Laboratory tests indicate that this Nafion-based system does not influence the mole fraction measurements of CH4, CO, N2O, SF6, and CO2 and the stable isotope composition of CO2.
Sarah A. Strode, James S. Wang, Michael Manyin, Bryan Duncan, Ryan Hossaini, Christoph A. Keller, Sylvia E. Michel, and James W. C. White
Atmos. Chem. Phys., 20, 8405–8419, https://doi.org/10.5194/acp-20-8405-2020, https://doi.org/10.5194/acp-20-8405-2020, 2020
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The 13C : 12C isotopic ratio in methane (CH4) provides information about CH4 sources, but loss of CH4 by reaction with OH and chlorine (Cl) also affects this ratio. Tropospheric Cl provides a small and uncertain sink for CH4 but has a large effect on its isotopic ratio. We use the GEOS model with several different Cl fields to test the sensitivity of methane's isotopic composition to tropospheric Cl. Cl affects the global mean, hemispheric gradient, and seasonal cycle of the isotopic ratio.
Kévin Fourteau, Laurent Arnaud, Xavier Faïn, Patricia Martinerie, David M. Etheridge, Vladimir Lipenkov, and Jean-Marc Barnola
Earth Syst. Sci. Data, 12, 1171–1177, https://doi.org/10.5194/essd-12-1171-2020, https://doi.org/10.5194/essd-12-1171-2020, 2020
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Measurements of the porosity of three polar firns were conducted in the 1990s by Jean-Marc Barnola using the method of gas pycnometry. From these data, a parametrization of firn pore closure was produced and used in different published articles. However, the data have not been published in their own right yet. We have made the data publicly accessible on the PANGAEA database and here propose describing how they were obtained and used to produce the pore closure parametrization.
Claudia Grossi, Scott D. Chambers, Olivier Llido, Felix R. Vogel, Victor Kazan, Alessandro Capuana, Sylvester Werczynski, Roger Curcoll, Marc Delmotte, Arturo Vargas, Josep-Anton Morguí, Ingeborg Levin, and Michel Ramonet
Atmos. Meas. Tech., 13, 2241–2255, https://doi.org/10.5194/amt-13-2241-2020, https://doi.org/10.5194/amt-13-2241-2020, 2020
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The sustainable support of radon metrology at the environmental level offers new scientific possibilities for the quantification of greenhouse gas (GHG) emissions and the determination of their source terms as well as for the identification of radioactive sources for the assessment of radiation exposure. This study helps to harmonize the techniques commonly used for atmospheric radon and radon progeny activity concentration measurements.
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.
Elizabeth Asher, Rebecca S. Hornbrook, Britton B. Stephens, Doug Kinnison, Eric J. Morgan, Ralph F. Keeling, Elliot L. Atlas, Sue M. Schauffler, Simone Tilmes, Eric A. Kort, Martin S. Hoecker-Martínez, Matt C. Long, Jean-François Lamarque, Alfonso Saiz-Lopez, Kathryn McKain, Colm Sweeney, Alan J. Hills, and Eric C. Apel
Atmos. Chem. Phys., 19, 14071–14090, https://doi.org/10.5194/acp-19-14071-2019, https://doi.org/10.5194/acp-19-14071-2019, 2019
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Halogenated organic trace gases, which are a source of reactive halogens to the atmosphere, exert a disproportionately large influence on atmospheric chemistry and climate. This paper reports novel aircraft observations of halogenated compounds over the Southern Ocean in summer and evaluates hypothesized regional sources and emissions of these trace gases through their relationships to additional aircraft observations.
Youngjoon Jang, Sang Bum Hong, Christo Buizert, Hun-Gyu Lee, Sang-Young Han, Ji-Woong Yang, Yoshinori Iizuka, Akira Hori, Yeongcheol Han, Seong Joon Jun, Pieter Tans, Taejin Choi, Seong-Joong Kim, Soon Do Hur, and Jinho Ahn
The Cryosphere, 13, 2407–2419, https://doi.org/10.5194/tc-13-2407-2019, https://doi.org/10.5194/tc-13-2407-2019, 2019
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We can learn how human activity altered atmospheric air from the interstitial air in the porous snow layer (firn) on top of glaciers. However, old firn air (> 55 years) was observed only at sites where surface temperatures and snow accumulation rates are very low, such as the South Pole. In this study, we report an unusually old firn air with CO2 age of 93 years from Styx Glacier, near the Ross Sea coast in Antarctica. We hypothesize that the large snow density variations increase firn air ages.
Haiyan Ni, Ru-Jin Huang, Junji Cao, Wenting Dai, Jiamao Zhou, Haoyue Deng, Anita Aerts-Bijma, Harro A. J. Meijer, and Ulrike Dusek
Atmos. Chem. Phys., 19, 10405–10422, https://doi.org/10.5194/acp-19-10405-2019, https://doi.org/10.5194/acp-19-10405-2019, 2019
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We apply radiocarbon source apportionment of more volatile organic carbon (mvOC) to winter aerosol samples from six Chinese cities. We find a consistently larger contribution of fossil sources to mvOC than to secondary or total organic carbon. Fossil mvOC concentrations are strongly correlated with primary fossil OC but not with secondary fossil OC. The variability in nonfossil mvOC seems to be related to both primary and secondary biomass burning sources.
Jens Mühle, Cathy M. Trudinger, Luke M. Western, Matthew Rigby, Martin K. Vollmer, Sunyoung Park, Alistair J. Manning, Daniel Say, Anita Ganesan, L. Paul Steele, Diane J. Ivy, Tim Arnold, Shanlan Li, Andreas Stohl, Christina M. Harth, Peter K. Salameh, Archie McCulloch, Simon O'Doherty, Mi-Kyung Park, Chun Ok Jo, Dickon Young, Kieran M. Stanley, Paul B. Krummel, Blagoj Mitrevski, Ove Hermansen, Chris Lunder, Nikolaos Evangeliou, Bo Yao, Jooil Kim, Benjamin Hmiel, Christo Buizert, Vasilii V. Petrenko, Jgor Arduini, Michela Maione, David M. Etheridge, Eleni Michalopoulou, Mike Czerniak, Jeffrey P. Severinghaus, Stefan Reimann, Peter G. Simmonds, Paul J. Fraser, Ronald G. Prinn, and Ray F. Weiss
Atmos. Chem. Phys., 19, 10335–10359, https://doi.org/10.5194/acp-19-10335-2019, https://doi.org/10.5194/acp-19-10335-2019, 2019
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We discuss atmospheric concentrations and emissions of the strong greenhouse gas perfluorocyclobutane. A large fraction of recent emissions stem from China, India, and Russia, probably as a by-product from the production of fluoropolymers and fluorochemicals. Most historic emissions likely stem from developed countries. Total emissions are higher than what is being reported. Clearly, more measurements and better reporting are needed to understand emissions of this and other greenhouse gases.
Isaac J. Vimont, Jocelyn C. Turnbull, Vasilii V. Petrenko, Philip F. Place, Colm Sweeney, Natasha Miles, Scott Richardson, Bruce H. Vaughn, and James W. C. White
Atmos. Chem. Phys., 19, 8547–8562, https://doi.org/10.5194/acp-19-8547-2019, https://doi.org/10.5194/acp-19-8547-2019, 2019
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Stable isotopes of Carbon Monoxide (CO) and radiocarbon carbon dioxide were measured over three summers at Indianapolis, Indiana, US, and for 1 year at a site thought to be strongly influenced by CO from oxidized volatile organic compounds (VOCs) in South Carolina, US. The Indianapolis results were used to provide an estimate of the carbon and oxygen isotopic signatures of CO produced from oxidized VOCs. This updated estimate agrees well with the data from South Carolina during the summer.
Christian Holme, Vasileios Gkinis, Mika Lanzky, Valerie Morris, Martin Olesen, Abigail Thayer, Bruce H. Vaughn, and Bo M. Vinther
Clim. Past, 15, 893–912, https://doi.org/10.5194/cp-15-893-2019, https://doi.org/10.5194/cp-15-893-2019, 2019
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This study investigates the linear relationship between the water isotopes of three East Greenland ice cores and regional temperatures. By comparing the water isotopes with nearby instrumental temperature records and reanalysis data, this study demonstrates that it can be problematic to reconstruct temperatures through regression of water isotope data from coastal ice cores. We further show that the varying linear relationship could be connected with changes in sea ice near the drill site.
Mauro Rubino, David M. Etheridge, David P. Thornton, Russell Howden, Colin E. Allison, Roger J. Francey, Ray L. Langenfelds, L. Paul Steele, Cathy M. Trudinger, Darren A. Spencer, Mark A. J. Curran, Tas D. van Ommen, and Andrew M. Smith
Earth Syst. Sci. Data, 11, 473–492, https://doi.org/10.5194/essd-11-473-2019, https://doi.org/10.5194/essd-11-473-2019, 2019
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The scientific community uses numerical models to predict future atmospheric levels of greenhouse gases causing global warming. This study presents the history of atmospheric concentration of the major greenhouse gases over the last 2000 years measured in ice core bubbles from the site of Law Dome (East Antarctica). The associated dataset is useful to test climate models and help provide accurate predictions of future climate change.
Martin K. Vollmer, François Bernard, Blagoj Mitrevski, L. Paul Steele, Cathy M. Trudinger, Stefan Reimann, Ray L. Langenfelds, Paul B. Krummel, Paul J. Fraser, David M. Etheridge, Mark A. J. Curran, and James B. Burkholder
Atmos. Chem. Phys., 19, 3481–3492, https://doi.org/10.5194/acp-19-3481-2019, https://doi.org/10.5194/acp-19-3481-2019, 2019
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We have discovered a new compound in the atmosphere, octafluorooxolane (c-C4F8O), from measurements in archived air samples. From our laboratory studies, we find that c-C4F8O is a very powerful greenhouse gas thereby contributing to global warming, and that it has a very long atmospheric lifetime of more than 3500 years. Based on our measurements we could reconstruct its atmospheric evolution over more than 4 decades. Based on this, we could estimate the global emissions of c-C4F8O.
Kieran Brophy, Heather Graven, Alistair J. Manning, Emily White, Tim Arnold, Marc L. Fischer, Seongeun Jeong, Xinguang Cui, and Matthew Rigby
Atmos. Chem. Phys., 19, 2991–3006, https://doi.org/10.5194/acp-19-2991-2019, https://doi.org/10.5194/acp-19-2991-2019, 2019
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We investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of California's fossil fuel CO2 emissions. Our results indicate that uncertainties in posterior total state fossil fuel CO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider.
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.
Haiyan Ni, Ru-Jin Huang, Junji Cao, Weiguo Liu, Ting Zhang, Meng Wang, Harro A. J. Meijer, and Ulrike Dusek
Atmos. Chem. Phys., 18, 16363–16383, https://doi.org/10.5194/acp-18-16363-2018, https://doi.org/10.5194/acp-18-16363-2018, 2018
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Seasonal changes in organic carbon (OC) and elemental carbon (EC) sources in Xi'an, China, are investigated based on measurements of radiocarbon and the stable isotope 13C. Relative contributions to EC from biomass burning, coal combustion, and vehicle emissions change substantially between different seasons. Biomass burning contributes 60 % to the EC increment in winter. Comparing concentrations and sources of primary OC to total OC suggests non-negligible OC loss due to active photochemistry.
Hinrich Schaefer, Dan Smale, Sylvia E. Nichol, Tony M. Bromley, Gordon W. Brailsford, Ross J. Martin, Rowena Moss, Sylvia Englund Michel, and James W. C. White
Biogeosciences, 15, 6371–6386, https://doi.org/10.5194/bg-15-6371-2018, https://doi.org/10.5194/bg-15-6371-2018, 2018
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To quantify the impact of El Nino–Southern Oscillation (ENSO) climate events on the methane budget, we studied the correlation between CH4 time series and ENSO indices. We find that ENSO explains less than one-third of the variability in CH4 levels and their stable carbon isotopes, which constrain the source processes of emissions. ENSO forcing of the CH4 cycle is too small, episodic, and regional to force atmospheric trends, which are more likely caused by agricultural or industrial emissions.
Michael F. Schibig, Duane Kitzis, and Pieter P. Tans
Atmos. Meas. Tech., 11, 5565–5586, https://doi.org/10.5194/amt-11-5565-2018, https://doi.org/10.5194/amt-11-5565-2018, 2018
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For long-term monitoring of CO2 in the atmosphere it is crucial that standard reference gas mixtures stored in high-pressure aluminum cylinders, used to calibrate global measurements, remain stable over their whole time of use. This study finds a reproducible small enrichment as a cylinder is emptied at a low-flow rate, as well as somewhat larger and variable effects when a cylinder is emptied using a high-flow rate.
Wei He, Ivar R. van der Velde, Arlyn E. Andrews, Colm Sweeney, John Miller, Pieter Tans, Ingrid T. van der Laan-Luijkx, Thomas Nehrkorn, Marikate Mountain, Weimin Ju, Wouter Peters, and Huilin Chen
Geosci. Model Dev., 11, 3515–3536, https://doi.org/10.5194/gmd-11-3515-2018, https://doi.org/10.5194/gmd-11-3515-2018, 2018
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We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system. This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions. The CTDAS-Lagrange system can be easily extended to assimilate an additional tracer, e.g., carbonyl sulfide (COS or OCS), for regional estimates of both net and gross carbon fluxes.
Vanessa Haverd, Benjamin Smith, Lars Nieradzik, Peter R. Briggs, William Woodgate, Cathy M. Trudinger, Josep G. Canadell, and Matthias Cuntz
Geosci. Model Dev., 11, 2995–3026, https://doi.org/10.5194/gmd-11-2995-2018, https://doi.org/10.5194/gmd-11-2995-2018, 2018
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CABLE is a terrestrial biosphere model that can be applied stand-alone and provides for land surface–atmosphere exchange within a climate model. We extend CABLE for regional and global carbon–climate simulations, accounting for land use and land cover change mediated by tree demography. A novel algorithm to simulate the coordination of rate-limiting photosynthetic processes is also implemented. Simulations satisfy multiple observational constraints on the global land carbon cycle.
Matthias Kuderer, Samuel Hammer, and Ingeborg Levin
Atmos. Chem. Phys., 18, 7951–7959, https://doi.org/10.5194/acp-18-7951-2018, https://doi.org/10.5194/acp-18-7951-2018, 2018
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Atmospheric 14CO2 measurements allow for estimating the regional fossil fuel CO2 component. However, results potentially need to be corrected for 14CO2 contamination from near-by nuclear facilities (NF). Our dispersion estimates of corresponding contaminations for Heidelberg, based on differently resolved wind fields, show differences of up to a factor of 2. Estimates from highly resolved models coupled with temporally resolved 14CO2 emissions from NFs are required for more accurate results.
Christian Rödenbeck, Sönke Zaehle, Ralph Keeling, and Martin Heimann
Biogeosciences, 15, 2481–2498, https://doi.org/10.5194/bg-15-2481-2018, https://doi.org/10.5194/bg-15-2481-2018, 2018
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In this paper we investigate how the CO2 exchange between the land vegetation and the atmosphere varies from year to year. We quantify the relation between variations in the CO2 exchange and variations in air temperature. For this quantification, we use long-term measurements of CO2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature. The results help us to understand the mechanisms of CO2 exchange.
Martin Kunz, Jost V. Lavric, Christoph Gerbig, Pieter Tans, Don Neff, Christine Hummelgård, Hans Martin, Henrik Rödjegård, Burkhard Wrenger, and Martin Heimann
Atmos. Meas. Tech., 11, 1833–1849, https://doi.org/10.5194/amt-11-1833-2018, https://doi.org/10.5194/amt-11-1833-2018, 2018
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Unmanned aircraft could provide a cost-effective way to close gaps in the observation of the carbon cycle, provided that small yet accurate analysers are available. We have developed a COmpact Carbon dioxide analyser for Airborne Platforms (COCAP). During validation of its CO2 measurements in simulated and real flights we found a measurement error of 1.2 μmol mol−1 or better with no indication of bias. COCAP is a self-contained package that has proven well suited for operation on board UASs.
Peter G. Simmonds, Matthew Rigby, Archie McCulloch, Martin K. Vollmer, Stephan Henne, Jens Mühle, Simon O'Doherty, Alistair J. Manning, Paul B. Krummel, Paul J. Fraser, Dickon Young, Ray F. Weiss, Peter K. Salameh, Christina M. Harth, Stefan Reimann, Cathy M. Trudinger, L. Paul Steele, Ray H. J. Wang, Diane J. Ivy, Ronald G. Prinn, Blagoj Mitrevski, and David M. Etheridge
Atmos. Chem. Phys., 18, 4153–4169, https://doi.org/10.5194/acp-18-4153-2018, https://doi.org/10.5194/acp-18-4153-2018, 2018
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Recent measurements of the potent greenhouse gas HFC-23, a by-product of HCFC-22 production, show a 28 % increase in the atmospheric mole fraction from 2009 to 2016. A minimum in the atmospheric abundance of HFC-23 in 2009 was attributed to abatement of HFC-23 emissions by incineration under the Clean Development Mechanism (CDM). Our results indicate that the recent increase in HFC-23 emissions is driven by failure of mitigation under the CDM to keep pace with increased HCFC-22 production.
David W. T. Griffith, Denis Pöhler, Stefan Schmitt, Samuel Hammer, Sanam N. Vardag, and Ulrich Platt
Atmos. Meas. Tech., 11, 1549–1563, https://doi.org/10.5194/amt-11-1549-2018, https://doi.org/10.5194/amt-11-1549-2018, 2018
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Measurements of atmospheric trace gases over an open path complement in situ measurements by spatial averaging. This paper describes the first open-path measurements of CO2, CH4 and other trace gases by near-infrared Fourier transform spectroscopy. The measurements were made in Heidelberg, Germany, for 4 months in 2014 over a 1.5 km path and compared to in situ measurements made at one end of the path. The experiment setup and methods (and the comparisons of open path to in situ) are described.
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.
Taku Umezawa, Carl A. M. Brenninkmeijer, Thomas Röckmann, Carina van der Veen, Stanley C. Tyler, Ryo Fujita, Shinji Morimoto, Shuji Aoki, Todd Sowers, Jochen Schmitt, Michael Bock, Jonas Beck, Hubertus Fischer, Sylvia E. Michel, Bruce H. Vaughn, John B. Miller, James W. C. White, Gordon Brailsford, Hinrich Schaefer, Peter Sperlich, Willi A. Brand, Michael Rothe, Thomas Blunier, David Lowry, Rebecca E. Fisher, Euan G. Nisbet, Andrew L. Rice, Peter Bergamaschi, Cordelia Veidt, and Ingeborg Levin
Atmos. Meas. Tech., 11, 1207–1231, https://doi.org/10.5194/amt-11-1207-2018, https://doi.org/10.5194/amt-11-1207-2018, 2018
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Isotope measurements are useful for separating different methane sources. However, the lack of widely accepted standards and calibration methods for stable carbon and hydrogen isotopic ratios of methane in air has caused significant measurement offsets among laboratories. We conducted worldwide interlaboratory comparisons, surveyed the literature and assessed them systematically. This study may be of help in future attempts to harmonize data sets of isotopic composition of atmospheric methane.
Peter Bergamaschi, Ute Karstens, Alistair J. Manning, Marielle Saunois, Aki Tsuruta, Antoine Berchet, Alexander T. Vermeulen, Tim Arnold, Greet Janssens-Maenhout, Samuel Hammer, Ingeborg Levin, Martina Schmidt, Michel Ramonet, Morgan Lopez, Jost Lavric, Tuula Aalto, Huilin Chen, Dietrich G. Feist, Christoph Gerbig, László Haszpra, Ove Hermansen, Giovanni Manca, John Moncrieff, Frank Meinhardt, Jaroslaw Necki, Michal Galkowski, Simon O'Doherty, Nina Paramonova, Hubertus A. Scheeren, Martin Steinbacher, and Ed Dlugokencky
Atmos. Chem. Phys., 18, 901–920, https://doi.org/10.5194/acp-18-901-2018, https://doi.org/10.5194/acp-18-901-2018, 2018
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European methane (CH4) emissions are estimated for 2006–2012 using atmospheric in situ measurements from 18 European monitoring stations and 7 different inverse models. Our analysis highlights the potential significant contribution of natural emissions from wetlands (including peatlands and wet soils) to the total European emissions. The top-down estimates of total EU-28 CH4 emissions are broadly consistent with the sum of reported anthropogenic CH4 emissions and the estimated natural emissions.
Martin K. Vollmer, Dickon Young, Cathy M. Trudinger, Jens Mühle, Stephan Henne, Matthew Rigby, Sunyoung Park, Shanlan Li, Myriam Guillevic, Blagoj Mitrevski, Christina M. Harth, Benjamin R. Miller, Stefan Reimann, Bo Yao, L. Paul Steele, Simon A. Wyss, Chris R. Lunder, Jgor Arduini, Archie McCulloch, Songhao Wu, Tae Siek Rhee, Ray H. J. Wang, Peter K. Salameh, Ove Hermansen, Matthias Hill, Ray L. Langenfelds, Diane Ivy, Simon O'Doherty, Paul B. Krummel, Michela Maione, David M. Etheridge, Lingxi Zhou, Paul J. Fraser, Ronald G. Prinn, Ray F. Weiss, and Peter G. Simmonds
Atmos. Chem. Phys., 18, 979–1002, https://doi.org/10.5194/acp-18-979-2018, https://doi.org/10.5194/acp-18-979-2018, 2018
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We measured the three chlorofluorocarbons (CFCs) CFC-13, CFC-114, and CFC-115 in the atmosphere because they are important in stratospheric ozone depletion. These compounds should have decreased in the atmosphere because they are banned by the Montreal Protocol but we find the opposite. Emissions over the last decade have not declined on a global scale. We use inverse modeling and our observations to find that a large part of the emissions originate in the Asian region.
Ivar R. van der Velde, John B. Miller, Michiel K. van der Molen, Pieter P. Tans, Bruce H. Vaughn, James W. C. White, Kevin Schaefer, and Wouter Peters
Geosci. Model Dev., 11, 283–304, https://doi.org/10.5194/gmd-11-283-2018, https://doi.org/10.5194/gmd-11-283-2018, 2018
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We explored an inverse modeling technique to interpret global atmospheric measurements of CO2 and the ratio of its stable carbon isotopes (δ13C). We detected the possible underestimation of drought stress in biosphere models after applying combined atmospheric CO2 and δ13C constraints. This study highlights the importance of improving the representation of the biosphere in carbon–climate models, in particular in a world where droughts become more extreme and more frequent.
Xin Lan, Pieter Tans, Colm Sweeney, Arlyn Andrews, Andrew Jacobson, Molly Crotwell, Edward Dlugokencky, Jonathan Kofler, Patricia Lang, Kirk Thoning, and Sonja Wolter
Atmos. Chem. Phys., 17, 15151–15165, https://doi.org/10.5194/acp-17-15151-2017, https://doi.org/10.5194/acp-17-15151-2017, 2017
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We analyze spatial patterns of column CO2 over North America using well-calibrated aircraft and tall tower measurements. We find that the long-term averaged spatial gradients of column CO2 across North America show a smooth pattern that mainly reflects the large-scale circulation. Our results can serve as a good reference for evaluating current and future column CO2 retrievals from both ground and satellite platforms.
Tesfaye A. Berhanu, Sönke Szidat, Dominik Brunner, Ece Satar, Rüdiger Schanda, Peter Nyfeler, Michael Battaglia, Martin Steinbacher, Samuel Hammer, and Markus Leuenberger
Atmos. Chem. Phys., 17, 10753–10766, https://doi.org/10.5194/acp-17-10753-2017, https://doi.org/10.5194/acp-17-10753-2017, 2017
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Fossil fuel CO2 is the major contributor of anthropogenic CO2 in the atmosphere, and accurate quantification is essential to better understand the carbon cycle. Such accurate quantification can be conducted based on radiocarbon measurements. In this study, we present radiocarbon measurements from a tall tower site in Switzerland. From these measurements, we have observed seasonally varying fossil fuel CO2 contributions and a biospheric CO2 component that varies diurnally and seasonally.
Jason Roberts, Andrew Moy, Christopher Plummer, Tas van Ommen, Mark Curran, Tessa Vance, Samuel Poynter, Yaping Liu, Joel Pedro, Adam Treverrow, Carly Tozer, Lenneke Jong, Pippa Whitehouse, Laetitia Loulergue, Jerome Chappellaz, Vin Morgan, Renato Spahni, Adrian Schilt, Cecilia MacFarling Meure, David Etheridge, and Thomas Stocker
Clim. Past Discuss., https://doi.org/10.5194/cp-2017-96, https://doi.org/10.5194/cp-2017-96, 2017
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Here we present a revised Law Dome, Dome Summit South (DSS) ice core age model (denoted LD2017) that significantly improves the chronology over the last 88 thousand years. An ensemble approach was used, allowing for the computation of both a median age and associated uncertainty as a function of depth. We use a non-linear interpolation between age ties and unlike previous studies, we made an independent estimate of the snow accumulation rate, where required, for the use of gas based age ties.
Pieter P. Tans, Andrew M. Crotwell, and Kirk W. Thoning
Atmos. Meas. Tech., 10, 2669–2685, https://doi.org/10.5194/amt-10-2669-2017, https://doi.org/10.5194/amt-10-2669-2017, 2017
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We describe a new CO2 calibration system for the Central Calibration Laboratory of the World Meteorological Organization Global Atmosphere Watch program. The system uses two laser spectroscopic instruments to measure the three major CO2 isotopologues individually. We account for isotopic differences between standards in the calibration hierarchy when assigning CO2 mole fraction, eliminating bias due to variations in the isotopic composition.
Kristal R. Verhulst, Anna Karion, Jooil Kim, Peter K. Salameh, Ralph F. Keeling, Sally Newman, John Miller, Christopher Sloop, Thomas Pongetti, Preeti Rao, Clare Wong, Francesca M. Hopkins, Vineet Yadav, Ray F. Weiss, Riley M. Duren, and Charles E. Miller
Atmos. Chem. Phys., 17, 8313–8341, https://doi.org/10.5194/acp-17-8313-2017, https://doi.org/10.5194/acp-17-8313-2017, 2017
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We present the first carbon dioxide (CO2) and methane (CH4) measurements from an extensive surface network as part of the Los Angeles Megacity Carbon Project. We describe methods that are essential for understanding carbon fluxes from complex urban environments. CO2 and CH4 levels are spatially and temporally variable, with urban sites showing significant enhancements relative to background. In 2015, the median afternoon enhancement near downtown Los Angeles was ~15 ppm CO2 and ~80 ppb CH4.
James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin, Keith Lindsay, Richard J. Matear, Galen A. McKinley, Anne Mouchet, Andreas Oschlies, Anastasia Romanou, Reiner Schlitzer, Alessandro Tagliabue, Toste Tanhua, and Andrew Yool
Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, https://doi.org/10.5194/gmd-10-2169-2017, 2017
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The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.
Malte Meinshausen, Elisabeth Vogel, Alexander Nauels, Katja Lorbacher, Nicolai Meinshausen, David M. Etheridge, Paul J. Fraser, Stephen A. Montzka, Peter J. Rayner, Cathy M. Trudinger, Paul B. Krummel, Urs Beyerle, Josep G. Canadell, John S. Daniel, Ian G. Enting, Rachel M. Law, Chris R. Lunder, Simon O'Doherty, Ron G. Prinn, Stefan Reimann, Mauro Rubino, Guus J. M. Velders, Martin K. Vollmer, Ray H. J. Wang, and Ray Weiss
Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, https://doi.org/10.5194/gmd-10-2057-2017, 2017
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Climate change is primarily driven by human-induced increases of greenhouse gas (GHG) concentrations. Based on ongoing community efforts (e.g. AGAGE and NOAA networks, ice cores), this study presents historical concentrations of CO2, CH4, N2O and 40 other GHGs from year 0 to year 2014. The data is recommended as input for climate models for pre-industrial, historical runs under CMIP6. Global means, but also latitudinal by monthly surface concentration fields are provided.
Markella Prokopiou, Patricia Martinerie, Célia J. Sapart, Emmanuel Witrant, Guillaume Monteil, Kentaro Ishijima, Sophie Bernard, Jan Kaiser, Ingeborg Levin, Thomas Blunier, David Etheridge, Ed Dlugokencky, Roderik S. W. van de Wal, and Thomas Röckmann
Atmos. Chem. Phys., 17, 4539–4564, https://doi.org/10.5194/acp-17-4539-2017, https://doi.org/10.5194/acp-17-4539-2017, 2017
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Nitrous oxide is the third most important anthropogenic greenhouse gas with an increasing mole fraction. To understand its natural and anthropogenic sources
we employ isotope measurements. Results show that while the N2O mole fraction increases, its heavy isotope content decreases. The isotopic changes observed underline the dominance of agricultural emissions especially at the early part of the record, whereas in the later decades the contribution from other anthropogenic sources increases.
Dominik Schmithüsen, Scott Chambers, Bernd Fischer, Stefan Gilge, Juha Hatakka, Victor Kazan, Rolf Neubert, Jussi Paatero, Michel Ramonet, Clemens Schlosser, Sabine Schmid, Alex Vermeulen, and Ingeborg Levin
Atmos. Meas. Tech., 10, 1299–1312, https://doi.org/10.5194/amt-10-1299-2017, https://doi.org/10.5194/amt-10-1299-2017, 2017
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A European-wide 222radon/222radon progeny comparison study has been conducted at nine measurement stations in order to determine differences between existing 222radon instrumentation and atmospheric data sets, respectively. Mean differences up to 45 % were found between monitors. These differences need to be taken into account if the data shall serve for quantitative regional atmospheric transport model validation.
Ingeborg Levin, Dominik Schmithüsen, and Alex Vermeulen
Atmos. Meas. Tech., 10, 1313–1321, https://doi.org/10.5194/amt-10-1313-2017, https://doi.org/10.5194/amt-10-1313-2017, 2017
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222Radon is often used to parameterise atmospheric transport in the lower troposphere. It can be measured via its decay products, which are bound to aerosol. Air sampling through long tubing, which sometimes cannot be avoided at tall tower sites, may then cause severe aerosol and corresponding radon daughter activity loss. We have quantified this loss for 8.2 mm ID Decabon tubing used at European stations and provide a length-dependent correction function for this experimental setting.
Ulrike Dusek, Regina Hitzenberger, Anne Kasper-Giebl, Magdalena Kistler, Harro A. J. Meijer, Sönke Szidat, Lukas Wacker, Rupert Holzinger, and Thomas Röckmann
Atmos. Chem. Phys., 17, 3233–3251, https://doi.org/10.5194/acp-17-3233-2017, https://doi.org/10.5194/acp-17-3233-2017, 2017
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Measurements of the radioactive carbon isotope 14C allow to identify the sources of aerosol carbon. We report an extensive 14C source apportionment record in the Netherlands with samples covering a whole year. We discovered that long-range transport has a large influence on aerosol carbon levels. Fossil fuel carbon is least influenced by long-range transport and more regional in origin. Biomass burning seems to be a minor source of aerosol carbon in the Netherlands.
Tyler R. Jones, James W. C. White, Eric J. Steig, Bruce H. Vaughn, Valerie Morris, Vasileios Gkinis, Bradley R. Markle, and Spruce W. Schoenemann
Atmos. Meas. Tech., 10, 617–632, https://doi.org/10.5194/amt-10-617-2017, https://doi.org/10.5194/amt-10-617-2017, 2017
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New measurement systems have been developed that continuously melt ice core samples, in contrast to other methods that analyze a single sample at a time. These newer systems are capable of reducing analysis time by many years and improving data set resolution. In this study, we introduce improved methodologies that optimize the speed, accuracy, and precision of a water isotope continuous-flow system. The presented system will be used for Antarctic and Greenland ice core projects.
Pearse J. Buchanan, Richard J. Matear, Andrew Lenton, Steven J. Phipps, Zanna Chase, and David M. Etheridge
Clim. Past, 12, 2271–2295, https://doi.org/10.5194/cp-12-2271-2016, https://doi.org/10.5194/cp-12-2271-2016, 2016
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We quantify the contributions of physical and biogeochemical changes in the ocean to enhancing ocean carbon storage at the Last Glacial Maximum. We find that simulated circulation and surface conditions cannot explain changes in carbon storage or other major biogeochemical fields that existed during the glacial climate. Key modifications to the functioning of the biological pump are therefore required to explain the glacial climate and improve model–proxy agreement for all fields.
Nicola J. Warwick, Michelle L. Cain, Rebecca Fisher, James L. France, David Lowry, Sylvia E. Michel, Euan G. Nisbet, Bruce H. Vaughn, James W. C. White, and John A. Pyle
Atmos. Chem. Phys., 16, 14891–14908, https://doi.org/10.5194/acp-16-14891-2016, https://doi.org/10.5194/acp-16-14891-2016, 2016
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Methane is an important greenhouse gas. Methane emissions from Arctic wetlands are poorly quantified and may increase in a warming climate. Using a global atmospheric model and atmospheric observations of methane and its isotopologues, we find that isotopologue data are useful in constraining Arctic wetland emissions. Our results suggest that the seasonal cycle of these emissions may be incorrectly simulated in land process models, with implications for our understanding of future emissions.
Cathy M. Trudinger, Vanessa Haverd, Peter R. Briggs, and Josep G. Canadell
Biogeosciences, 13, 6363–6383, https://doi.org/10.5194/bg-13-6363-2016, https://doi.org/10.5194/bg-13-6363-2016, 2016
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Semi-arid ecosystems in Australia are responsible for a significant part of the variability in global atmospheric carbon dioxide. Here we use Australian observations to estimate parameters in a land surface model of carbon and water cycles. We quantify the variability in Australian carbon fluxes between 1982 and 2013, including the large uptake in 2011 associated with exceptionally wet conditions following a prolonged drought. We estimate the effect of parameter uncertainty on these estimates.
Sander van der Laan, Swagath Manohar, Alex Vermeulen, Fred Bosveld, Harro Meijer, Andrew Manning, Michiel van der Molen, and Ingrid van der Laan-Luijkx
Atmos. Meas. Tech., 9, 5523–5533, https://doi.org/10.5194/amt-9-5523-2016, https://doi.org/10.5194/amt-9-5523-2016, 2016
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A new methodology is presented to estimate regional-scale surface fluxes of 222Rn. 222Rn is an increasingly important trace gas which is used to calculate regional-scale greenhouse gas emissions and to validate atmospheric transport models. We tested our method at two atmospheric research stations in the Netherlands and compared our results with measurements from accumulation chambers and two recently published 222Rn soil flux maps for Europe.
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.
Dipayan Paul, Huilin Chen, Henk A. Been, Rigel Kivi, and Harro A. J. Meijer
Atmos. Meas. Tech., 9, 4997–5006, https://doi.org/10.5194/amt-9-4997-2016, https://doi.org/10.5194/amt-9-4997-2016, 2016
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Here we describe the determination of C-14 concentration in stratospheric CO2 samples collected using the AirCore sampling method. Two stratospheric AirCore profiles, collected in Sodankylä, were used for this study. The stratospheric profile was divided into six sections. CO2 from each section was extracted and converted to graphite for the determination of C-14 using AMS. Through this study, we show that the AirCore is a viable and valuable sampling method for stratospheric C-14 measurements.
Cathy M. Trudinger, Paul J. Fraser, David M. Etheridge, William T. Sturges, Martin K. Vollmer, Matt Rigby, Patricia Martinerie, Jens Mühle, David R. Worton, Paul B. Krummel, L. Paul Steele, Benjamin R. Miller, Johannes Laube, Francis S. Mani, Peter J. Rayner, Christina M. Harth, Emmanuel Witrant, Thomas Blunier, Jakob Schwander, Simon O'Doherty, and Mark Battle
Atmos. Chem. Phys., 16, 11733–11754, https://doi.org/10.5194/acp-16-11733-2016, https://doi.org/10.5194/acp-16-11733-2016, 2016
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Perfluorocarbons (PFCs) are potent, long-lived and mostly man-made greenhouse gases released to the atmosphere mainly during aluminium production and semiconductor manufacture. Here we present the first continuous histories of three PFCs from 1800 to 2014, derived from measurements of these PFCs in the atmosphere and in air bubbles in polar ice. The records show how human actions have affected these important greenhouse gases over the past century.
Dorothee C. E. Bakker, Benjamin Pfeil, Camilla S. Landa, Nicolas Metzl, Kevin M. O'Brien, Are Olsen, Karl Smith, Cathy Cosca, Sumiko Harasawa, Stephen D. Jones, Shin-ichiro Nakaoka, Yukihiro Nojiri, Ute Schuster, Tobias Steinhoff, Colm Sweeney, Taro Takahashi, Bronte Tilbrook, Chisato Wada, Rik Wanninkhof, Simone R. Alin, Carlos F. Balestrini, Leticia Barbero, Nicholas R. Bates, Alejandro A. Bianchi, Frédéric Bonou, Jacqueline Boutin, Yann Bozec, Eugene F. Burger, Wei-Jun Cai, Robert D. Castle, Liqi Chen, Melissa Chierici, Kim Currie, Wiley Evans, Charles Featherstone, Richard A. Feely, Agneta Fransson, Catherine Goyet, Naomi Greenwood, Luke Gregor, Steven Hankin, Nick J. Hardman-Mountford, Jérôme Harlay, Judith Hauck, Mario Hoppema, Matthew P. Humphreys, Christopher W. Hunt, Betty Huss, J. Severino P. Ibánhez, Truls Johannessen, Ralph Keeling, Vassilis Kitidis, Arne Körtzinger, Alex Kozyr, Evangelia Krasakopoulou, Akira Kuwata, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Claire Lo Monaco, Ansley Manke, Jeremy T. Mathis, Liliane Merlivat, Frank J. Millero, Pedro M. S. Monteiro, David R. Munro, Akihiko Murata, Timothy Newberger, Abdirahman M. Omar, Tsuneo Ono, Kristina Paterson, David Pearce, Denis Pierrot, Lisa L. Robbins, Shu Saito, Joe Salisbury, Reiner Schlitzer, Bernd Schneider, Roland Schweitzer, Rainer Sieger, Ingunn Skjelvan, Kevin F. Sullivan, Stewart C. Sutherland, Adrienne J. Sutton, Kazuaki Tadokoro, Maciej Telszewski, Matthias Tuma, Steven M. A. C. van Heuven, Doug Vandemark, Brian Ward, Andrew J. Watson, and Suqing Xu
Earth Syst. Sci. Data, 8, 383–413, https://doi.org/10.5194/essd-8-383-2016, https://doi.org/10.5194/essd-8-383-2016, 2016
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Version 3 of the Surface Ocean CO2 Atlas (www.socat.info) has 14.5 million CO2 (carbon dioxide) values for the years 1957 to 2014 covering the global oceans and coastal seas. Version 3 is an update to version 2 with a longer record and 44 % more CO2 values. The CO2 measurements have been made on ships, fixed moorings and drifting buoys. SOCAT enables quantification of the ocean carbon sink and ocean acidification, as well as model evaluation, thus informing climate negotiations.
E. N. Koffi, P. Bergamaschi, U. Karstens, M. Krol, A. Segers, M. Schmidt, I. Levin, A. T. Vermeulen, R. E. Fisher, V. Kazan, H. Klein Baltink, D. Lowry, G. Manca, H. A. J. Meijer, J. Moncrieff, S. Pal, M. Ramonet, H. A. Scheeren, and A. G. Williams
Geosci. Model Dev., 9, 3137–3160, https://doi.org/10.5194/gmd-9-3137-2016, https://doi.org/10.5194/gmd-9-3137-2016, 2016
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We evaluate the capability of the TM5 model to reproduce observations of the boundary layer dynamics and the associated variability of trace gases close to the surface, using 222Rn. Focusing on the European scale, we compare the TM5 boundary layer heights with observations from radiosondes, lidar, and ceilometer. Furthermore, we compare TM5 simulations of 222Rn activity concentrations, using a novel, process-based 222Rn flux map over Europe, with 222Rn harmonized measurements from 10 stations.
Ana Bastos, Philippe Ciais, Jonathan Barichivich, Laurent Bopp, Victor Brovkin, Thomas Gasser, Shushi Peng, Julia Pongratz, Nicolas Viovy, and Cathy M. Trudinger
Biogeosciences, 13, 4877–4897, https://doi.org/10.5194/bg-13-4877-2016, https://doi.org/10.5194/bg-13-4877-2016, 2016
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The ice-core record shows a stabilisation of atmospheric CO2 in the 1940s, despite continued emissions from fossil fuel burning and land-use change (LUC). We use up-to-date reconstructions of the CO2 sources and sinks over the 20th century to evaluate whether these capture the CO2 plateau and to test the previously proposed hypothesis. Both strong terrestrial sink, possibly due to LUC not fully accounted for in the records, and enhanced oceanic uptake are necessary to explain this stall.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
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How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Theo Manuel Jenk, Mauro Rubino, David Etheridge, Viorela Gabriela Ciobanu, and Thomas Blunier
Atmos. Meas. Tech., 9, 3687–3706, https://doi.org/10.5194/amt-9-3687-2016, https://doi.org/10.5194/amt-9-3687-2016, 2016
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Atmospheric CO2 and δ13C-CO2 records from polar ice cores provide important constraints on the natural carbon cycle variability. Still, data exist only from a limited number of sampling sites and time periods due to demanding analytical challenges. Additional analytical state-of-the-art resources are desirable. This study describes such a new facility. Its analytical performance and new approaches for dealing with procedural blank contribution and analytical outliers are discussed in detail.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
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In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Sanam Noreen Vardag, Samuel Hammer, and Ingeborg Levin
Biogeosciences, 13, 4237–4251, https://doi.org/10.5194/bg-13-4237-2016, https://doi.org/10.5194/bg-13-4237-2016, 2016
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Using a synthetic dataset, we show how to best determine the mean source signature, δS, at high temporal resolution using continuous CO2 and δ13C(CO2) data. We apply this method to measured data from Heidelberg and find a distinct seasonal cycle of δS. Disentangling this record into its source components requires the isotopic end members of CO2 from the biosphere and those from the fuel mix. They can be estimated from the δS record, but only when their relative share is close to 100 %.
Lisa R. Welp, Prabir K. Patra, Christian Rödenbeck, Rama Nemani, Jian Bi, Stephen C. Piper, and Ralph F. Keeling
Atmos. Chem. Phys., 16, 9047–9066, https://doi.org/10.5194/acp-16-9047-2016, https://doi.org/10.5194/acp-16-9047-2016, 2016
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Boreal and arctic ecosystems have been responding to elevated temperatures and atmospheric CO2 over the last decades. It is not clear if these ecosystems are sequestering more carbon or possibly becoming sources. This is an important feedback of the carbon cycle to global warming. We studied monthly biological land CO2 fluxes inferred from atmospheric CO2 concentrations using inverse models and found that net summer CO2 uptake increased, resulting in a small increase in annual CO2 uptake.
Sally Newman, Xiaomei Xu, Kevin R. Gurney, Ying Kuang Hsu, King Fai Li, Xun Jiang, Ralph Keeling, Sha Feng, Darragh O'Keefe, Risa Patarasuk, Kam Weng Wong, Preeti Rao, Marc L. Fischer, and Yuk L. Yung
Atmos. Chem. Phys., 16, 3843–3863, https://doi.org/10.5194/acp-16-3843-2016, https://doi.org/10.5194/acp-16-3843-2016, 2016
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Combining 14C and 13C data from the Los Angeles, CA megacity with background data allows source attribution of CO2 emissions among biosphere, natural gas, and gasoline. The 8-year record of CO2 emissions from fossil fuel burning is consistent with "The Great Recession" of 2008–2010. The long-term trend and source attribution are consistent with government inventories. Seasonal patterns agree with the high-resolution Hestia-LA emission data product, when seasonal wind directions are considered.
V. Haverd, B. Smith, M. Raupach, P. Briggs, L. Nieradzik, J. Beringer, L. Hutley, C. M. Trudinger, and J. Cleverly
Biogeosciences, 13, 761–779, https://doi.org/10.5194/bg-13-761-2016, https://doi.org/10.5194/bg-13-761-2016, 2016
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We present a new approach for modelling coupled phenology and carbon allocation in savannas, and test it using data from the OzFlux network. Model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, in response to resource availability, and not from imposed hypotheses about the controls on tree-grass co-existence. Results indicate that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.
A. Laeng, J. Plieninger, T. von Clarmann, U. Grabowski, G. Stiller, E. Eckert, N. Glatthor, F. Haenel, S. Kellmann, M. Kiefer, A. Linden, S. Lossow, L. Deaver, A. Engel, M. Hervig, I. Levin, M. McHugh, S. Noël, G. Toon, and K. Walker
Atmos. Meas. Tech., 8, 5251–5261, https://doi.org/10.5194/amt-8-5251-2015, https://doi.org/10.5194/amt-8-5251-2015, 2015
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.
U. Karstens, C. Schwingshackl, D. Schmithüsen, and I. Levin
Atmos. Chem. Phys., 15, 12845–12865, https://doi.org/10.5194/acp-15-12845-2015, https://doi.org/10.5194/acp-15-12845-2015, 2015
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Detailed 222Rn flux maps are a prerequisite for the use of radon in atmospheric transport studies. We present a high-resolution 222Rn flux map for Europe, based on a parameterization of 222Rn production and transport in the soil. Spatial variations in 222Rn exhalation rates are determined by soil uranium content, water table depth and soil texture. Temporal variations are related to soil moisture variations as the diffusion in the soil depends on available air-filled pore space.
S. N. Vardag, C. Gerbig, G. Janssens-Maenhout, and I. Levin
Atmos. Chem. Phys., 15, 12705–12729, https://doi.org/10.5194/acp-15-12705-2015, https://doi.org/10.5194/acp-15-12705-2015, 2015
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In this model sensitivity study we compare and evaluate the surrogate tracers CO2, CO, δ13C-CO2 and Δ14C-CO2 for estimating continuous anthropogenic CO2. The results can be used to optimize the measurement network design with respect to the partitioning of total CO2 into biospheric and anthropogenic CO2 contributions. This enables improvement and validation of highly resolved emission inventories using atmospheric observation and regional modeling.
G. van der Wel, H. Fischer, H. Oerter, H. Meyer, and H. A. J. Meijer
The Cryosphere, 9, 1601–1616, https://doi.org/10.5194/tc-9-1601-2015, https://doi.org/10.5194/tc-9-1601-2015, 2015
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The diffusion of the stable water isotope signal during firnification of snow is a temperature-dependent process. Therefore, past local temperatures can be derived from the differential diffusion length. In this paper we develop a new method for determining this quantity and compare it with the existing method. Both methods are applied to a large number of synthetic data sets to assess the precision and accuracy of the reconstruction and to a section of the Antarctic EDML ice core record.
V. Masson-Delmotte, H. C. Steen-Larsen, P. Ortega, D. Swingedouw, T. Popp, B. M. Vinther, H. Oerter, A. E. Sveinbjornsdottir, H. Gudlaugsdottir, J. E. Box, S. Falourd, X. Fettweis, H. Gallée, E. Garnier, V. Gkinis, J. Jouzel, A. Landais, B. Minster, N. Paradis, A. Orsi, C. Risi, M. Werner, and J. W. C. White
The Cryosphere, 9, 1481–1504, https://doi.org/10.5194/tc-9-1481-2015, https://doi.org/10.5194/tc-9-1481-2015, 2015
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The deep NEEM ice core provides the oldest Greenland ice core record, enabling improved understanding of the response of ice core records to local climate. Here, we focus on shallow ice cores providing a stack record of accumulation and water-stable isotopes spanning the past centuries. For the first time, we document the ongoing warming in a Greenland ice core. By combining our data with other Greenland ice cores and model results, we characterise the spatio-temporal patterns of variability.
D. D. Lucas, C. Yver Kwok, P. Cameron-Smith, H. Graven, D. Bergmann, T. P. Guilderson, R. Weiss, and R. Keeling
Geosci. Instrum. Method. Data Syst., 4, 121–137, https://doi.org/10.5194/gi-4-121-2015, https://doi.org/10.5194/gi-4-121-2015, 2015
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Multiobjective optimization is used to design Pareto optimal greenhouse gas (GHG) observing networks. A prototype GHG network is designed to optimize scientific performance and measurement costs. The Pareto frontier is convex, showing the trade-offs between performance and cost and the diminishing returns in trading one for the other. Other objectives and constraints that are important in the design of practical GHG monitoring networks can be incorporated into our method.
L. G. van der Wel, H. A. Been, R. S. W. van de Wal, C. J. P. P. Smeets, and H. A. J. Meijer
The Cryosphere, 9, 1089–1103, https://doi.org/10.5194/tc-9-1089-2015, https://doi.org/10.5194/tc-9-1089-2015, 2015
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We performed 2H isotope diffusion measurements in the upper 3 metres of firn at Summit, Greenland, by following over a 4-year period isotope-enriched snow that we deposited.
We found that the diffusion process was much less rapid than in the most commonly used model. We discuss several aspects of the diffusion process that are still poorly constrained and might lead to this discrepancy. Quantitative knowledge of diffusion is necessary for use of the diffusion process itself as a climate proxy.
A. S. Lansø, J. Bendtsen, J. H. Christensen, L. L. Sørensen, H. Chen, H. A. J. Meijer, and C. Geels
Biogeosciences, 12, 2753–2772, https://doi.org/10.5194/bg-12-2753-2015, https://doi.org/10.5194/bg-12-2753-2015, 2015
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The air-sea CO2 exchange is investigated in the coastal region of the Baltic Sea and Danish inner waters. The impact of short-term variability in atmospheric CO2 on the air-sea CO2 exchange is examined, and it is found that ignoring short-term variability in the atmospheric CO2 creates a significant bias in the CO2 exchange. Atmospheric short-term variability is not always included in studies of the air-sea CO2 exchange, but based on the present study, we recommend it to be so in the future.
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.
A. P. Ballantyne, R. Andres, R. Houghton, B. D. Stocker, R. Wanninkhof, W. Anderegg, L. A. Cooper, M. DeGrandpre, P. P. Tans, J. B. Miller, C. Alden, and J. W. C. White
Biogeosciences, 12, 2565–2584, https://doi.org/10.5194/bg-12-2565-2015, https://doi.org/10.5194/bg-12-2565-2015, 2015
R. J. Matear, A. Lenton, D. Etheridge, and S. J. Phipps
Clim. Past Discuss., https://doi.org/10.5194/cpd-11-1093-2015, https://doi.org/10.5194/cpd-11-1093-2015, 2015
Revised manuscript has not been submitted
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Global climate models provide an important tool for simulating the earth's climate. Here we present a simulation of the climate of the Last Glacial Maximum, which was obtained by setting atmospheric greenhouse gas concentrations and the earth's orbital parameters to the 21 000 years before present values. We simulate an ocean behaviour that agrees with paleoclimate reconstructions supporting our ability to model the climate system and use the model to explore the impacts on the carbon cycle.
A. Ghosh, P. K. Patra, K. Ishijima, T. Umezawa, A. Ito, D. M. Etheridge, S. Sugawara, K. Kawamura, J. B. Miller, E. J. Dlugokencky, P. B. Krummel, P. J. Fraser, L. P. Steele, R. L. Langenfelds, C. M. Trudinger, J. W. C. White, B. Vaughn, T. Saeki, S. Aoki, and T. Nakazawa
Atmos. Chem. Phys., 15, 2595–2612, https://doi.org/10.5194/acp-15-2595-2015, https://doi.org/10.5194/acp-15-2595-2015, 2015
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Atmospheric CH4 increased from 900ppb to 1800ppb during the period 1900–2010 at a rate unprecedented in any observational records. We use bottom-up emissions and a chemistry-transport model to simulate CH4. The optimized global total CH4 emission, estimated from the model–observation differences, increased at fastest rate during 1940–1990. Using δ13C of CH4 measurements we attribute this emission increase to biomass burning. Total CH4 lifetime is shortened by 4% over the simulation period.
P. J. Rayner, A. Stavert, M. Scholze, A. Ahlström, C. E. Allison, and R. M. Law
Biogeosciences, 12, 835–844, https://doi.org/10.5194/bg-12-835-2015, https://doi.org/10.5194/bg-12-835-2015, 2015
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Recent papers suggest a slow-down in the natural uptake of
anthropogenic CO2. We analyse recent trends in atmospheric concentration and
known inputs to test for such a slow-down. We see, rather, an increase
in uptake compared to a simple response to changing CO2 concentration. Using atmospheric models and statistical techniques we isolate this increased uptake to the northern temperate and boreal continents during summer, suggesting a stronger growing season.
S. N. Vardag, S. Hammer, M. Sabasch, D. W. T. Griffith, and I. Levin
Atmos. Meas. Tech., 8, 579–592, https://doi.org/10.5194/amt-8-579-2015, https://doi.org/10.5194/amt-8-579-2015, 2015
C. Elsässer, D. Wagenbach, I. Levin, A. Stanzick, M. Christl, A. Wallner, S. Kipfstuhl, I. K. Seierstad, H. Wershofen, and J. Dibb
Clim. Past, 11, 115–133, https://doi.org/10.5194/cp-11-115-2015, https://doi.org/10.5194/cp-11-115-2015, 2015
R. Locatelli, P. Bousquet, F. Hourdin, M. Saunois, A. Cozic, F. Couvreux, J.-Y. Grandpeix, M.-P. Lefebvre, C. Rio, P. Bergamaschi, S. D. Chambers, U. Karstens, V. Kazan, S. van der Laan, H. A. J. Meijer, J. Moncrieff, M. Ramonet, H. A. Scheeren, C. Schlosser, M. Schmidt, A. Vermeulen, and A. G. Williams
Geosci. Model Dev., 8, 129–150, https://doi.org/10.5194/gmd-8-129-2015, https://doi.org/10.5194/gmd-8-129-2015, 2015
C. D. Nevison, M. Manizza, R. F. Keeling, M. Kahru, L. Bopp, J. Dunne, J. Tiputra, T. Ilyina, and B. G. Mitchell
Biogeosciences, 12, 193–208, https://doi.org/10.5194/bg-12-193-2015, https://doi.org/10.5194/bg-12-193-2015, 2015
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The observed seasonal cycles in atmospheric potential oxygen (APO) at five surface monitoring sites are compared to those inferred from the air-sea O2 fluxes of six ocean biogeochemistry models. The simulated air-sea fluxes are translated into APO seasonal cycles using a matrix method that takes into account atmospheric transport model (ATM) uncertainty among 13 different ATMs. Net primary production (NPP), estimated from satellite ocean color data, is also compared to model output.
C. Rödenbeck, D. C. E. Bakker, N. Metzl, A. Olsen, C. Sabine, N. Cassar, F. Reum, R. F. Keeling, and M. Heimann
Biogeosciences, 11, 4599–4613, https://doi.org/10.5194/bg-11-4599-2014, https://doi.org/10.5194/bg-11-4599-2014, 2014
S. N. Vardag, S. Hammer, S. O'Doherty, T. G. Spain, B. Wastine, A. Jordan, and I. Levin
Atmos. Chem. Phys., 14, 8403–8418, https://doi.org/10.5194/acp-14-8403-2014, https://doi.org/10.5194/acp-14-8403-2014, 2014
H. C. Steen-Larsen, A. E. Sveinbjörnsdottir, A. J. Peters, V. Masson-Delmotte, M. P. Guishard, G. Hsiao, J. Jouzel, D. Noone, J. K. Warren, and J. W. C. White
Atmos. Chem. Phys., 14, 7741–7756, https://doi.org/10.5194/acp-14-7741-2014, https://doi.org/10.5194/acp-14-7741-2014, 2014
K. B. Rodgers, O. Aumont, S. E. Mikaloff Fletcher, Y. Plancherel, L. Bopp, C. de Boyer Montégut, D. Iudicone, R. F. Keeling, G. Madec, and R. Wanninkhof
Biogeosciences, 11, 4077–4098, https://doi.org/10.5194/bg-11-4077-2014, https://doi.org/10.5194/bg-11-4077-2014, 2014
D. Bozhinova, M. K. van der Molen, I. R. van der Velde, M. C. Krol, S. van der Laan, H. A. J. Meijer, and W. Peters
Atmos. Chem. Phys., 14, 7273–7290, https://doi.org/10.5194/acp-14-7273-2014, https://doi.org/10.5194/acp-14-7273-2014, 2014
U. Dusek, M. Monaco, M. Prokopiou, F. Gongriep, R. Hitzenberger, H. A. J. Meijer, and T. Röckmann
Atmos. Meas. Tech., 7, 1943–1955, https://doi.org/10.5194/amt-7-1943-2014, https://doi.org/10.5194/amt-7-1943-2014, 2014
M. R. Raupach, M. Gloor, J. L. Sarmiento, J. G. Canadell, T. L. Frölicher, T. Gasser, R. A. Houghton, C. Le Quéré, and C. M. Trudinger
Biogeosciences, 11, 3453–3475, https://doi.org/10.5194/bg-11-3453-2014, https://doi.org/10.5194/bg-11-3453-2014, 2014
T. R. Jones, J. W. C. White, and T. Popp
Clim. Past, 10, 1253–1267, https://doi.org/10.5194/cp-10-1253-2014, https://doi.org/10.5194/cp-10-1253-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
R. Weller, I. Levin, D. Schmithüsen, M. Nachbar, J. Asseng, and D. Wagenbach
Atmos. Chem. Phys., 14, 3843–3853, https://doi.org/10.5194/acp-14-3843-2014, https://doi.org/10.5194/acp-14-3843-2014, 2014
D. Helmig, V. Petrenko, P. Martinerie, E. Witrant, T. Röckmann, A. Zuiderweg, R. Holzinger, J. Hueber, C. Thompson, J. W. C. White, W. Sturges, A. Baker, T. Blunier, D. Etheridge, M. Rubino, and P. Tans
Atmos. Chem. Phys., 14, 1463–1483, https://doi.org/10.5194/acp-14-1463-2014, https://doi.org/10.5194/acp-14-1463-2014, 2014
B. D. Hall, A. Engel, J. Mühle, J. W. Elkins, F. Artuso, E. Atlas, M. Aydin, D. Blake, E.-G. Brunke, S. Chiavarini, P. J. Fraser, J. Happell, P. B. Krummel, I. Levin, M. Loewenstein, M. Maione, S. A. Montzka, S. O'Doherty, S. Reimann, G. Rhoderick, E. S. Saltzman, H. E. Scheel, L. P. Steele, M. K. Vollmer, R. F. Weiss, D. Worthy, and Y. Yokouchi
Atmos. Meas. Tech., 7, 469–490, https://doi.org/10.5194/amt-7-469-2014, https://doi.org/10.5194/amt-7-469-2014, 2014
V. V. Petrenko, P. Martinerie, P. Novelli, D. M. Etheridge, I. Levin, Z. Wang, T. Blunier, J. Chappellaz, J. Kaiser, P. Lang, L. P. Steele, S. Hammer, J. Mak, R. L. Langenfelds, J. Schwander, J. P. Severinghaus, E. Witrant, G. Petron, M. O. Battle, G. Forster, W. T. Sturges, J.-F. Lamarque, K. Steffen, and J. W. C. White
Atmos. Chem. Phys., 13, 7567–7585, https://doi.org/10.5194/acp-13-7567-2013, https://doi.org/10.5194/acp-13-7567-2013, 2013
I. T. van der Laan-Luijkx, S. van der Laan, C. Uglietti, M. F. Schibig, R. E. M. Neubert, H. A. J. Meijer, W. A. Brand, A. Jordan, J. M. Richter, M. Rothe, and M. C. Leuenberger
Atmos. Meas. Tech., 6, 1805–1815, https://doi.org/10.5194/amt-6-1805-2013, https://doi.org/10.5194/amt-6-1805-2013, 2013
L. R. Welp, R. F. Keeling, R. F. Weiss, W. Paplawsky, and S. Heckman
Atmos. Meas. Tech., 6, 1217–1226, https://doi.org/10.5194/amt-6-1217-2013, https://doi.org/10.5194/amt-6-1217-2013, 2013
S. Hammer, G. Konrad, A. T. Vermeulen, O. Laurent, M. Delmotte, A. Jordan, L. Hazan, S. Conil, and I. Levin
Atmos. Meas. Tech., 6, 1201–1216, https://doi.org/10.5194/amt-6-1201-2013, https://doi.org/10.5194/amt-6-1201-2013, 2013
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
C. Rödenbeck, R. F. Keeling, D. C. E. Bakker, N. Metzl, A. Olsen, C. Sabine, and M. Heimann
Ocean Sci., 9, 193–216, https://doi.org/10.5194/os-9-193-2013, https://doi.org/10.5194/os-9-193-2013, 2013
C. E. Yver, H. D. Graven, D. D. Lucas, P. J. Cameron-Smith, R. F. Keeling, and R. F. Weiss
Atmos. Chem. Phys., 13, 1837–1852, https://doi.org/10.5194/acp-13-1837-2013, https://doi.org/10.5194/acp-13-1837-2013, 2013
C. M. Trudinger, I. G. Enting, P. J. Rayner, D. M. Etheridge, C. Buizert, M. Rubino, P. B. Krummel, and T. Blunier
Atmos. Chem. Phys., 13, 1485–1510, https://doi.org/10.5194/acp-13-1485-2013, https://doi.org/10.5194/acp-13-1485-2013, 2013
Related subject area
Climate and Earth system modeling
A sub-grid parameterization scheme for topographic vertical motion in CAM5-SE
Technology to aid the analysis of large-volume multi-institute climate model output at a central analysis facility (PRIMAVERA Data Management Tool V2.10)
A diffusion-based kernel density estimator (diffKDE, version 1) with optimal bandwidth approximation for the analysis of data in geoscience and ecological research
Monte Carlo drift correction – quantifying the drift uncertainty of global climate models
Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1
Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0
Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method
Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands
URock 2023a: an open-source GIS-based wind model for complex urban settings
DASH: a MATLAB toolbox for paleoclimate data assimilation
Comparing the Performance of Julia on CPUs versus GPUs and Julia-MPI versus Fortran-MPI: a case study with MPAS-Ocean (Version 7.1)
All aboard! Earth system investigations with the CH2O-CHOO TRAIN v1.0
The Canadian Atmospheric Model version 5 (CanAM5.0.3)
The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis
Assimilation of the AMSU-A radiances using the CESM (v2.1.0) and the DART (v9.11.13)–RTTOV (v12.3)
Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability
Simulated stable water isotopes during the mid-Holocene and pre-industrial periods using AWI-ESM-2.1-wiso
Truly Conserving with Conservative Remapping Methods
Rainbows and climate change: a tutorial on climate model diagnostics and parameterization
ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009)
MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region
Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications
IceTFT v1.0.0: interpretable long-term prediction of Arctic sea ice extent with deep learning
Earth system modeling on Modular Supercomputing Architectures: coupled atmosphere-ocean simulations with ICON 2.6.6-rc
The KNMI Large Ensemble Time Slice (KNMI–LENTIS)
ENSO statistics, teleconnections, and atmosphere–ocean coupling in the Taiwan Earth System Model version 1
Using probabilistic machine learning to better model temporal patterns in parameterizations: a case study with the Lorenz 96 model
The Regional Aerosol Model Intercomparison Project (RAMIP)
DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise
TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change
Recalibration of a three-dimensional water quality model with a newly developed autocalibration toolkit (EFDC-ACT v1.0.0): how much improvement will be achieved with a wider hydrological variability?
Description and evaluation of the JULES-ES set-up for ISIMIP2b
Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses
Understanding Changes in Cloud Simulations from E3SM Version 1 to Version 2
Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM
Modeling river water temperature with limiting forcing data: Air2stream v1.0.0, machine learning and multiple regression
WRF (v4.0)-SUEWS (v2018c) Coupled System: Development, Evaluation and Application
A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)
Resolving the mesoscale at reduced computational cost with FESOM 2.5: efficient modeling approaches applied to the Southern Ocean
Modeling and evaluating the effects of irrigation on land-atmosphere interaction in South-West Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization
The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results
The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies
A new simplified parameterization of secondary organic aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)
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Deep Learning Model based on Multi-scale Feature Fusion for Precipitation Nowcasting
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The Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
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In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Jon Seddon, Ag Stephens, Matthew S. Mizielinski, Pier Luigi Vidale, and Malcolm J. Roberts
Geosci. Model Dev., 16, 6689–6700, https://doi.org/10.5194/gmd-16-6689-2023, https://doi.org/10.5194/gmd-16-6689-2023, 2023
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The PRIMAVERA project aimed to develop a new generation of advanced global climate models. The large volume of data generated was uploaded to a central analysis facility (CAF) and was analysed by 100 PRIMAVERA scientists there. We describe how the PRIMAVERA project used the CAF's facilities to enable users to analyse this large dataset. We believe that similar, multi-institute, big-data projects could also use a CAF to efficiently share, organise and analyse large volumes of data.
Maria-Theresia Pelz, Markus Schartau, Christopher J. Somes, Vanessa Lampe, and Thomas Slawig
Geosci. Model Dev., 16, 6609–6634, https://doi.org/10.5194/gmd-16-6609-2023, https://doi.org/10.5194/gmd-16-6609-2023, 2023
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Kernel density estimators (KDE) approximate the probability density of a data set without the assumption of an underlying distribution. We used the solution of the diffusion equation, and a new approximation of the optimal smoothing parameter build on two pilot estimation steps, to construct such a KDE best suited for typical characteristics of geoscientific data. The resulting KDE is insensitive to noise and well resolves multimodal data structures as well as boundary-close data.
Benjamin S. Grandey, Zhi Yang Koh, Dhrubajyoti Samanta, Benjamin P. Horton, Justin Dauwels, and Lock Yue Chew
Geosci. Model Dev., 16, 6593–6608, https://doi.org/10.5194/gmd-16-6593-2023, https://doi.org/10.5194/gmd-16-6593-2023, 2023
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Global climate models are susceptible to spurious trends known as drift. Fortunately, drift can be corrected when analysing data produced by models. To explore the uncertainty associated with drift correction, we develop a new method: Monte Carlo drift correction. For historical simulations of thermosteric sea level rise, drift uncertainty is relatively large. When analysing data susceptible to drift, researchers should consider drift uncertainty.
Michael Sigmond, James Anstey, Vivek Arora, Ruth Digby, Nathan Gillett, Viatcheslav Kharin, William Merryfield, Catherine Reader, John Scinocca, Neil Swart, John Virgin, Carsten Abraham, Jason Cole, Nicolas Lambert, Woo-Sung Lee, Yongxiao Liang, Elizaveta Malinina, Landon Rieger, Knut von Salzen, Christian Seiler, Clint Seinen, Andrew Shao, Reinel Sospedra-Alfonso, Libo Wang, and Duo Yang
Geosci. Model Dev., 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023, https://doi.org/10.5194/gmd-16-6553-2023, 2023
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We present a new activity which aims to organize the analysis of biases in the Canadian Earth System model (CanESM) in a systematic manner. Results of this “Analysis for Development” (A4D) activity includes a new CanESM version, CanESM5.1, which features substantial improvements regarding the simulation of dust and stratospheric temperatures, a second CanESM5.1 variant with reduced climate sensitivity, and insights into potential avenues to reduce various other model biases.
Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, and Po-Lun Ma
Geosci. Model Dev., 16, 6355–6376, https://doi.org/10.5194/gmd-16-6355-2023, https://doi.org/10.5194/gmd-16-6355-2023, 2023
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To assess the ability of Earth system model (ESM) predictions, we developed a tool called ESMAC Diags to understand how aerosols, clouds, and aerosol–cloud interactions are represented in ESMs. This paper describes its version 2 functionality. We compared the model predictions with measurements taken by planes, ships, satellites, and ground instruments over four regions across the world. Results show that this new tool can help identify model problems and guide future development of ESMs.
Xinzhu Yu, Li Liu, Chao Sun, Qingu Jiang, Biao Zhao, Zhiyuan Zhang, Hao Yu, and Bin Wang
Geosci. Model Dev., 16, 6285–6308, https://doi.org/10.5194/gmd-16-6285-2023, https://doi.org/10.5194/gmd-16-6285-2023, 2023
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In this paper we propose a new common, flexible, and efficient parallel I/O framework for earth system modeling based on C-Coupler2.0. CIOFC1.0 can handle data I/O in parallel and provides a configuration file format that enables users to conveniently change the I/O configurations. It can automatically make grid and time interpolation, output data with an aperiodic time series, and accelerate data I/O when the field size is large.
Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima
Geosci. Model Dev., 16, 6211–6245, https://doi.org/10.5194/gmd-16-6211-2023, https://doi.org/10.5194/gmd-16-6211-2023, 2023
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A particle-based cloud model was developed for meter- to submeter-scale resolution in cloud simulations. Our new cloud model's computational performance is superior to a bin method and comparable to a two-moment bulk method. A highlight of this study is the 2 m resolution shallow cloud simulations over an area covering ∼10 km2. This model allows for studying turbulence and cloud physics at spatial scales that overlap with those covered by direct numerical simulations and field studies.
Anthony Schrapffer, Jan Polcher, Anna Sörensson, and Lluís Fita
Geosci. Model Dev., 16, 5755–5782, https://doi.org/10.5194/gmd-16-5755-2023, https://doi.org/10.5194/gmd-16-5755-2023, 2023
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The present paper introduces a floodplain scheme for a high-resolution land surface model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land–atmosphere fluxes and highlights the potential impact of floodplains on land–atmosphere interactions and the importance of integrating this module in coupled simulations.
Jérémy Bernard, Fredrik Lindberg, and Sandro Oswald
Geosci. Model Dev., 16, 5703–5727, https://doi.org/10.5194/gmd-16-5703-2023, https://doi.org/10.5194/gmd-16-5703-2023, 2023
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The UMEP plug-in integrated in the free QGIS software can now calculate the spatial variation of the wind speed within urban settings. This paper shows that the new wind model, URock, generally fits observations well and highlights the main needed improvements. According to this work, pedestrian wind fields and outdoor thermal comfort can now simply be estimated by any QGIS user (researchers, students, and practitioners).
Jonathan King, Jessica Tierney, Matthew Osman, Emily J. Judd, and Kevin J. Anchukaitis
Geosci. Model Dev., 16, 5653–5683, https://doi.org/10.5194/gmd-16-5653-2023, https://doi.org/10.5194/gmd-16-5653-2023, 2023
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Paleoclimate data assimilation is a useful method that allows researchers to combine climate models with natural archives of past climates. However, it can be difficult to implement in practice. To facilitate this method, we present DASH, a MATLAB toolbox. The toolbox provides routines that implement common steps of paleoclimate data assimilation, and it can be used to implement assimilations for a wide variety of time periods, spatial regions, data networks, and analytical algorithms.
Siddhartha Bishnu, Robert R. Strauss, and Mark R. Petersen
Geosci. Model Dev., 16, 5539–5559, https://doi.org/10.5194/gmd-16-5539-2023, https://doi.org/10.5194/gmd-16-5539-2023, 2023
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Here we test Julia, a relatively new programming language, which is designed to be simple to write, but also fast on advanced computer architectures. We found that Julia is both convenient and fast, but there is no free lunch. Our first attempt to develop an ocean model in Julia was relatively easy, but the code was slow. After several months of further development, we created a Julia code that is as fast on supercomputers as a Fortran ocean model.
Tyler Kukla, Daniel E. Ibarra, Kimberly V. Lau, and Jeremy K. C. Rugenstein
Geosci. Model Dev., 16, 5515–5538, https://doi.org/10.5194/gmd-16-5515-2023, https://doi.org/10.5194/gmd-16-5515-2023, 2023
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The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact across millions of years on a standard PC. While efficient, the model accounts for many factors including the location of land masses, the spatial pattern of the water cycle, and fundamental climate feedbacks. The model is a powerful tool for investigating how short-term climate processes can affect long-term changes in the Earth system.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
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The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Florian Zabel and Benjamin Poschlod
Geosci. Model Dev., 16, 5383–5399, https://doi.org/10.5194/gmd-16-5383-2023, https://doi.org/10.5194/gmd-16-5383-2023, 2023
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Today, most climate model data are provided at daily time steps. However, more and more models from different sectors, such as energy, water, agriculture, and health, require climate information at a sub-daily temporal resolution for a more robust and reliable climate impact assessment. Here we describe and validate the Teddy tool, a new model for the temporal disaggregation of daily climate model data for climate impact analysis.
Young-Chan Noh, Yonghan Choi, Hyo-Jong Song, Kevin Raeder, Joo-Hong Kim, and Youngchae Kwon
Geosci. Model Dev., 16, 5365–5382, https://doi.org/10.5194/gmd-16-5365-2023, https://doi.org/10.5194/gmd-16-5365-2023, 2023
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This is the first attempt to assimilate the observations of microwave temperature sounders into the global climate forecast model in which the satellite observations have not been assimilated in the past. To do this, preprocessing schemes are developed to make the satellite observations suitable to be assimilated. In the assimilation experiments, the model analysis is significantly improved by assimilating the observations of microwave temperature sounders.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
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Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
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We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Karl E. Taylor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-177, https://doi.org/10.5194/gmd-2023-177, 2023
Revised manuscript accepted for GMD
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Andrew Gettelman
Geosci. Model Dev., 16, 4937–4956, https://doi.org/10.5194/gmd-16-4937-2023, https://doi.org/10.5194/gmd-16-4937-2023, 2023
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A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
Geosci. Model Dev., 16, 4853–4866, https://doi.org/10.5194/gmd-16-4853-2023, https://doi.org/10.5194/gmd-16-4853-2023, 2023
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ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
Geosci. Model Dev., 16, 4811–4833, https://doi.org/10.5194/gmd-16-4811-2023, https://doi.org/10.5194/gmd-16-4811-2023, 2023
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Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Anna L. Merrifield, Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti
Geosci. Model Dev., 16, 4715–4747, https://doi.org/10.5194/gmd-16-4715-2023, https://doi.org/10.5194/gmd-16-4715-2023, 2023
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Using all Coupled Model Intercomparison Project (CMIP) models is unfeasible for many applications. We provide a subselection protocol that balances user needs for model independence, performance, and spread capturing CMIP’s projection uncertainty simultaneously. We show how sets of three to five models selected for European applications map to user priorities. An audit of model independence and its influence on equilibrium climate sensitivity uncertainty in CMIP is also presented.
Bin Mu, Xiaodan Luo, Shijin Yuan, and Xi Liang
Geosci. Model Dev., 16, 4677–4697, https://doi.org/10.5194/gmd-16-4677-2023, https://doi.org/10.5194/gmd-16-4677-2023, 2023
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To improve the long-term forecast skill for sea ice extent (SIE), we introduce IceTFT, which directly predicts 12 months of averaged Arctic SIE. The results show that IceTFT has higher forecasting skill. We conducted a sensitivity analysis of the variables in the IceTFT model. These sensitivities can help researchers study the mechanisms of sea ice development, and they also provide useful references for the selection of variables in data assimilation or the input of deep learning models.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
EGUsphere, https://doi.org/10.5194/egusphere-2023-1476, https://doi.org/10.5194/egusphere-2023-1476, 2023
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere-ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 59 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023, https://doi.org/10.5194/gmd-16-4581-2023, 2023
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The KNMI Large Ensemble Time Slice (KNMI–LENTIS) is a large ensemble of global climate model simulations with EC-Earth3. It covers two climate scenarios by focusing on two time slices: the present day (2000–2009) and a future +2 K climate (2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub-)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.
Yi-Chi Wang, Wan-Ling Tseng, Yu-Luen Chen, Shih-Yu Lee, Huang-Hsiung Hsu, and Hsin-Chien Liang
Geosci. Model Dev., 16, 4599–4616, https://doi.org/10.5194/gmd-16-4599-2023, https://doi.org/10.5194/gmd-16-4599-2023, 2023
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This study focuses on evaluating the performance of the Taiwan Earth System Model version 1 (TaiESM1) in simulating the El Niño–Southern Oscillation (ENSO), a significant tropical climate pattern with global impacts. Our findings reveal that TaiESM1 effectively captures several characteristics of ENSO, such as its seasonal variation and remote teleconnections. Its pronounced ENSO strength bias is also thoroughly investigated, aiming to gain insights to improve climate model performance.
Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, and Damon J. Wischik
Geosci. Model Dev., 16, 4501–4519, https://doi.org/10.5194/gmd-16-4501-2023, https://doi.org/10.5194/gmd-16-4501-2023, 2023
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How can we create better climate models? We tackle this by proposing a data-driven successor to the existing approach for capturing key temporal trends in climate models. We combine probability, allowing us to represent uncertainty, with machine learning, a technique to learn relationships from data which are undiscoverable to humans. Our model is often superior to existing baselines when tested in a simple atmospheric simulation.
Laura J. Wilcox, Robert J. Allen, Bjørn H. Samset, Massimo A. Bollasina, Paul T. Griffiths, James Keeble, Marianne T. Lund, Risto Makkonen, Joonas Merikanto, Declan O'Donnell, David J. Paynter, Geeta G. Persad, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Sabine Undorf, and Daniel M. Westervelt
Geosci. Model Dev., 16, 4451–4479, https://doi.org/10.5194/gmd-16-4451-2023, https://doi.org/10.5194/gmd-16-4451-2023, 2023
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Changes in anthropogenic aerosol emissions have strongly contributed to global and regional climate change. However, the size of these regional impacts and the way they arise are still uncertain. With large changes in aerosol emissions a possibility over the next few decades, it is important to better quantify the potential role of aerosol in future regional climate change. The Regional Aerosol Model Intercomparison Project will deliver experiments designed to facilitate this.
Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang
Geosci. Model Dev., 16, 4331–4366, https://doi.org/10.5194/gmd-16-4331-2023, https://doi.org/10.5194/gmd-16-4331-2023, 2023
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This work presents a novel open-source modeling platform for evaluating future sea level rise (SLR) impacts. Using nearly 10 000 discrete coastline segments around the world, we estimate 21st-century costs for 230 SLR and socioeconomic scenarios. We find that annual end-of-century costs range from USD 100 billion under a 2 °C warming scenario with proactive adaptation to 7 trillion under a 4 °C warming scenario with minimal adaptation, illustrating the cost-effectiveness of coastal adaptation.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
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Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Chen Zhang and Tianyu Fu
Geosci. Model Dev., 16, 4315–4329, https://doi.org/10.5194/gmd-16-4315-2023, https://doi.org/10.5194/gmd-16-4315-2023, 2023
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A new automatic calibration toolkit was developed and implemented into the recalibration of a 3-D water quality model, with observations in a wider range of hydrological variability. Compared to the model calibrated with the original strategy, the recalibrated model performed significantly better in modeled total phosphorus, chlorophyll a, and dissolved oxygen. Our work indicates that hydrological variability in the calibration periods has a non-negligible impact on the water quality models.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines
Geosci. Model Dev., 16, 4233–4247, https://doi.org/10.5194/gmd-16-4233-2023, https://doi.org/10.5194/gmd-16-4233-2023, 2023
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Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1263, https://doi.org/10.5194/egusphere-2023-1263, 2023
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We performed systematic evaluation of clouds simulated in the E3SMv2 to document model performance on clouds and understand what updates in E3SMv2 have caused the changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved primarily due to the re-tuning of cloud macrophysics parameters. This study offers additional insights about clouds simulated in E3SMv2 and will benefit the future E3SM developments.
Makcim L. De Sisto, Andrew H. MacDougall, Nadine Mengis, and Sophia Antoniello
Geosci. Model Dev., 16, 4113–4136, https://doi.org/10.5194/gmd-16-4113-2023, https://doi.org/10.5194/gmd-16-4113-2023, 2023
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In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
Manuel C. Almeida and Pedro S. Coelho
Geosci. Model Dev., 16, 4083–4112, https://doi.org/10.5194/gmd-16-4083-2023, https://doi.org/10.5194/gmd-16-4083-2023, 2023
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Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different models are used to predict the WT of 83 rivers. Generally, the results show that the models' hyperparameter optimization is essential and that to minimize the prediction error it is relevant to apply all the models considered in this study. Results also show that there is a logarithmic correlation among the error of the predicted river WT and the watershed time of concentration.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-117, https://doi.org/10.5194/gmd-2023-117, 2023
Revised manuscript accepted for GMD
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
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Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
EGUsphere, https://doi.org/10.5194/egusphere-2023-1496, https://doi.org/10.5194/egusphere-2023-1496, 2023
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Ocean models struggle to simulate small-scale ocean flows due to the computational cost of high-resolution simulations. Several cost-reducing strategies are applied to simulations of the Southern Ocean and evaluated with respect to observations and traditional, lower-resolution modelling methods. The high-resolution simulations effectively reproduce small-scale flows seen in satellite data and are largely consistent with traditional model simulations regarding their response to climate change.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
EGUsphere, https://doi.org/10.5194/egusphere-2023-890, https://doi.org/10.5194/egusphere-2023-890, 2023
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Irrigation modifies the land surface and soil conditions. The caused effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which is simulating the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
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The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev., 16, 3893–3906, https://doi.org/10.5194/gmd-16-3893-2023, https://doi.org/10.5194/gmd-16-3893-2023, 2023
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A new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM) based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Leroy J. Bird, Matthew G. W. Walker, Greg E. Bodeker, Isaac H. Campbell, Guangzhong Liu, Swapna Josmi Sam, Jared Lewis, and Suzanne M. Rosier
Geosci. Model Dev., 16, 3785–3808, https://doi.org/10.5194/gmd-16-3785-2023, https://doi.org/10.5194/gmd-16-3785-2023, 2023
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Deriving the statistics of expected future changes in extreme precipitation is challenging due to these events being rare. Regional climate models (RCMs) are computationally prohibitive for generating ensembles capable of capturing large numbers of extreme precipitation events with statistical robustness. Stochastic precipitation generators (SPGs) provide an alternative to RCMs. We describe a novel single-site SPG that learns the statistics of precipitation using a machine-learning approach.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825, https://doi.org/10.5194/gmd-16-3809-2023, https://doi.org/10.5194/gmd-16-3809-2023, 2023
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Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-109, https://doi.org/10.5194/gmd-2023-109, 2023
Revised manuscript accepted for GMD
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1. This study present a deep learning architecture MFF to improve the forecast skills of precipitations especially for heavy precipitations. 2. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. 3. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors, so that heavy precipitations are produced.
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Feijia Yin, Federica Castino, Volker Grewe, and Sabine Baumann
Geosci. Model Dev., 16, 3723–3748, https://doi.org/10.5194/gmd-16-3723-2023, https://doi.org/10.5194/gmd-16-3723-2023, 2023
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This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio Bento, and Angelina Bushenkova
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-136, https://doi.org/10.5194/gmd-2023-136, 2023
Revised manuscript accepted for GMD
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data, and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
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Short summary
Modelling of carbon isotopes 13C and 14C in land and ocean components of Earth system models provides opportunities for new insights and improved understanding of global carbon cycling, and for model evaluation. We compiled existing historical datasets to define the annual mean carbon isotopic composition of atmospheric CO2 for 1850–2015 that can be used in CMIP6 and other modelling activities.
Modelling of carbon isotopes 13C and 14C in land and ocean components of Earth system models...
