Articles | Volume 9, issue 2
https://doi.org/10.5194/gmd-9-749-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-749-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation
Dmitry A. Belikov
CORRESPONDING AUTHOR
National Institute for Environmental Studies, Tsukuba,
Japan
National Institute of Polar Research, Tokyo,
Japan
Tomsk State University, Tomsk, Russia
Shamil Maksyutov
National Institute for Environmental Studies, Tsukuba,
Japan
Alexey Yaremchuk
N. Andreev Acoustic Institute, Moscow,
Russia
Alexander Ganshin
Tomsk State University, Tomsk, Russia
Central Aerological Observatory, Dolgoprudny,
Russia
Thomas Kaminski
The Inversion Lab, Hamburg, Germany
previously at: FastOpt GmbH, Hamburg, Germany
Simon Blessing
FastOpt GmbH, Hamburg, Germany
Motoki Sasakawa
National Institute for Environmental Studies, Tsukuba,
Japan
Angel J. Gomez-Pelaez
Izaña Atmospheric Research Center (IARC),
Meteorological State Agency of Spain (AEMET), Izaña, 38311,
Spain
Alexander Starchenko
Tomsk State University, Tomsk, Russia
Related authors
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-516, https://doi.org/10.5194/essd-2023-516, 2024
Preprint under review for ESSD
Short summary
Short summary
This study provides an overview of data availability from observation and inventory-based CH4 emissions estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more Parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Alessandro Damiani, Hitoshi Irie, Dmitry A. Belikov, Shuei Kaizuka, Hossain Mohammed Syedul Hoque, and Raul R. Cordero
Atmos. Chem. Phys., 22, 12705–12726, https://doi.org/10.5194/acp-22-12705-2022, https://doi.org/10.5194/acp-22-12705-2022, 2022
Short summary
Short summary
We analyzed the variabilities in tropospheric gases and aerosols within the Greater Tokyo Area, Japan. Beyond highlighting air quality changes caused by the pandemic during the lockdown, we found that the degree of weekly cycling of most gases and aerosols was enhanced during the whole of 2020. The changes were unprecedented in recent years and potentially related to coincident reduced mobility in Japan, which, in contrast to other countries, was anomalously low on weekends in 2020.
Shamil Maksyutov, Tomohiro Oda, Makoto Saito, Rajesh Janardanan, Dmitry Belikov, Johannes W. Kaiser, Ruslan Zhuravlev, Alexander Ganshin, Vinu K. Valsala, Arlyn Andrews, Lukasz Chmura, Edward Dlugokencky, László Haszpra, Ray L. Langenfelds, Toshinobu Machida, Takakiyo Nakazawa, Michel Ramonet, Colm Sweeney, and Douglas Worthy
Atmos. Chem. Phys., 21, 1245–1266, https://doi.org/10.5194/acp-21-1245-2021, https://doi.org/10.5194/acp-21-1245-2021, 2021
Short summary
Short summary
In order to improve the top-down estimation of the anthropogenic greenhouse gas emissions, a high-resolution inverse modelling technique was developed for applications to global transport modelling of carbon dioxide and other greenhouse gases. A coupled Eulerian–Lagrangian transport model and its adjoint are combined with surface fluxes at 0.1° resolution to provide high-resolution forward simulation and inverse modelling of surface fluxes accounting for signals from emission hot spots.
Dmitry A. Belikov, Naoko Saitoh, Prabir K. Patra, and Naveen Chandra
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-101, https://doi.org/10.5194/amt-2020-101, 2020
Preprint withdrawn
Dmitry Belikov, Satoshi Sugawara, Shigeyuki Ishidoya, Fumio Hasebe, Shamil Maksyutov, Shuji Aoki, Shinji Morimoto, and Takakiyo Nakazawa
Atmos. Chem. Phys., 19, 5349–5361, https://doi.org/10.5194/acp-19-5349-2019, https://doi.org/10.5194/acp-19-5349-2019, 2019
Maarten Krol, Marco de Bruine, Lars Killaars, Huug Ouwersloot, Andrea Pozzer, Yi Yin, Frederic Chevallier, Philippe Bousquet, Prabir Patra, Dmitry Belikov, Shamil Maksyutov, Sandip Dhomse, Wuhu Feng, and Martyn P. Chipperfield
Geosci. Model Dev., 11, 3109–3130, https://doi.org/10.5194/gmd-11-3109-2018, https://doi.org/10.5194/gmd-11-3109-2018, 2018
Short summary
Short summary
The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced. Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis.
Dmitry A. Belikov, Shamil Maksyutov, Alexander Ganshin, Ruslan Zhuravlev, Nicholas M. Deutscher, Debra Wunch, Dietrich G. Feist, Isamu Morino, Robert J. Parker, Kimberly Strong, Yukio Yoshida, Andrey Bril, Sergey Oshchepkov, Hartmut Boesch, Manvendra K. Dubey, David Griffith, Will Hewson, Rigel Kivi, Joseph Mendonca, Justus Notholt, Matthias Schneider, Ralf Sussmann, Voltaire A. Velazco, and Shuji Aoki
Atmos. Chem. Phys., 17, 143–157, https://doi.org/10.5194/acp-17-143-2017, https://doi.org/10.5194/acp-17-143-2017, 2017
Misa Ishizawa, Osamu Uchino, Isamu Morino, Makoto Inoue, Yukio Yoshida, Kazuo Mabuchi, Tomoko Shirai, Yasunori Tohjima, Shamil Maksyutov, Hirofumi Ohyama, Shuji Kawakami, Atsushi Takizawa, and Dmitry Belikov
Atmos. Chem. Phys., 16, 9149–9161, https://doi.org/10.5194/acp-16-9149-2016, https://doi.org/10.5194/acp-16-9149-2016, 2016
Short summary
Short summary
Greenhouse gases Observing SATellite (GOSAT) was launched to monitor CO2 and CH4 concentrations from the space. This paper analyses an extremely high XCH4 event over Northeast Asia observed by GOSAT in the summer of 2013. Results indicate that the high XCH4 event was caused by fast transport of CH4-rich air from East China to Japan due to anomalies of north Pacific high-pressure system over East Asia. This study demonstrates the capability of GOSAT to detect an XCH4 event on a synoptic scale.
R. Hossaini, P. K. Patra, A. A. Leeson, G. Krysztofiak, N. L. Abraham, S. J. Andrews, A. T. Archibald, J. Aschmann, E. L. Atlas, D. A. Belikov, H. Bönisch, L. J. Carpenter, S. Dhomse, M. Dorf, A. Engel, W. Feng, S. Fuhlbrügge, P. T. Griffiths, N. R. P. Harris, R. Hommel, T. Keber, K. Krüger, S. T. Lennartz, S. Maksyutov, H. Mantle, G. P. Mills, B. Miller, S. A. Montzka, F. Moore, M. A. Navarro, D. E. Oram, K. Pfeilsticker, J. A. Pyle, B. Quack, A. D. Robinson, E. Saikawa, A. Saiz-Lopez, S. Sala, B.-M. Sinnhuber, S. Taguchi, S. Tegtmeier, R. T. Lidster, C. Wilson, and F. Ziska
Atmos. Chem. Phys., 16, 9163–9187, https://doi.org/10.5194/acp-16-9163-2016, https://doi.org/10.5194/acp-16-9163-2016, 2016
C. Song, S. Maksyutov, D. Belikov, H. Takagi, and J. Shu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-6745-2015, https://doi.org/10.5194/acpd-15-6745-2015, 2015
Preprint withdrawn
S. Maksyutov, H. Takagi, V. K. Valsala, M. Saito, T. Oda, T. Saeki, D. A. Belikov, R. Saito, A. Ito, Y. Yoshida, I. Morino, O. Uchino, R. J. Andres, and T. Yokota
Atmos. Chem. Phys., 13, 9351–9373, https://doi.org/10.5194/acp-13-9351-2013, https://doi.org/10.5194/acp-13-9351-2013, 2013
D. A. Belikov, S. Maksyutov, M. Krol, A. Fraser, M. Rigby, H. Bian, A. Agusti-Panareda, D. Bergmann, P. Bousquet, P. Cameron-Smith, M. P. Chipperfield, A. Fortems-Cheiney, E. Gloor, K. Haynes, P. Hess, S. Houweling, S. R. Kawa, R. M. Law, Z. Loh, L. Meng, P. I. Palmer, P. K. Patra, R. G. Prinn, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013, https://doi.org/10.5194/acp-13-1093-2013, 2013
T. Saeki, R. Saito, D. Belikov, and S. Maksyutov
Geosci. Model Dev., 6, 81–100, https://doi.org/10.5194/gmd-6-81-2013, https://doi.org/10.5194/gmd-6-81-2013, 2013
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-516, https://doi.org/10.5194/essd-2023-516, 2024
Preprint under review for ESSD
Short summary
Short summary
This study provides an overview of data availability from observation and inventory-based CH4 emissions estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more Parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1955, https://doi.org/10.5194/egusphere-2023-1955, 2023
Short summary
Short summary
In this work, Nanjing University Carbon Assimilation System (NUCAS) was developed. Data assimilation experiments were conducted to demonstrate the robustness and to investigate the feasibility and applicability of NUCAS. The assimilation of COS significantly improved the model performance in gross primary productivity, sensible heat, latent heat and even soil moisture, demonstrating that COS can provide strong constraints on parameters relevant to water, energy and carbon processes.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
Short summary
Short summary
Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Alessandro Damiani, Hitoshi Irie, Dmitry A. Belikov, Shuei Kaizuka, Hossain Mohammed Syedul Hoque, and Raul R. Cordero
Atmos. Chem. Phys., 22, 12705–12726, https://doi.org/10.5194/acp-22-12705-2022, https://doi.org/10.5194/acp-22-12705-2022, 2022
Short summary
Short summary
We analyzed the variabilities in tropospheric gases and aerosols within the Greater Tokyo Area, Japan. Beyond highlighting air quality changes caused by the pandemic during the lockdown, we found that the degree of weekly cycling of most gases and aerosols was enhanced during the whole of 2020. The changes were unprecedented in recent years and potentially related to coincident reduced mobility in Japan, which, in contrast to other countries, was anomalously low on weekends in 2020.
Omaira E. García, Matthias Schneider, Eliezer Sepúlveda, Frank Hase, Thomas Blumenstock, Emilio Cuevas, Ramón Ramos, Jochen Gross, Sabine Barthlott, Amelie N. Röhling, Esther Sanromá, Yenny González, Ángel J. Gómez-Peláez, Mónica Navarro-Comas, Olga Puentedura, Margarita Yela, Alberto Redondas, Virgilio Carreño, Sergio F. León-Luis, Enrique Reyes, Rosa D. García, Pedro P. Rivas, Pedro M. Romero-Campos, Carlos Torres, Natalia Prats, Miguel Hernández, and César López
Atmos. Chem. Phys., 21, 15519–15554, https://doi.org/10.5194/acp-21-15519-2021, https://doi.org/10.5194/acp-21-15519-2021, 2021
Short summary
Short summary
This paper analyses the potential of ground-based Fourier transform infrared (FTIR) solar observations to monitor atmospheric gaseous composition and investigate multiple climate processes. To this end, this work reviews the FTIR programme of one of most relevant ground-based FTIR stations at a global scale, the subtropical Izaña Observatory (IZO, Spain), going over its history during its first 20 years of operation (1999–2018) and exploring its great value for long-term climate research.
Shamil Maksyutov, Tomohiro Oda, Makoto Saito, Rajesh Janardanan, Dmitry Belikov, Johannes W. Kaiser, Ruslan Zhuravlev, Alexander Ganshin, Vinu K. Valsala, Arlyn Andrews, Lukasz Chmura, Edward Dlugokencky, László Haszpra, Ray L. Langenfelds, Toshinobu Machida, Takakiyo Nakazawa, Michel Ramonet, Colm Sweeney, and Douglas Worthy
Atmos. Chem. Phys., 21, 1245–1266, https://doi.org/10.5194/acp-21-1245-2021, https://doi.org/10.5194/acp-21-1245-2021, 2021
Short summary
Short summary
In order to improve the top-down estimation of the anthropogenic greenhouse gas emissions, a high-resolution inverse modelling technique was developed for applications to global transport modelling of carbon dioxide and other greenhouse gases. A coupled Eulerian–Lagrangian transport model and its adjoint are combined with surface fluxes at 0.1° resolution to provide high-resolution forward simulation and inverse modelling of surface fluxes accounting for signals from emission hot spots.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
Short summary
Short summary
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Dmitry A. Belikov, Naoko Saitoh, Prabir K. Patra, and Naveen Chandra
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-101, https://doi.org/10.5194/amt-2020-101, 2020
Preprint withdrawn
Brendan Byrne, Dylan B. A. Jones, Kimberly Strong, Saroja M. Polavarapu, Anna B. Harper, David F. Baker, and Shamil Maksyutov
Atmos. Chem. Phys., 19, 13017–13035, https://doi.org/10.5194/acp-19-13017-2019, https://doi.org/10.5194/acp-19-13017-2019, 2019
Short summary
Short summary
Interannual variations in net ecosystem exchange (NEE) estimated from the Greenhouse Gases Observing Satellite (GOSAT) XCO2 measurements are shown to be correlated (P < 0.05) with temperature and FLUXCOM NEE anomalies. Furthermore, the GOSAT-informed NEE anomalies are found to be better correlated with temperature and FLUXCOM anomalies than NEE estimates from most terrestrial biosphere models, suggesting that GOSAT CO2 measurements provide a useful constraint on NEE interannual variability.
Dmitry Belikov, Satoshi Sugawara, Shigeyuki Ishidoya, Fumio Hasebe, Shamil Maksyutov, Shuji Aoki, Shinji Morimoto, and Takakiyo Nakazawa
Atmos. Chem. Phys., 19, 5349–5361, https://doi.org/10.5194/acp-19-5349-2019, https://doi.org/10.5194/acp-19-5349-2019, 2019
Misa Ishizawa, Douglas Chan, Doug Worthy, Elton Chan, Felix Vogel, and Shamil Maksyutov
Atmos. Chem. Phys., 19, 4637–4658, https://doi.org/10.5194/acp-19-4637-2019, https://doi.org/10.5194/acp-19-4637-2019, 2019
Short summary
Short summary
The Canadian Arctic has the potential for enhanced methane (CH4) emissions under global warming. However, the regional CH4 emission (fluxes) estimates range widely. This study analyzes recent Canadian Arctic CH4 observations and estimates the regional emissions. The additional observations yield robust CH4 flux estimates and enable the partitioning of the CH4 sources into wetland and forest fires. The results indicate that years with warmer summer conditions result in more wetland CH4 emissions.
Angel J. Gomez-Pelaez, Ramon Ramos, Emilio Cuevas, Vanessa Gomez-Trueba, and Enrique Reyes
Atmos. Meas. Tech., 12, 2043–2066, https://doi.org/10.5194/amt-12-2043-2019, https://doi.org/10.5194/amt-12-2043-2019, 2019
Short summary
Short summary
In 2015, a CO2/CH4/CO CRDS was installed at Izaña station (Tenerife). We present the acceptance tests, the processing of raw data applied, the ambient measurements performed, and their comparison with other continuous in situ measurements. We determine linear relationships between flow rate, CRDS inlet pressure, and CRDS outlet valve aperture; a slight CO2 correction that takes into account changes in the inlet pressure/flow rate and its origin; and the H2O correction for CO in a novel way.
Jacob K. Hedelius, Junjie Liu, Tomohiro Oda, Shamil Maksyutov, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Jianming Liang, Kevin R. Gurney, Debra Wunch, and Paul O. Wennberg
Atmos. Chem. Phys., 18, 16271–16291, https://doi.org/10.5194/acp-18-16271-2018, https://doi.org/10.5194/acp-18-16271-2018, 2018
Short summary
Short summary
Human activities can cause concentrated emissions of greenhouse gases and other pollutants from cities. There is ongoing effort to convert new satellite observations of pollutants into fluxes for many cities. Here we present a method for determining the flux of three species (CO2, CH4, and CO) from the greater LA area using satellite (CO2 only) and ground-based (all three species) observations. We run tests to estimate uncertainty and find the direct net CO2 flux is 104 ± 26 Tg CO2 yr−1.
R. Cong, M. Saito, R. Hirata, A. Ito, and S. Maksyutov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 115–119, https://doi.org/10.5194/isprs-archives-XLII-4-115-2018, https://doi.org/10.5194/isprs-archives-XLII-4-115-2018, 2018
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
Short summary
Short summary
We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Maarten Krol, Marco de Bruine, Lars Killaars, Huug Ouwersloot, Andrea Pozzer, Yi Yin, Frederic Chevallier, Philippe Bousquet, Prabir Patra, Dmitry Belikov, Shamil Maksyutov, Sandip Dhomse, Wuhu Feng, and Martyn P. Chipperfield
Geosci. Model Dev., 11, 3109–3130, https://doi.org/10.5194/gmd-11-3109-2018, https://doi.org/10.5194/gmd-11-3109-2018, 2018
Short summary
Short summary
The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced. Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis.
Nemesio J. Rodríguez-Fernández, Arnaud Mialon, Stephane Mermoz, Alexandre Bouvet, Philippe Richaume, Ahmad Al Bitar, Amen Al-Yaari, Martin Brandt, Thomas Kaminski, Thuy Le Toan, Yann H. Kerr, and Jean-Pierre Wigneron
Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, https://doi.org/10.5194/bg-15-4627-2018, 2018
Short summary
Short summary
Existing global scale above-ground biomass (AGB) maps are made at very high spatial resolution collecting data during several years. In this paper we discuss the use of a new data set from the SMOS satellite: the vegetation optical depth estimated from low microwave frequencies. It is shown that this new data set is highly sensitive to AGB. The spacial resolution of SMOS is coarse (40 km) but the new data set can be used to monitor AGB variations with time due to its high revisit frequency.
Janne Hakkarainen, Iolanda Ialongo, Shamil Maksyutov, and David Crisp
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-649, https://doi.org/10.5194/acp-2018-649, 2018
Revised manuscript not accepted
Short summary
Short summary
We provide a global (60° S–60° N) view of the XCO2 anomalies, indicators of CO2 emissions to and removal from the atmosphere, and study their annual variations and seasonal patterns. We see that positive anomalies correspond to the emissions from fossil fuel combustion over the major industrial areas as well as biomass burning during different fire seasons. The largest negative anomalies correspond to the growing seasons in the middle latitudes. The results are achieved using NASA's OCO-2 data.
Omaira E. García, Matthias Schneider, Benjamin Ertl, Eliezer Sepúlveda, Christian Borger, Christopher Diekmann, Andreas Wiegele, Frank Hase, Sabine Barthlott, Thomas Blumenstock, Uwe Raffalski, Angel Gómez-Peláez, Martin Steinbacher, Ludwig Ries, and Angel M. de Frutos
Atmos. Meas. Tech., 11, 4171–4215, https://doi.org/10.5194/amt-11-4171-2018, https://doi.org/10.5194/amt-11-4171-2018, 2018
Short summary
Short summary
This work presents the CH4 and N2O products of the MUSICA IASI processor. We analytically assess precisions of 1.5–3 %, good sensitivity in the UTLS region (for CH4 and N2O) and a possibility for retrieving free-tropospheric CH4 at low latitudes independently from CH4 in the UTLS. This is confirmed by comparison to HIPPO profile data (covering a large latitudinal range), continuous GAW data (covering 9 years) and NDACC FTIR data (covering 10 years and three different climate zones).
Yang Qu, Shamil Maksyutov, and Qianlai Zhuang
Biogeosciences, 15, 3967–3973, https://doi.org/10.5194/bg-15-3967-2018, https://doi.org/10.5194/bg-15-3967-2018, 2018
Short summary
Short summary
We developed an algorithm for a fast spin-up by finding the exact solution of a linearized system representing the cyclo-stationary state of a model and implemented it in a biogeochemistry model, the Terrestrial Ecosystem Model. For the test sites with five different plant functional types, the new method saves over 90 % of the original spin-up time in site-level simulations. The developed spin-up method will be used for future quantification of carbon dynamics at fine spatiotemporal scales.
Rosa Delia García, Africa Barreto, Emilio Cuevas, Julian Gröbner, Omaira Elena García, Angel Gómez-Peláez, Pedro Miguel Romero-Campos, Alberto Redondas, Victoria Eugenia Cachorro, and Ramon Ramos
Geosci. Model Dev., 11, 2139–2152, https://doi.org/10.5194/gmd-11-2139-2018, https://doi.org/10.5194/gmd-11-2139-2018, 2018
Short summary
Short summary
A 7-year comparison study between measured and simulated longwave
downward radiation under cloud-free conditions has been performed at BSRN Izaña. Results show an excellent agreement with a mean bias (simulated–measured) less than 1.1 % and RMSE less than 1 %, which are within the instrumental error (2 %).
Ye Yuan, Ludwig Ries, Hannes Petermeier, Martin Steinbacher, Angel J. Gómez-Peláez, Markus C. Leuenberger, Marcus Schumacher, Thomas Trickl, Cedric Couret, Frank Meinhardt, and Annette Menzel
Atmos. Meas. Tech., 11, 1501–1514, https://doi.org/10.5194/amt-11-1501-2018, https://doi.org/10.5194/amt-11-1501-2018, 2018
Short summary
Short summary
This paper presents a novel statistical method, ADVS, for baseline selection of representative CO2 data at elevated mountain measurement stations. It provides insights on how data processing techniques are critical for measurements and data analyses. Compared with other statistical methods, our method appears to be a good option as a generalized approach with improved comparability, which is important for research on measurement site characteristics and comparisons between stations.
Tomohiro Oda, Shamil Maksyutov, and Robert J. Andres
Earth Syst. Sci. Data, 10, 87–107, https://doi.org/10.5194/essd-10-87-2018, https://doi.org/10.5194/essd-10-87-2018, 2018
Short summary
Short summary
The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a 1 x 1 km global high-resolution fossil fuel CO2 emissions data product. ODIAC first introduced the combined use of point source profiles and nighttime light satellite data to create high-resolution emissions spatial distributions and it has been intensively used in the carbon cycle research community. This manuscript describes the 2016 version of ODIAC data, the modeling approach, and future data production and model developments.
Thomas Kaminski and Peter Julian Rayner
Biogeosciences, 14, 4755–4766, https://doi.org/10.5194/bg-14-4755-2017, https://doi.org/10.5194/bg-14-4755-2017, 2017
Short summary
Short summary
Observations can reduce uncertainties in past, current, and predicted natural and anthropogenic CO2 fluxes. They provide independent information for verification of actions as requested by the Paris Agreement. Quantitative network design (QND) is an objective approach to optimise in situ networks and space missions to achieve an optimal use of the observational capabilities. We describe recent progress and advocate an integrated QND system that simultaneously evaluates multiple data streams.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
Short summary
Short summary
We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
Short summary
Short summary
Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
Aleksandr F. Sabrekov, Benjamin R. K. Runkle, Mikhail V. Glagolev, Irina E. Terentieva, Victor M. Stepanenko, Oleg R. Kotsyurbenko, Shamil S. Maksyutov, and Oleg S. Pokrovsky
Biogeosciences, 14, 3715–3742, https://doi.org/10.5194/bg-14-3715-2017, https://doi.org/10.5194/bg-14-3715-2017, 2017
Short summary
Short summary
Boreal lakes and wetland ponds have pronounced impacts on the global methane cycle. During field campaigns to West Siberian lakes, strong variations in the methane flux on both local and regional scales were observed, with significant emissions from southern taiga lakes. A newly constructed process-based model helps reveal what controls this variability and on what spatial scales. Our results provide insights into the emissions and possible ways to significantly improve global carbon models.
Thomas Kaminski, Bernard Pinty, Michael Voßbeck, Maciej Lopatka, Nadine Gobron, and Monica Robustelli
Biogeosciences, 14, 2527–2541, https://doi.org/10.5194/bg-14-2527-2017, https://doi.org/10.5194/bg-14-2527-2017, 2017
Short summary
Short summary
We present the Joint Research Centre Two-stream Inversion Package (JRC-TIP) for retrieval of variables characterising the state of the vegetation–soil system. The system provides a set of land surface variables that satisfy all requirements for assimilation into the land component of climate and numerical weather prediction models.
Thomas Kaminski and Pierre-Philippe Mathieu
Biogeosciences, 14, 2343–2357, https://doi.org/10.5194/bg-14-2343-2017, https://doi.org/10.5194/bg-14-2343-2017, 2017
Short summary
Short summary
This paper provides the formalism and examples of how observation operators can be used, in combination with data assimilation or retrieval techniques, to better ingest satellite products in a manner consistent with the dynamics of the Earth system expressed by models.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters
Geosci. Model Dev., 10, 1261–1289, https://doi.org/10.5194/gmd-10-1261-2017, https://doi.org/10.5194/gmd-10-1261-2017, 2017
Short summary
Short summary
In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
Jinwoong Kim, Hyun Mee Kim, Chun-Ho Cho, Kyung-On Boo, Andrew R. Jacobson, Motoki Sasakawa, Toshinobu Machida, Mikhail Arshinov, and Nikolay Fedoseev
Atmos. Chem. Phys., 17, 2881–2899, https://doi.org/10.5194/acp-17-2881-2017, https://doi.org/10.5194/acp-17-2881-2017, 2017
Short summary
Short summary
To investigate the effect of CO2 observations in Siberia on the surface CO2 flux analyses, two experiments using observation data sets with and without Siberian measurements were performed. While the magnitude of the optimized surface CO2 flux uptake in Siberia decreased, that in the other regions of the Northern Hemisphere increased for the experiment with Siberian observations. It is expected that the Siberian observations play an important role in estimating surface CO2 flux in the future.
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
Short summary
Short summary
The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Dmitry A. Belikov, Shamil Maksyutov, Alexander Ganshin, Ruslan Zhuravlev, Nicholas M. Deutscher, Debra Wunch, Dietrich G. Feist, Isamu Morino, Robert J. Parker, Kimberly Strong, Yukio Yoshida, Andrey Bril, Sergey Oshchepkov, Hartmut Boesch, Manvendra K. Dubey, David Griffith, Will Hewson, Rigel Kivi, Joseph Mendonca, Justus Notholt, Matthias Schneider, Ralf Sussmann, Voltaire A. Velazco, and Shuji Aoki
Atmos. Chem. Phys., 17, 143–157, https://doi.org/10.5194/acp-17-143-2017, https://doi.org/10.5194/acp-17-143-2017, 2017
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
Short summary
Short summary
An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Gregor J. Schürmann, Thomas Kaminski, Christoph Köstler, Nuno Carvalhais, Michael Voßbeck, Jens Kattge, Ralf Giering, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, https://doi.org/10.5194/gmd-9-2999-2016, 2016
Short summary
Short summary
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
Irina Evgenievna Terentieva, Mikhail Vladimirovich Glagolev, Elena Dmitrievna Lapshina, Alexandr Faritovich Sabrekov, and Shamil Maksyutov
Biogeosciences, 13, 4615–4626, https://doi.org/10.5194/bg-13-4615-2016, https://doi.org/10.5194/bg-13-4615-2016, 2016
Short summary
Short summary
West Siberia (WS) wetlands are the world’s largest high-latitude wetland system. WS methane emission estimates suffered from large uncertainty due to high emission rate variability across the wetland vegetation cover. We mapped WS taiga zone wetlands with Landsat imagery and applied wetland typology specifically developed to reflect heterogeneity of methane fluxes. The map provides a benchmark for validation of coarse-resolution land cover products and wetland data sets in high latitudes.
Misa Ishizawa, Osamu Uchino, Isamu Morino, Makoto Inoue, Yukio Yoshida, Kazuo Mabuchi, Tomoko Shirai, Yasunori Tohjima, Shamil Maksyutov, Hirofumi Ohyama, Shuji Kawakami, Atsushi Takizawa, and Dmitry Belikov
Atmos. Chem. Phys., 16, 9149–9161, https://doi.org/10.5194/acp-16-9149-2016, https://doi.org/10.5194/acp-16-9149-2016, 2016
Short summary
Short summary
Greenhouse gases Observing SATellite (GOSAT) was launched to monitor CO2 and CH4 concentrations from the space. This paper analyses an extremely high XCH4 event over Northeast Asia observed by GOSAT in the summer of 2013. Results indicate that the high XCH4 event was caused by fast transport of CH4-rich air from East China to Japan due to anomalies of north Pacific high-pressure system over East Asia. This study demonstrates the capability of GOSAT to detect an XCH4 event on a synoptic scale.
R. Hossaini, P. K. Patra, A. A. Leeson, G. Krysztofiak, N. L. Abraham, S. J. Andrews, A. T. Archibald, J. Aschmann, E. L. Atlas, D. A. Belikov, H. Bönisch, L. J. Carpenter, S. Dhomse, M. Dorf, A. Engel, W. Feng, S. Fuhlbrügge, P. T. Griffiths, N. R. P. Harris, R. Hommel, T. Keber, K. Krüger, S. T. Lennartz, S. Maksyutov, H. Mantle, G. P. Mills, B. Miller, S. A. Montzka, F. Moore, M. A. Navarro, D. E. Oram, K. Pfeilsticker, J. A. Pyle, B. Quack, A. D. Robinson, E. Saikawa, A. Saiz-Lopez, S. Sala, B.-M. Sinnhuber, S. Taguchi, S. Tegtmeier, R. T. Lidster, C. Wilson, and F. Ziska
Atmos. Chem. Phys., 16, 9163–9187, https://doi.org/10.5194/acp-16-9163-2016, https://doi.org/10.5194/acp-16-9163-2016, 2016
Omaira Elena García, Eliezer Sepúlveda, Matthias Schneider, Frank Hase, Thomas August, Thomas Blumenstock, Sven Kühl, Rosemary Munro, Ángel Jesús Gómez-Peláez, Tim Hultberg, Alberto Redondas, Sabine Barthlott, Andreas Wiegele, Yenny González, and Esther Sanromá
Atmos. Meas. Tech., 9, 2315–2333, https://doi.org/10.5194/amt-9-2315-2016, https://doi.org/10.5194/amt-9-2315-2016, 2016
Short summary
Short summary
Atmospheric remote sounding from space is fundamental for investigating the processes driving climate change. However, for a correct scientific interpretation of these records a documentation of their quality is required. In this context, this paper exploits the high potential of the Izaña Atmospheric Observatory, as a ground-based reference site, to perform the first comprehensive validation of the EUMETSAT atmospheric trace gas products O3, CH4, N2O, CO and CO2 of the remote sensor IASI.
E. Cuevas, Á. J. Gómez-Peláez, S. Rodríguez, E. Terradellas, S. Basart, R. D. García, O. E. García, and S. Alonso-Pérez
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-287, https://doi.org/10.5194/acp-2016-287, 2016
Revised manuscript not accepted
Short summary
Short summary
We revise the North African Dipole Intensity (NAFDI) index, and explain and quantify its relationship with the Saharan Heat Low (SHL) and mid-latitude Rossby waves. An analysis of aerosol optical depth anomalies over Northern Africa is performed for each phase of NAFDI/SHL. A comprehensive top-down conceptual model is introduced to explain the relationships between the NAFDI, the SHL and the mid-latitude Rossby waves and their impact in dust mobilization and transport in Northern Africa.
Stig B. Dalsøren, Cathrine L. Myhre, Gunnar Myhre, Angel J. Gomez-Pelaez, Ole A. Søvde, Ivar S. A. Isaksen, Ray F. Weiss, and Christina M. Harth
Atmos. Chem. Phys., 16, 3099–3126, https://doi.org/10.5194/acp-16-3099-2016, https://doi.org/10.5194/acp-16-3099-2016, 2016
Short summary
Short summary
Methane is a key greenhouse gas. Observations at surface sites show a more than 10 % increase over the period 1984–2012. Using an atmospheric model we calculate a growth in the atmospheric chemical methane loss the last decades. Without this, the rise in atmospheric methane would have been even higher. The model reproduces trends and short-term variations in observation data. However, some discrepancies in model performance question the accuracy in estimates of emission increases in Asia.
A. Berchet, I. Pison, F. Chevallier, J.-D. Paris, P. Bousquet, J.-L. Bonne, M. Y. Arshinov, B. D. Belan, C. Cressot, D. K. Davydov, E. J. Dlugokencky, A. V. Fofonov, A. Galanin, J. Lavrič, T. Machida, R. Parker, M. Sasakawa, R. Spahni, B. D. Stocker, and J. Winderlich
Biogeosciences, 12, 5393–5414, https://doi.org/10.5194/bg-12-5393-2015, https://doi.org/10.5194/bg-12-5393-2015, 2015
T. Kaminski, F. Kauker, H. Eicken, and M. Karcher
The Cryosphere, 9, 1721–1733, https://doi.org/10.5194/tc-9-1721-2015, https://doi.org/10.5194/tc-9-1721-2015, 2015
Short summary
Short summary
We present a quantitative network design study of the Arctic sea ice-ocean system. For a demonstration, we evaluate two idealised hypothetical flight transects derived from NASA’s Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. It further quantifies the complementarity of combining two flight transects.
T. J. Bohn, J. R. Melton, A. Ito, T. Kleinen, R. Spahni, B. D. Stocker, B. Zhang, X. Zhu, R. Schroeder, M. V. Glagolev, S. Maksyutov, V. Brovkin, G. Chen, S. N. Denisov, A. V. Eliseev, A. Gallego-Sala, K. C. McDonald, M.A. Rawlins, W. J. Riley, Z. M. Subin, H. Tian, Q. Zhuang, and J. O. Kaplan
Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, https://doi.org/10.5194/bg-12-3321-2015, 2015
Short summary
Short summary
We evaluated 21 forward models and 5 inversions over western Siberia in terms of CH4 emissions and simulated wetland areas and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite inundation products. In addition to assembling a definitive collection of methane emissions estimates for the region, we were able to identify the types of wetland maps and model features necessary for accurate simulations of high-latitude wetlands.
C. Song, S. Maksyutov, D. Belikov, H. Takagi, and J. Shu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-6745-2015, https://doi.org/10.5194/acpd-15-6745-2015, 2015
Preprint withdrawn
M. Saito, A. Ito, and S. Maksyutov
Geosci. Model Dev., 7, 1829–1840, https://doi.org/10.5194/gmd-7-1829-2014, https://doi.org/10.5194/gmd-7-1829-2014, 2014
S. Kemp, M. Scholze, T. Ziehn, and T. Kaminski
Geosci. Model Dev., 7, 1609–1619, https://doi.org/10.5194/gmd-7-1609-2014, https://doi.org/10.5194/gmd-7-1609-2014, 2014
E. Sepúlveda, M. Schneider, F. Hase, S. Barthlott, D. Dubravica, O. E. García, A. Gomez-Pelaez, Y. González, J. C. Guerra, M. Gisi, R. Kohlhepp, S. Dohe, T. Blumenstock, K. Strong, D. Weaver, M. Palm, A. Sadeghi, N. M. Deutscher, T. Warneke, J. Notholt, N. Jones, D. W. T. Griffith, D. Smale, G. W. Brailsford, J. Robinson, F. Meinhardt, M. Steinbacher, T. Aalto, and D. Worthy
Atmos. Meas. Tech., 7, 2337–2360, https://doi.org/10.5194/amt-7-2337-2014, https://doi.org/10.5194/amt-7-2337-2014, 2014
W. Knorr, T. Kaminski, A. Arneth, and U. Weber
Biogeosciences, 11, 1085–1102, https://doi.org/10.5194/bg-11-1085-2014, https://doi.org/10.5194/bg-11-1085-2014, 2014
Y. Tohjima, M. Kubo, C. Minejima, H. Mukai, H. Tanimoto, A. Ganshin, S. Maksyutov, K. Katsumata, T. Machida, and K. Kita
Atmos. Chem. Phys., 14, 1663–1677, https://doi.org/10.5194/acp-14-1663-2014, https://doi.org/10.5194/acp-14-1663-2014, 2014
T. J. Bohn, E. Podest, R. Schroeder, N. Pinto, K. C. McDonald, M. Glagolev, I. Filippov, S. Maksyutov, M. Heimann, X. Chen, and D. P. Lettenmaier
Biogeosciences, 10, 6559–6576, https://doi.org/10.5194/bg-10-6559-2013, https://doi.org/10.5194/bg-10-6559-2013, 2013
S. Maksyutov, H. Takagi, V. K. Valsala, M. Saito, T. Oda, T. Saeki, D. A. Belikov, R. Saito, A. Ito, Y. Yoshida, I. Morino, O. Uchino, R. J. Andres, and T. Yokota
Atmos. Chem. Phys., 13, 9351–9373, https://doi.org/10.5194/acp-13-9351-2013, https://doi.org/10.5194/acp-13-9351-2013, 2013
A. J. Gomez-Pelaez, R. Ramos, V. Gomez-Trueba, P. C. Novelli, and R. Campo-Hernandez
Atmos. Meas. Tech., 6, 787–799, https://doi.org/10.5194/amt-6-787-2013, https://doi.org/10.5194/amt-6-787-2013, 2013
D. A. Belikov, S. Maksyutov, M. Krol, A. Fraser, M. Rigby, H. Bian, A. Agusti-Panareda, D. Bergmann, P. Bousquet, P. Cameron-Smith, M. P. Chipperfield, A. Fortems-Cheiney, E. Gloor, K. Haynes, P. Hess, S. Houweling, S. R. Kawa, R. M. Law, Z. Loh, L. Meng, P. I. Palmer, P. K. Patra, R. G. Prinn, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013, https://doi.org/10.5194/acp-13-1093-2013, 2013
T. Saeki, R. Saito, D. Belikov, and S. Maksyutov
Geosci. Model Dev., 6, 81–100, https://doi.org/10.5194/gmd-6-81-2013, https://doi.org/10.5194/gmd-6-81-2013, 2013
Related subject area
Atmospheric sciences
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
Advances and Prospects of Deep Learning for Medium-Range Extreme Weather Forecasting
A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models
The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Challenges of constructing and selecting the "perfect" initial and boundary conditions for the LES model PALM
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective
Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model
Efficient and Stable Coupling of the SuperdropNet Deep Learning-based Cloud Microphysics (v0.1.0) to the ICON Climate and Weather Model (v2.6.5)
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data
Validation and Analysis of the Polair3D v1.11 Chemical Transport Model Over Quebec
The capabilities of the adjoint of GEOS-Chem model to support HEMCO emission inventories and MERRA-2 meteorological data
Rapid O3 assimilations – Part 1: Background and local contributions to tropospheric O3 changes in China in 2015–2020
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
Short summary
Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
Short summary
Short summary
PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Short summary
Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
Short summary
Short summary
Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
Short summary
Short summary
We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
Short summary
Short summary
The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
Short summary
Short summary
We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
Short summary
Short summary
A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
Short summary
Short summary
The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
Short summary
Short summary
Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
Short summary
Short summary
Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
Short summary
Short summary
Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
Short summary
Short summary
This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
Short summary
Short summary
With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
Short summary
Short summary
GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
Short summary
Short summary
In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
Short summary
Short summary
The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
Short summary
Short summary
Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
Short summary
Short summary
In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
Short summary
Short summary
We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
Short summary
Short summary
The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
Short summary
Short summary
Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
Short summary
Short summary
Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
Short summary
Short summary
A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
Short summary
Short summary
Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
Short summary
Short summary
Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
Short summary
Short summary
In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
Short summary
Short summary
This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
Short summary
Short summary
We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
Short summary
Short summary
Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
Short summary
Short summary
Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
Short summary
Short summary
Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
Short summary
Short summary
The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
Short summary
Short summary
We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Hang, and Feijuan Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-201, https://doi.org/10.5194/gmd-2023-201, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize PWV variation with altitude in the study area. The RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
Short summary
Short summary
The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
Short summary
Short summary
In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Leonardo Olivetti and Gabriele Messori
EGUsphere, https://doi.org/10.5194/egusphere-2023-2490, https://doi.org/10.5194/egusphere-2023-2490, 2023
Short summary
Short summary
In recent years, deep learning models have emerged as a data-driven alternative to physics-based models for medium-range weather forecasting. This article provides an overview of recent developments in the field, and explores the challenges that deep learning models face when considering extreme weather events. It argues for the need to complement current approaches with models specifically designed to handle extreme events, and proposes a foundational framework to develop such models.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
Short summary
Short summary
Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
Short summary
Short summary
This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Jelena Radovic, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-197, https://doi.org/10.5194/gmd-2023-197, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
The initial and boundary conditions are of crucial importance for numerical model (e.g., PALM model) validation studies and have a large influence on the model results especially in the case of studying the atmosphere of a real, complex, and densely built urban environments. Our experiments with different driving conditions for the LES model PALM show its strong dependency on them which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
Short summary
Short summary
Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
Short summary
Short summary
It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David Greenberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-2047, https://doi.org/10.5194/egusphere-2023-2047, 2023
Short summary
Short summary
In weather and climate models, rain formation is simplified by parameterizations to be computationally efficient. We trained a machine learning algorithm, SuperdropNet, to emulate rain formation in warm clouds based on physically more accurate super-droplet simulations. Here, we validate SuperdropNet coupled to ICON in a warm bubble experiment. We find the coupled simulation runs stable and produces reasonable results, and present a computational benchmark for the coupling software.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
EGUsphere, https://doi.org/10.5194/egusphere-2023-2587, https://doi.org/10.5194/egusphere-2023-2587, 2023
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation we find that MESSy’s bias in modelling routinely observed inorganic aerosol mass concentrations is reduced. Furthermore, the representation of fine aerosol pH is particularly improved in the marine boundary layer.
Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento
Geosci. Model Dev., 16, 6413–6431, https://doi.org/10.5194/gmd-16-6413-2023, https://doi.org/10.5194/gmd-16-6413-2023, 2023
Short summary
Short summary
A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Youngseob Kim, Daniel Yazgi, Andrée-Anne Brown, and Marianne Hatzopoulou
EGUsphere, https://doi.org/10.5194/egusphere-2023-2038, https://doi.org/10.5194/egusphere-2023-2038, 2023
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models are valuable tools that aid in our understanding of the risks of air pollution both at local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Zhaojun Tang, Zhe Jiang, Jiaqi Chen, Panpan Yang, and Yanan Shen
Geosci. Model Dev., 16, 6377–6392, https://doi.org/10.5194/gmd-16-6377-2023, https://doi.org/10.5194/gmd-16-6377-2023, 2023
Short summary
Short summary
We designed a new framework to facilitate emission inventory updates in the adjoint of GEOS-Chem model. It allows us to support Harmonized Emissions Component (HEMCO) emission inventories conveniently and to easily add more emission inventories following future updates in GEOS-Chem forward simulations. Furthermore, we developed new modules to support MERRA-2 meteorological data; this allows us to perform long-term analysis with consistent meteorological data.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Geosci. Model Dev., 16, 6337–6354, https://doi.org/10.5194/gmd-16-6337-2023, https://doi.org/10.5194/gmd-16-6337-2023, 2023
Short summary
Short summary
A single ozone (O3) tracer mode was developed in this work to build the capability of the GEOS-Chem model for rapid O3 simulation. It is combined with OMI and surface O3 observations to investigate the changes in tropospheric O3 in China in 2015–2020. The assimilations indicate rapid surface O3 increases that are underestimated by the a priori simulations. We find stronger increases in tropospheric O3 columns over polluted areas and a large discrepancy by assimilating different observations.
Cited articles
Andres, R. J., Boden, T. A., and Marland, G.: Annual fossil-fuel CO2
emissions: Mass of emissions gridded by one degree latitude by one degree
longitude. Carbon Dioxide Information Analysis Center, Oak Ridge National
Laboratory, US Department of Energy, Oak Ridge, Tenn., USA,
https://doi.org/10.3334/CDIAC/ffe.ndp058.2009, 2009.
Andres, R. J., Gregg, J. S., Losey, L., Marland, G., and Boden, T.: Monthly,
global emissions of carbon dioxide from fossil fuel consumption, Tellus 63B,
309–327, 2011.
Baker, D. F., Law, R. M., Gurney, K. R., Rayner, P., Peylin, P., Denning, A.
S., Bousquet, P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fung, I. Y.,
Heimann, M., John, J., Maki, T., Maksyutov, S., Masarie, K., Prather, M.,
Pak, B., Taguchi, S., and Zhu, Z.: TransCom 3 inversion intercomparison:
impact of transport model errors on the interannual variability of regional
CO2 fluxes, 1988–2003, Global Biogeochem. Cy., 20, GB1002,
https://doi.org/10.1029/2004GB002439, 2006.
Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I.,
Krummel, P., Steele, P., Langenfelds, R., Torn, M., Biraud, S., Stephens, B.,
Andrews, A., and Worthy, D.: Global CO2 fluxes estimated from GOSAT
retrievals of total column CO2, Atmos. Chem. Phys., 13, 8695–8717,
https://doi.org/10.5194/acp-13-8695-2013, 2013.
Belikov, D., Maksyutov, S., Miyasaka, T., Saeki, T., Zhuravlev, R., and
Kiryushov, B.: Mass-conserving tracer transport modelling on a reduced
latitude-longitude grid with NIES-TM, Geosci. Model Dev., 4, 207–222,
https://doi.org/10.5194/gmd-4-207-2011, 2011.
Belikov, D. A., Maksyutov, S., Krol, M., Fraser, A., Rigby, M., Bian, H.,
Agusti-Panareda, A., Bergmann, D., Bousquet, P., Cameron-Smith, P.,
Chipperfield, M. P., Fortems-Cheiney, A., Gloor, E., Haynes, K., Hess, P.,
Houweling, S., Kawa, S. R., Law, R. M., Loh, Z., Meng, L., Palmer, P. I.,
Patra, P. K., Prinn, R. G., Saito, R., and Wilson, C.: Off-line algorithm for
calculation of vertical tracer transport in the troposphere due to deep
convection, Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013,
2013a.
Belikov, D. A., Maksyutov, S., Sherlock, V., Aoki, S., Deutscher, N. M.,
Dohe, S., Griffith, D., Kyro, E., Morino, I., Nakazawa, T., Notholt, J.,
Rettinger, M., Schneider, M., Sussmann, R., Toon, G. C., Wennberg, P. O., and
Wunch, D.: Simulations of column-averaged CO2 and CH4 using the NIES TM
with a hybrid sigma-isentropic (s-θ) vertical coordinate, Atmos. Chem.
Phys., 13, 1713–1732, https://doi.org/10.5194/acp-13-1713-2013, 2013b.
Bovensmann, H., Buchwitz, M., Burrows, J. P., Reuter, M., Krings, T.,
Gerilowski, K., Schneising, O., Heymann, J., Tretner, A., and Erzinger, J.: A
remote sensing technique for global monitoring of power plant CO2
emissions from space and related applications, Atmos. Meas. Tech., 3,
781–811, https://doi.org/10.5194/amt-3-781-2010, 2010.
Bruhwiler, L. M. P., Michalak, A. M., Peters, W., Baker, D. F., and Tans, P.:
An improved Kalman Smoother for atmospheric inversions, Atmos. Chem. Phys.,
5, 2691–2702, https://doi.org/10.5194/acp-5-2691-2005, 2005.
Buchwitz, M., Reuter, M., Bovensmann, H., Pillai, D., Heymann, J.,
Schneising, O., Rozanov, V., Krings, T., Burrows, J. P., Boesch, H., Gerbig,
C., Meijer, Y., and Löscher, A.: Carbon Monitoring Satellite (CarbonSat):
assessment of atmospheric CO2 and CH4 retrieval errors by error
parameterization, Atmos. Meas. Tech., 6, 3477–3500,
https://doi.org/10.5194/amt-6-3477-2013, 2013.
Chevallier, F., Fisher, M., Peylin, P., Serrar, S., Bousquet, P., Bréon,
F.-M., Chédin, A., and Ciais, P.: Inferring CO2 sources and sinks
from satellite observations: method and application to TOVS data, J. Geophys.
Res., 110, D24309, https://doi.org/10.1029/2005JD006390, 2005.
Crisp, D., Atlas, R. M., Bréon, F.-M., Brown, L. R., Burrows, J. P.,
Ciais, P., Connor, B. J., Doney, S. C., Fung, I. Y., Jacob, D. J., Miller, C.
E., O'Brien, D., Pawson, S., Randerson, J. T., Rayner, P., Salawitch, R. S.,
Sander, S. P., Sen, B., Stephens, G. L., Tans, P. P., Toon, G. C., Wennberg,
P. O., Wofsy, S. C., Yung, Y. L., Kuang, Z., Chudasama, B., Sprague, G.,
Weiss, P., Pollock, R., Kenyon, D., and Schroll, S.: The Orbiting Carbon
Observatory (OCO) mission, Adv. Space Res., 34, 700–709, 2004.
Deng, F., Jones, D. B. A., Henze, D. K., Bousserez, N., Bowman, K. W.,
Fisher, J. B., Nassar, R., O'Dell, C., Wunch, D., Wennberg, P. O., Kort, E.
A., Wofsy, S. C., Blumenstock, T., Deutscher, N. M., Griffith, D. W. T.,
Hase, F., Heikkinen, P., Sherlock, V., Strong, K., Sussmann, R., and Warneke,
T.: Inferring regional sources and sinks of atmospheric CO2 from GOSAT
XCO2 data, Atmos. Chem. Phys., 14, 3703–3727,
https://doi.org/10.5194/acp-14-3703-2014, 2014.
Denning, A. S., Holzer, M., Gurney, K. R., Heimann, M., Law, R. M.,
Rayner, P. J., Fung, I. Y., Fan, S., Taguchi, S., Friedlingstein, P.,
Balkanski, Y., Taylor, J., Maiss, M., and Levin, I.: Three-dimensional
transport and concentration of SF6: a model intercomparison study
(TransCom-2), Tellus B, 51, 266–297, 1999.
Elbern, H., Schmidt, H., and Ebel, A.: Variational data assimilation for
tropospheric chemistry modeling, J. Geophys. Res., 102, 15967–15985, 1997.
Enting, I. G. and Mansbridge, J. V.: Seasonal sources and sinks of
atmospheric CO2: Direct inversion of filtered data, Tellus B, 41,
111–126, https://doi.org/10.1111/j.1600-0889.1989.tb00129.x, 1989.
Enting, I. T.: Inverse problems in atmospheric constituent transport,
Cambridge University Press, Cambridge, UK, 2002.
Ganshin, A., Oda, T., Saito, M., Maksyutov, S., Valsala, V., Andres, R. J.,
Fisher, R. E., Lowry, D., Lukyanov, A., Matsueda, H., Nisbet, E. G., Rigby,
M., Sawa, Y., Toumi, R., Tsuboi, K., Varlagin, A., and Zhuravlev, R.: A
global coupled Eulerian-Lagrangian model and 1 × 1 km CO2
surface flux dataset for high-resolution atmospheric CO2 transport
simulations, Geosci. Model Dev., 5, 231–243, https://doi.org/10.5194/gmd-5-231-2012,
2012.
Ganshin, A. V., Zhuravlev, R. V., Maksyutov, S., Lukyanov, A. N.,
and Mukai, H.: Simulation of contribution of continental anthropogenic
sources to variations in the CO2 concentration during winter period on
Hateruma Island, Atmos. Ocean. Opt., 26, 35–40, 2013.
Giles, M. B. and Pierce, N. A.: An Introduction to the Adjoint Approach to
Design, Flow Turbul. Combust., 65, 393–415, 2000.
Giering, R. and Kaminski, T.: Recipes for adjoint code construction, Trans.
Math. Software, 24, 437–474, https://doi.org/10.1145/293686.293695, 1998.
GLOBALVIEW-CO2: Cooperative Atmospheric Data Integration Project – Carbon
Dioxide, CD-ROM, NOAA ESRL, Boulder, Colorado (also available on Internet via
anonymous FTP to ftp://ftp.cmdl.noaa.gov, last access: 8 January 2014, Path: ccg/co2/GLOBALVIEW),
2014.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D.,
Bousquet, P., Bruhwilerk, L., Chen, Y.-H., Ciais, P., Fan, S., Fung, I.,
Gloor, M., Heimann, M., Higuchi, K., John, J., Maki, T., Maksyutov, S.,
Masarie, K., Peylin, P., Prather, M., Pak, B. C., Randerson, J. R.,
Sarmiento, J., Taguchi, S., Takahashi, T., and Yuen, C.-W.: Towards robust
regional estimates of CO2 sources and sinks using atmospheric transport
models, Nature, 415, 626–630, 2002.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Pak, B. C., Baker,
D., Bousquet, P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fung, I. Y.,
Heimann, M., John, J., Maki, T., Maksyutov, S., Peylin, P., Prather, M., and
Taguchi, S.: Transcom 3 inversion intercomparison: model mean results for the
estimation of seasonal carbon sources and sinks, Global Biogeochem. Cy., 18,
GB1010, https://doi.org/10.1029/2003GB002111, 2004.
Hack, J. J., Boville, B. A., Briegleb, B. P., Kiehl, J. T., Rasch, P. J., and
Williamson, D. L.: Description of the NCAR community climate model (CCM2),
NCAR/TN-382, 108, 1993.
Haines, P. E., Esler, J. G., and Carver, G. D.: Technical Note: Adjoint
formulation of the TOMCAT atmospheric transport scheme in the Eulerian
backtracking framework (RETRO-TOM), Atmos. Chem. Phys., 14, 5477–5493,
https://doi.org/10.5194/acp-14-5477-2014, 2014.
Hayes, D. J., McGuire, A. D., Kicklighter, D. W., Gurney, K. R., Burnside, T.
J., and Melillo, J. M.: Is the northern high-latitude land-based CO2
sink weakening?, Global Biogeochem. Cy., 25, GB3018,
https://doi.org/10.1029/2010GB003813, 2011.
Henze, D. K., Hakami, A., and Seinfeld, J. H.: Development of the adjoint of
GEOS-Chem, Atmos. Chem. Phys., 7, 2413–2433, https://doi.org/10.5194/acp-7-2413-2007,
2007.
Hourdin, F. and Talagrand, O.: Eulerian backtracking of atmospheric tracers.
I: Adjoint derivation and parametrization of subgid-scale transport, Q. J.
Roy. Meteor. Soc., 132, 585–603, 2006.
IPCC: Climate change 2007: the physical science basis, in: Contribution of
Working Group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt,
K. B., Tignor, M., and Miller, H. L., Cambridge
University Press, Cambridge, 135–145, 2007.
Ito, A.: Changing ecophysiological processes and carbon budget in East Asian
ecosystems under near-future changes in climate: Implications for long-term
monitoring from a process-based model, J. Plant Res., 123, 577–588, 2010.
Kaminski, T., Heimann, M., and Giering, R.: A coarse grid three-dimensional
global inverse model of the atmospheric transport: 1. Adjoint model and
Jacobian matrix, J. Geophys. Res., 104, 18535–18553,
https://doi.org/10.1029/1999JD900147, 1999a.
Kaminski, T., Heimann, M., and Giering, R.: A coarse grid three-dimensional
global inverse model of the atmospheric transport: 2. Inversion of the
transport of CO2 in the 1980s, J. Geophys. Res., 104, 18555–18581,
https://doi.org/10.1029/1999JD900146, 1999b.
Kaminski, T., Rayner, P., Heimann, M., and Enting, I.: On aggregation errors
in atmospheric transport inversions, J. Geophys. Res., 106, 4703–4715, https://doi.org/10.1029/2000JD900581,
2001.
Karion, A., Sweeney, C., Wolter, S., Newberger, T., Chen, H., Andrews, A.,
Kofler, J., Neff, D., and Tans, P.: Long-term greenhouse gas measurements
from aircraft, Atmos. Meas. Tech., 6, 511–526, https://doi.org/10.5194/amt-6-511-2013,
2013.
Koyama, Y., Maksyutov, S., Mukai, H., Thoning, K., and Tans, P.: Simulation
of variability in atmospheric carbon dioxide using a global coupled Eulerian
– Lagrangian transport model, Geosci. Model Dev., 4, 317–324,
https://doi.org/10.5194/gmd-4-317-2011, 2011.
Kuze, A., Suto H., Nakajima M., and Hamazaki T.: Thermal and near infrared
sensor for carbon observation Fourier-transform spectrometer on the
Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl.
Optics, 48, 6716–6733, https://doi.org/10.1364/AO.48.006716, 2009.
Law, R. M., Rayner, P. J., Denning, A. S., Erickson, D., Fung, I. Y.,
Heimann, M., Piper, S. C., Ramonet, M., Taguchi, S., Taylor, J. A.,
Trudinger, C. M., and Watterson, I. G.: Variations in modelled atmospheric
transport of carbon dioxide and the consequences for CO2 inversions,
Global Biogeochem. Cy., 10, 783–796, 1996.
Law, R. M., Peters, W., Rödenbeck, C., Aulagnier, C., Baker, I.,
Bergmann, D. J., Bousquet, P., Brandt, J., Bruhwiler, L., Cameron-Smith, P.
J., Christensen, J. H., Delage, F., Denning, A. S., Fan, S., Geels, C.,
Houweling, S., Imasu, R., Karstens, U., Kawa, S. R., Kleist, J., Krol, M. C.,
Lin, S.-J., Lokupitiya, R., Maki, T., Maksyutov, S., Niwa, Y., Onishi, R.,
Parazoo, N., Patra, P. K., Pieterse, G., Rivier, L., Satoh, M., Serrar, S.,
Taguchi, S., Takigawa, M., Vautard, R., Vermeulen, A. T., and Zhu, Z.:
TransCom model simulations of hourly atmospheric CO2: Experimental
overview and diurnal cycle results for 2002, Global Biogeochem. Cy., 22,
GB3009, https://doi.org/10.1029/2007GB003050, 2008.
Liu, J., Bowman, K. W., and Henze D. K.: Source-receptor relationships of
column-average CO2 and implications for the impact of observations on flux
inversions. J. Geophys. Res.-Atmos., 120, 5214–5236,
https://doi.org/10.1002/2014JD022914, 2015.
Liu, Z. and Sandu, A.: On the properties of discrete adjoints of numerical
methods for the advection equation, Int. J. Numer. Meth. Fl., 56, 769–803,
https://doi.org/10.1002/fld.1547, 2008.
Maki, T., Ikegami, M., Fujita, T., Hirahara, T., Yamada, K., Mori, K.,
Takeuchi, A., Tsutsumi, Y., Suda, K., and Conway, T. J.: New technique to
analyse global distributions of CO2 concentrations and fluxes from
non-processed observational data, Tellus B, 62, 797–809,
https://doi.org/10.1111/j.1600-0889.2010.00488.x, 2010.
Maksyutov, S., Patra, P. K., Onishi, R., Saeki, T., and Nakazawa, T.:
NIES/FRCGC Global Atmospheric Tracer Transport Model: Description,
validation, and surface sources and sinks inversion, J. Earth Simulator, 9,
3–18, 2008.
Maksyutov, S., Takagi, H., Valsala, V. K., Saito, M., Oda, T., Saeki, T.,
Belikov, D. A., Saito, R., Ito, A., Yoshida, Y., Morino, I., Uchino, O.,
Andres, R. J., and Yokota, T.: Regional CO2 flux estimates for 2009–2010
based on GOSAT and ground-based CO2 observations, Atmos. Chem. Phys., 13,
9351–9373, https://doi.org/10.5194/acp-13-9351-2013, 2013.
Marchuk, G.: Numerical solution of the problems of the dynamics of the
atmosphere and the ocean, Gidrometeoizdat, Leningrad, 303 pp., 1974 (in
Russian).
Marchuk, G. I.: Adjoint equations and analysis of complex systems, Series:
Mathematics and its applications, Vol. 295, Kluwer Academic Publishers,
Dordrecht and Boston, 484 pp., 1995.
McGuire, A. D., Anderson, L. G., Christensen, T. R., Dallimore, S., Guo, L.
D., Hayes, D. J., Heimann, M., Lorenson, T. D., Macdonald, R. W., and Roulet,
N.: Sensitivity of the carbon cycle in the Arctic to climate change, Ecol.
Monogr., 79, 523–555, https://doi.org/10.1890/08-2025.1, 2009.
Oda, T. and Maksyutov, S.: A very high-resolution (1 km × 1 km)
global fossil fuel CO2 emission inventory derived using a point source
database and satellite observations of nighttime lights, Atmos. Chem. Phys.,
11, 543–556, https://doi.org/10.5194/acp-11-543-2011, 2011.
Onogi, K., Tsutsui, J., Koide, H., Sakamoto, M., Kobayashi, S., Hatsushika,
H., Matsumoto, T., Yamazaki, N., Kamahori, H., Takahashi, K., Kadokura, S.,
Wada, K., Kato, K., Oyama, R., Ose, T., Mannoji, N., and Taira, R.: The
JRA-25 Reanalysis, J. Meteorol. Soc. Jpn., 85, 369–432, 2007.
Patra, P. K., Law, R. M., Peters, W., Rodenbeck, C., Takigawa, M., Aulagnier,
C., Baker, I., Bergmann, D. J., Bousquet, P., Brandt, J., Bruhwiler, L.,
Cameron-Smith, P. J., Christensen, J. H., Delage, F., Denning, A. S., Fan,
S., Geels, C., Houweling, S., Imasu, R., Karstens, U., Kawa, S. R., Kleist,
J., Krol, M. C., Lin, S.-J., Lokupitiya, R., Maki, T., Maksyutov, S., Niwa,
Y., Onishi, R., Parazoo, N., Pieterse, G., River, L., Satoh, M., Serrar, S.,
Taguchi, S., Vautard, R., Vermeulen, A. T., and Zhu, Z.: TransCom model
simulations of hourly atmospheric CO2: Analysis of synoptic-scale
variations for the period 2002–2003, Global Biogeochem. Cy., 22, GB4013,
https://doi.org/10.1029/2007GB003081, 2008.
Patra, P. K., Houweling, S., Krol, M., Bousquet, P., Belikov, D., Bergmann,
D., Bian, H., Cameron-Smith, P., Chipperfield, M. P., Corbin, K.,
Fortems-Cheiney, A., Fraser, A., Gloor, E., Hess, P., Ito, A., Kawa, S. R.,
Law, R. M., Loh, Z., Maksyutov, S., Meng, L., Palmer, P. I., Prinn, R. G.,
Rigby, M., Saito, R., and Wilson, C.: TransCom model simulations of CH4
and related species: linking transport, surface flux and chemical loss with
CH4 variability in the troposphere and lower stratosphere, Atmos. Chem.
Phys., 11, 12813–12837, https://doi.org/10.5194/acp-11-12813-2011, 2011.
Peters, W., Miller, J. B., Whitaker, J., Denning, A. S., Hirsch, A., Krol, M.
C., Zupanski, D., Bruhwiler, L., and Tans, P. P.: An ensemble data
assimilation system to estimate CO2 surface fluxes from atmospheric
trace gas observations, J. Geophys. Res., 110, D24304,
https://doi.org/10.1029/2005JD006157, 2005.
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway,
T. J., Masarie, K., Miller, J. B., Bruhwiler, L. M. P., Petron, G.,
Hirsch, A. I., Worthy, D. E. J., van der Werf, G. R., Randerson, J. T.,
Wennberg, P. O., Krol, M. C., and Tans, P. P.: An atmospheric
perspective on North American carbon dioxide exchange: CarbonTracker,
P. Natl. Acad Sci. USA, 104, 18925–18930, 2007.
Peylin, P., Rayner, P. J., Bousquet, P., Carouge, C., Hourdin, F., Heinrich,
P., Ciais, P., and AEROCARB contributors: Daily CO2 flux estimates over
Europe from continuous atmospheric measurements: 1, inverse methodology,
Atmos. Chem. Phys., 5, 3173–3186, https://doi.org/10.5194/acp-5-3173-2005, 2005.
Peylin, P., Law, R. M., Gurney, K. R., Chevallier, F., Jacobson, A. R., Maki,
T., Niwa, Y., Patra, P. K., Peters, W., Rayner, P. J., Rödenbeck, C., van
der Laan-Luijkx, I. T., and Zhang, X.: Global atmospheric carbon budget:
results from an ensemble of atmospheric CO2 inversions, Biogeosciences,
10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, 2013.
Rayner P. J. and O'Brien, D. M.: The utility of remotely sensed CO2
concentration data in surface source inversions, Geophys. Res. Lett., 28,
175–178, 2001.
Rigby, M., Manning, A. J., and Prinn, R. G.: Inversion of long-lived trace
gas emissions using combined Eulerian and Lagrangian chemical transport
models, Atmos. Chem. Phys., 11, 9887–9898, https://doi.org/10.5194/acp-11-9887-2011,
2011.
Rodgers, C. D.: Inverse methods for atmospheric sounding, Vol. 2 of Series on
Atmospheric, Oceanic and Planetary Physics, World Scientific, Singapore,
2000.
Rödenbeck, C., Houweling, S., Gloor, M., and Heimann, M.: CO2 flux
history 1982–2001 inferred from atmospheric data using a global inversion of
atmospheric transport, Atmos. Chem. Phys., 3, 1919–1964,
https://doi.org/10.5194/acp-3-1919-2003, 2003.
Rödenbeck, C., Gerbig, C., Trusilova, K., and Heimann, M.: A two-step
scheme for high-resolution regional atmospheric trace gas inversions based on
independent models, Atmos. Chem. Phys., 9, 5331–5342,
https://doi.org/10.5194/acp-9-5331-2009, 2009.
Saito, M., Ito, A., and Maksyutov, S.: Evaluation of biases in JRA-25/JCDAS
precipitation and their impact on the global terrestrial carbon balance, J.
Climate, 24, 4109–4125, 2011.
Saito, M., Ito, A., and Maksyutov, S.: Optimization of a prognostic biosphere
model for terrestrial biomass and atmospheric CO2 variability, Geosci.
Model Dev., 7, 1829–1840, https://doi.org/10.5194/gmd-7-1829-2014, 2014.
Saeki, T., Maksyutov, S., Sasakawa, M., Machida, T., Arshinov, M., Tans, P.,
Conway, T. J., Saito, M., Valsala, V., Oda, T., Andres, R. J., and Belikov,
D.: Carbon flux estimation for Siberia by inverse modeling constrained by
aircraft and tower CO2 measurements, J. Geophys. Res.-Atmos., 118,
https://doi.org/10.1002/jgrd.50127, 2013.
Sasakawa, M., Shimoyama, K., Machida, T., Tsuda, N., Suto, H., Arshinov, M.,
Davydov, D., Fofonov, A., Krasnov, O., Saeki, T., Koyama, Y., and Maksyutov,
S.: Continuous measurements of methane from a tower network over Siberia,
Tellus 62B, 403–416, 2010.
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical
note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos.
Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005.
Stohl, A., Seibert, P., Arduini, J., Eckhardt, S., Fraser, P., Greally, B.
R., Lunder, C., Maione, M., Mühle, J., O'Doherty, S., Prinn, R. G.,
Reimann, S., Saito, T., Schmidbauer, N., Simmonds, P. G., Vollmer, M. K.,
Weiss, R. F., and Yokouchi, Y.: An analytical inversion method for
determining regional and global emissions of greenhouse gases: Sensitivity
studies and application to halocarbons, Atmos. Chem. Phys., 9, 1597–1620,
https://doi.org/10.5194/acp-9-1597-2009, 2009.
Takagi, H., Saeki, T., Oda, T., Saito, M., Valsala, V., Belikov, D., Saito,
R., Yoshida, Y., Morino, I., Uchino, O., Andres, R. J., Yokota, T., and
Maksyutov, S.: On the benefit of GOSAT observations to the estimation of
regional CO2 fluxes, SOLA, 7, 161–164, 2011.
Tans, P. P., Conway, T. J., and Nakazawa, T.: Latitudinal distribution of the
sources and sinks of atmospheric carbon dioxide derived from surface
observations and an atmospheric transport model, J. Geophys. Res., 94,
5151–5172, 1989.
Tarantola, A.: Inverse Problem Theory and Methods
for Model Parameter Estimation, Society for Industrial and Applied
Mathematics, Philadelphia, USA, 2005.
Thompson, R. L. and Stohl, A.: FLEXINVERT: an atmospheric Bayesian inversion
framework for determining surface fluxes of trace species using an optimized
grid, Geosci. Model Dev., 7, 2223–2242, https://doi.org/10.5194/gmd-7-2223-2014, 2014.
Tohjima, Y., Terao, Y., Mukai, H., Machida, T., Nojiri, Y., and Maksyutov,
S.: ENSO-related variability in latitudinal distribution of annual mean
atmospheric potential oxygen (APO) in the equatorial Western Pacific, Tellus
B, 67, 25869, https://doi.org/10.3402/tellusb.v67.25869, 2015.
Valsala V. and Maksyutov S.: Simulation and assimilation of global ocean
pCO2 and air-sea CO2 fluxes using ship observations of surface
ocean pCO2 in a simplified biogeochemical offline model, Tellus B, 62,
821–840, https://doi.org/10.1111/j.1600-0889.2010.00495.x, 2010.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Mu, M.,
Kasibhatla, P. S., Morton, D. C., DeFries, R. S., Jin, Y., and van Leeuwen,
T. T.: Global fire emissions and the contribution of deforestation, savanna,
forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10,
11707–11735, https://doi.org/10.5194/acp-10-11707-2010, 2010.
Wilson, C., Chipperfield, M. P., Gloor, M., and Chevallier, F.: Development
of a variational flux inversion system (INVICAT v1.0) using the TOMCAT
chemical transport model, Geosci. Model Dev., 7, 2485–2500,
https://doi.org/10.5194/gmd-7-2485-2014, 2014.
WDCGG: WMO World Data Centre for Greenhouse Gases, Japan Meteorological
Agency, Tokyo, available at:
http://ds.data.jma.go.jp/gmd/wdcgg/introduction.html (last access: 23 October 2015),
2015.
Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H., and
Maksyutov, S.: Global concentrations of CO2 and CH4 retrieved from
GOSAT: First preliminary results, SOLA, 5, 160–163,
https://doi.org/10.2151/sola.2009-041, 2009.