Articles | Volume 15, issue 5
https://doi.org/10.5194/acp-15-2903-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-2903-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
13 Mar 2015
Research article |
| 13 Mar 2015
Biases in atmospheric CO2 estimates from correlated meteorology modeling errors
Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
M. N. Hayek
Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
A. E. Andrews
Global Monitoring Division, Earth Systems Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
I. Fung
Department of Earth and Planetary Sciences, University of California Berkeley, Berkeley, CA, USA
Earth Science Division, Jet Propulsion Laboratory, NASA, Pasadena, CA, USA
Related authors
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot Miller, and Arvind Saibaba
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-90, https://doi.org/10.5194/gmd-2024-90, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
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.
Taewon Cho, Julianne Chung, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 15, 5547–5565, https://doi.org/10.5194/gmd-15-5547-2022, https://doi.org/10.5194/gmd-15-5547-2022, 2022
Short summary
Short summary
Atmospheric inverse modeling describes the process of estimating greenhouse gas fluxes or air pollution emissions at the Earth's surface using observations of these gases collected in the atmosphere. The launch of new satellites, the expansion of surface observation networks, and a desire for more detailed maps of surface fluxes have yielded numerous computational and statistical challenges. This article describes computationally efficient methods for large-scale atmospheric inverse modeling.
Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller
Geosci. Model Dev., 14, 4683–4696, https://doi.org/10.5194/gmd-14-4683-2021, https://doi.org/10.5194/gmd-14-4683-2021, 2021
Short summary
Short summary
Observations of greenhouse gases have become far more numerous in recent years due to new satellite observations. The sheer size of these datasets makes it challenging to incorporate these data into statistical models and use these data to estimate greenhouse gas sources and sinks. In this paper, we develop an approach to reduce the size of these datasets while preserving the most information possible. We subsequently test this approach using satellite observations of carbon dioxide.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Scot M. Miller, Arvind K. Saibaba, Michael E. Trudeau, Marikate E. Mountain, and Arlyn E. Andrews
Geosci. Model Dev., 13, 1771–1785, https://doi.org/10.5194/gmd-13-1771-2020, https://doi.org/10.5194/gmd-13-1771-2020, 2020
Short summary
Short summary
New observations of greenhouse gases from satellites and aircraft provide an unprecedented window into global carbon sources and sinks. However, these new datasets also present enormous computational challenges due to the sheer number of observations. In this article, we discuss the challenges of estimating greenhouse gas source and sinks using very large atmospheric datasets and evaluate several strategies for overcoming these challenges.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 20, 323–331, https://doi.org/10.5194/acp-20-323-2020, https://doi.org/10.5194/acp-20-323-2020, 2020
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere. The satellite measures radiation, and these measurements are then converted to an estimate of atmospheric CO2. This conversion or retrieval algorithm has improved markedly since the satellite launch. We find that these improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance.
Scot M. Miller, Anna M. Michalak, Vineet Yadav, and Jovan M. Tadić
Atmos. Chem. Phys., 18, 6785–6799, https://doi.org/10.5194/acp-18-6785-2018, https://doi.org/10.5194/acp-18-6785-2018, 2018
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere globally. We evaluate the extent to which current OCO-2 observations can inform scientific understanding of the biospheric carbon balance. We find that current observations are best-equipped to constrain the biospheric carbon balance across continental or hemispheric regions and provide limited information on smaller regions.
Nils Hase, Scot M. Miller, Peter Maaß, Justus Notholt, Mathias Palm, and Thorsten Warneke
Geosci. Model Dev., 10, 3695–3713, https://doi.org/10.5194/gmd-10-3695-2017, https://doi.org/10.5194/gmd-10-3695-2017, 2017
Short summary
Short summary
Inverse modeling uses atmospheric measurements to estimate emissions of greenhouse gases, which are key to understand the climate system. However, the measurement information alone is typically insufficient to provide reasonable emission estimates. Additional information is required. This article applies modern mathematical inversion techniques to formulate such additional knowledge. It is a prime example of how such tools can improve the quality of estimates compared to commonly used methods.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 17, 3963–3985, https://doi.org/10.5194/acp-17-3963-2017, https://doi.org/10.5194/acp-17-3963-2017, 2017
Short summary
Short summary
We reviewed recent efforts to estimate state- and national-scale carbon dioxide and methane emissions from individual anthropogenic source sectors in the United States. State and federal greenhouse gas regulations almost always target reductions from specific source sectors, and reliable emission estimates are important to support and evaluate these policies. We also describe a number of forward-looking opportunities that would improve sector-specific estimates.
Jovan M. Tadić, Xuemei Qiu, Scot Miller, and Anna M. Michalak
Geosci. Model Dev., 10, 709–720, https://doi.org/10.5194/gmd-10-709-2017, https://doi.org/10.5194/gmd-10-709-2017, 2017
Short summary
Short summary
We developed a new method to create contiguous maps from sparse and/or noisy satellite observations. This approach could be used to produce retroactive or real-time estimates of environmental data observed by satellites which exhibit spatio-temporal autocorrelations. The method could be applied in a standalone mode or as part of a broader satellite data processing package. Maps produced in this way could then be incorporated into physical and biogeochemical models of the Earth system.
Scot M. Miller, Roisin Commane, Joe R. Melton, Arlyn E. Andrews, Joshua Benmergui, Edward J. Dlugokencky, Greet Janssens-Maenhout, Anna M. Michalak, Colm Sweeney, and Doug E. J. Worthy
Biogeosciences, 13, 1329–1339, https://doi.org/10.5194/bg-13-1329-2016, https://doi.org/10.5194/bg-13-1329-2016, 2016
Short summary
Short summary
We use atmospheric data from the US and Canada to examine seven wetland methane flux estimates. Relative to existing estimates, we find a methane source that is smaller in magnitude with a broader seasonal cycle. Furthermore, we estimate the largest fluxes over the Hudson Bay Lowlands, a spatial distribution that differs from commonly used remote sensing estimates of wetland location.
S. M. Miller, A. M. Michalak, and P. J. Levi
Geosci. Model Dev., 7, 303–315, https://doi.org/10.5194/gmd-7-303-2014, https://doi.org/10.5194/gmd-7-303-2014, 2014
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-519, https://doi.org/10.5194/essd-2024-519, 2024
Preprint under review for ESSD
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Michael Stanley, Mikael Kuusela, Brendan Byrne, and Junjie Liu
Atmos. Chem. Phys., 24, 9419–9433, https://doi.org/10.5194/acp-24-9419-2024, https://doi.org/10.5194/acp-24-9419-2024, 2024
Short summary
Short summary
To serve the uncertainty quantification (UQ) needs of 4D-Var data assimilation (DA) practitioners, we describe and justify a UQ algorithm from carbon flux inversion and incorporate its sampling uncertainty into the final reported UQ. The algorithm is mathematically proved, and its performance is shown for a carbon flux observing system simulation experiment. These results legitimize and generalize this algorithm's current use and make available this effective algorithm to new DA domains.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-103, https://doi.org/10.5194/essd-2024-103, 2024
Revised manuscript under review for ESSD
Short summary
Short summary
This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three main GHG fluxes at the national level. Compared to the previous study, new satellite-based CO2 inversions were included. Additionally, an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot Miller, and Arvind Saibaba
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-90, https://doi.org/10.5194/gmd-2024-90, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
Jonathan Hobbs, Matthias Katzfuss, Hai Nguyen, Vineet Yadav, and Junjie Liu
Geosci. Model Dev., 17, 1133–1151, https://doi.org/10.5194/gmd-17-1133-2024, https://doi.org/10.5194/gmd-17-1133-2024, 2024
Short summary
Short summary
The cycling of carbon among the land, oceans, and atmosphere is a closely monitored process in the global climate system. These exchanges between the atmosphere and the surface can be quantified using a combination of atmospheric carbon dioxide observations and computer models. This study presents a statistical method for investigating the similarities and differences in the estimated surface–atmosphere carbon exchange when different computer model assumptions are invoked.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
Short summary
Short summary
To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca Baier, and Luciana V. Gatti
EGUsphere, https://doi.org/10.5194/egusphere-2023-2258, https://doi.org/10.5194/egusphere-2023-2258, 2023
Short summary
Short summary
Multi-inverse modeling inter-comparison projects offer a chance to assess uncertainties in inversion estimates arising from various sources. This study proposes a method to quantify errors of regional terrestrial biosphere CO2 flux estimates from an inverse model ensemble by using airborne CO2 measurements. Our observation-based error estimates exceed the ensemble spread of flux estimates in regions with high anthropogenic emission regions, suggesting systematic biases in inversion estimates.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
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.
Lei Hu, Deborah Ottinger, Stephanie Bogle, Stephen A. Montzka, Philip L. DeCola, Ed Dlugokencky, Arlyn Andrews, Kirk Thoning, Colm Sweeney, Geoff Dutton, Lauren Aepli, and Andrew Crotwell
Atmos. Chem. Phys., 23, 1437–1448, https://doi.org/10.5194/acp-23-1437-2023, https://doi.org/10.5194/acp-23-1437-2023, 2023
Short summary
Short summary
Effective mitigation of greenhouse gas (GHG) emissions relies on an accurate understanding of emissions. Here we demonstrate the added value of using inventory- and atmosphere-based approaches for estimating US emissions of SF6, the most potent GHG known. The results suggest a large decline in US SF6 emissions, shed light on the possible processes causing the differences between the independent estimates, and identify opportunities for substantial additional emission reductions.
Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
Short summary
Short summary
Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
Short summary
Short summary
Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Taewon Cho, Julianne Chung, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 15, 5547–5565, https://doi.org/10.5194/gmd-15-5547-2022, https://doi.org/10.5194/gmd-15-5547-2022, 2022
Short summary
Short summary
Atmospheric inverse modeling describes the process of estimating greenhouse gas fluxes or air pollution emissions at the Earth's surface using observations of these gases collected in the atmosphere. The launch of new satellites, the expansion of surface observation networks, and a desire for more detailed maps of surface fluxes have yielded numerous computational and statistical challenges. This article describes computationally efficient methods for large-scale atmospheric inverse modeling.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Francesco N. Tubiello, Kevin Karl, Alessandro Flammini, Johannes Gütschow, Griffiths Obli-Laryea, Giulia Conchedda, Xueyao Pan, Sally Yue Qi, Hörn Halldórudóttir Heiðarsdóttir, Nathan Wanner, Roberta Quadrelli, Leonardo Rocha Souza, Philippe Benoit, Matthew Hayek, David Sandalow, Erik Mencos Contreras, Cynthia Rosenzweig, Jose Rosero Moncayo, Piero Conforti, and Maximo Torero
Earth Syst. Sci. Data, 14, 1795–1809, https://doi.org/10.5194/essd-14-1795-2022, https://doi.org/10.5194/essd-14-1795-2022, 2022
Short summary
Short summary
The paper presents results from the new FAOSTAT database on food system emissions, covering all countries over the time series 1990–2019. Results indicate and further clarify – updated to 2019 – the relevance of emissions from crop and livestock production processes within the farm gate; from conversion of natural ecosystems to agriculture, such as deforestation and peat degradation; and from use of fossil fuels for energy and other industrial processes along food supply chains.
Hélène Peiro, Sean Crowell, Andrew Schuh, David F. Baker, Chris O'Dell, Andrew R. Jacobson, Frédéric Chevallier, Junjie Liu, Annmarie Eldering, David Crisp, Feng Deng, Brad Weir, Sourish Basu, Matthew S. Johnson, Sajeev Philip, and Ian Baker
Atmos. Chem. Phys., 22, 1097–1130, https://doi.org/10.5194/acp-22-1097-2022, https://doi.org/10.5194/acp-22-1097-2022, 2022
Short summary
Short summary
Satellite CO2 observations are constantly improved. We study an ensemble of different atmospheric models (inversions) from 2015 to 2018 using separate ground-based data or two versions of the OCO-2 satellite. Our study aims to determine if different satellite data corrections can yield different estimates of carbon cycle flux. A difference in the carbon budget between the two versions is found over tropical Africa, which seems to show the impact of corrections applied in satellite data.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
Short summary
Short summary
We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Bharat Rastogi, John B. Miller, Micheal Trudeau, Arlyn E. Andrews, Lei Hu, Marikate Mountain, Thomas Nehrkorn, Bianca Baier, Kathryn McKain, John Mund, Kaiyu Guan, and Caroline B. Alden
Atmos. Chem. Phys., 21, 14385–14401, https://doi.org/10.5194/acp-21-14385-2021, https://doi.org/10.5194/acp-21-14385-2021, 2021
Short summary
Short summary
Predicting Earth's climate is difficult, partly due to uncertainty in forecasting how much CO2 can be removed by oceans and plants, because we cannot measure these exchanges directly on large scales. Satellites such as NASA's OCO-2 can provide part of the needed information, but data need to be highly precise and accurate. We evaluate these data and find small biases in certain months that are similar to the signals of interest. We argue that continued improvement of these data is necessary.
Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller
Geosci. Model Dev., 14, 4683–4696, https://doi.org/10.5194/gmd-14-4683-2021, https://doi.org/10.5194/gmd-14-4683-2021, 2021
Short summary
Short summary
Observations of greenhouse gases have become far more numerous in recent years due to new satellite observations. The sheer size of these datasets makes it challenging to incorporate these data into statistical models and use these data to estimate greenhouse gas sources and sinks. In this paper, we develop an approach to reduce the size of these datasets while preserving the most information possible. We subsequently test this approach using satellite observations of carbon dioxide.
Elizabeth B. Wiggins, Arlyn Andrews, Colm Sweeney, John B. Miller, Charles E. Miller, Sander Veraverbeke, Roisin Commane, Steven Wofsy, John M. Henderson, and James T. Randerson
Atmos. Chem. Phys., 21, 8557–8574, https://doi.org/10.5194/acp-21-8557-2021, https://doi.org/10.5194/acp-21-8557-2021, 2021
Short summary
Short summary
We analyzed high-resolution trace gas measurements collected from a tower in Alaska during a very active fire season to improve our understanding of trace gas emissions from boreal forest fires. Our results suggest previous studies may have underestimated emissions from smoldering combustion in boreal forest fires.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
Short summary
Short summary
We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
Short summary
Short summary
On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
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.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
Short summary
Short summary
We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Yonghong Yi, John S. Kimball, Jennifer D. Watts, Susan M. Natali, Donatella Zona, Junjie Liu, Masahito Ueyama, Hideki Kobayashi, Walter Oechel, and Charles E. Miller
Biogeosciences, 17, 5861–5882, https://doi.org/10.5194/bg-17-5861-2020, https://doi.org/10.5194/bg-17-5861-2020, 2020
Short summary
Short summary
We developed a 1 km satellite-data-driven permafrost carbon model to evaluate soil respiration sensitivity to recent snow cover changes in Alaska. Results show earlier snowmelt enhances growing-season soil respiration and reduces annual carbon uptake, while early cold-season soil respiration is linked to the number of snow-free days after the land surface freezes. Our results also show nonnegligible influences of subgrid variability in surface conditions on model-simulated CO2 seasonal cycles.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
Short summary
Short summary
Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
Scot M. Miller, Arvind K. Saibaba, Michael E. Trudeau, Marikate E. Mountain, and Arlyn E. Andrews
Geosci. Model Dev., 13, 1771–1785, https://doi.org/10.5194/gmd-13-1771-2020, https://doi.org/10.5194/gmd-13-1771-2020, 2020
Short summary
Short summary
New observations of greenhouse gases from satellites and aircraft provide an unprecedented window into global carbon sources and sinks. However, these new datasets also present enormous computational challenges due to the sheer number of observations. In this article, we discuss the challenges of estimating greenhouse gas source and sinks using very large atmospheric datasets and evaluate several strategies for overcoming these challenges.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 20, 323–331, https://doi.org/10.5194/acp-20-323-2020, https://doi.org/10.5194/acp-20-323-2020, 2020
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere. The satellite measures radiation, and these measurements are then converted to an estimate of atmospheric CO2. This conversion or retrieval algorithm has improved markedly since the satellite launch. We find that these improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance.
Sajeev Philip, Matthew S. Johnson, Christopher Potter, Vanessa Genovesse, David F. Baker, Katherine D. Haynes, Daven K. Henze, Junjie Liu, and Benjamin Poulter
Atmos. Chem. Phys., 19, 13267–13287, https://doi.org/10.5194/acp-19-13267-2019, https://doi.org/10.5194/acp-19-13267-2019, 2019
Short summary
Short summary
This research was conducted to quantify the impact of different prior global biosphere models on the estimate of terrestrial CO2 fluxes when assimilating Orbiting Carbon Observatory-2 (OCO-2) satellite observations. To determine the prior model impact, we apply observing system simulation experiments (OSSEs). Even with the substantial spatiotemporal coverage of OCO-2 data, residual differences in posterior CO2 flux estimates remain due to the choice of prior flux mean and uncertainties.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
Publication in AMT not foreseen
Short summary
Short summary
This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, https://doi.org/10.5194/gmd-12-4347-2019, 2019
Short summary
Short summary
The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
Short summary
Short summary
Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Alexandra G. Konings, A. Anthony Bloom, Junjie Liu, Nicholas C. Parazoo, David S. Schimel, and Kevin W. Bowman
Biogeosciences, 16, 2269–2284, https://doi.org/10.5194/bg-16-2269-2019, https://doi.org/10.5194/bg-16-2269-2019, 2019
Short summary
Short summary
We estimate heterotrophic respiration (Rh) – the respiration from microbes in the soil – using satellite estimates of the net carbon flux and other quantities. Rh is an important carbon flux but is rarely studied by itself. Our method is the first to estimate how Rh varies in both space and time. The resulting new estimate of Rh is compared to the best currently available alternative, which is based on interpolating field measurements globally. The two estimates disagree and are both uncertain.
Anna Karion, Thomas Lauvaux, Israel Lopez Coto, Colm Sweeney, Kimberly Mueller, Sharon Gourdji, Wayne Angevine, Zachary Barkley, Aijun Deng, Arlyn Andrews, Ariel Stein, and James Whetstone
Atmos. Chem. Phys., 19, 2561–2576, https://doi.org/10.5194/acp-19-2561-2019, https://doi.org/10.5194/acp-19-2561-2019, 2019
Short summary
Short summary
In this study, we use atmospheric methane concentration observations collected during an airborne campaign to compare different model-based emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We find that the tracer dispersion model has a significant impact on the results because the models differ in their simulation of vertical dispersion. Additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models.
Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman, and Kenneth J. Davis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-342, https://doi.org/10.5194/gmd-2018-342, 2019
Revised manuscript not accepted
Short summary
Short summary
This paper describes a mass-conserving framework for computing time-varying lateral boundary conditions from global model carbon dioxide concentrations for introduction into the WRF-Chem regional model. The goal is to create a laboratory environment in which carbon dioxide transport uncertainties may be explored separately from inversion-derived flux uncertainties. The software is currently available on GitHub at https://github.com/psu-inversion/WRF_Boundary_Coupling.
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.
Wei He, Ivar R. van der Velde, Arlyn E. Andrews, Colm Sweeney, John Miller, Pieter Tans, Ingrid T. van der Laan-Luijkx, Thomas Nehrkorn, Marikate Mountain, Weimin Ju, Wouter Peters, and Huilin Chen
Geosci. Model Dev., 11, 3515–3536, https://doi.org/10.5194/gmd-11-3515-2018, https://doi.org/10.5194/gmd-11-3515-2018, 2018
Short summary
Short summary
We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system. This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions. The CTDAS-Lagrange system can be easily extended to assimilate an additional tracer, e.g., carbonyl sulfide (COS or OCS), for regional estimates of both net and gross carbon fluxes.
Matthew N. Hayek, Marcos Longo, Jin Wu, Marielle N. Smith, Natalia Restrepo-Coupe, Raphael Tapajós, Rodrigo da Silva, David R. Fitzjarrald, Plinio B. Camargo, Lucy R. Hutyra, Luciana F. Alves, Bruce Daube, J. William Munger, Kenia T. Wiedemann, Scott R. Saleska, and Steven C. Wofsy
Biogeosciences, 15, 4833–4848, https://doi.org/10.5194/bg-15-4833-2018, https://doi.org/10.5194/bg-15-4833-2018, 2018
Short summary
Short summary
We investigated the roles that weather and forest disturbances like drought play in shaping changes in ecosystem photosynthesis and carbon exchange in an Amazon forest. We discovered that weather largely influenced differences between years, but a prior drought, which occurred 3 years before measurements started, likely hampered photosynthesis in the first year. This is the first atmospheric evidence that drought can have legacy impacts on Amazon forest photosynthesis.
Sourish Basu, David F. Baker, Frédéric Chevallier, Prabir K. Patra, Junjie Liu, and John B. Miller
Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, https://doi.org/10.5194/acp-18-7189-2018, 2018
Short summary
Short summary
CO2 measurements from the global surface network and CO2 estimates from satellites such as the Orbiting Carbon Observatory 2 (OCO-2) are currently used to quantify the surface sources and sinks of CO2, using what we know about atmospheric transport of gases. In this work, we quantify the uncertainties in those surface source/sink estimates that stem from errors in our atmospheric transport models, using an observing system simulation experiment (OSSE).
Scot M. Miller, Anna M. Michalak, Vineet Yadav, and Jovan M. Tadić
Atmos. Chem. Phys., 18, 6785–6799, https://doi.org/10.5194/acp-18-6785-2018, https://doi.org/10.5194/acp-18-6785-2018, 2018
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere globally. We evaluate the extent to which current OCO-2 observations can inform scientific understanding of the biospheric carbon balance. We find that current observations are best-equipped to constrain the biospheric carbon balance across continental or hemispheric regions and provide limited information on smaller regions.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Melissa P. Sulprizio, A. Anthony Bloom, Arlyn E. Andrews, and Debra Wunch
Atmos. Chem. Phys., 18, 6483–6491, https://doi.org/10.5194/acp-18-6483-2018, https://doi.org/10.5194/acp-18-6483-2018, 2018
Short summary
Short summary
We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US to estimate methane emissions in that region. Our results suggest that the EPA inventory is regionally unbiased but there are large local biases, suggesting variable emission factors. Our results also suggest that the choice of landcover map is the dominant source of error for wetland emission estimates.
Xin Lan, Pieter Tans, Colm Sweeney, Arlyn Andrews, Andrew Jacobson, Molly Crotwell, Edward Dlugokencky, Jonathan Kofler, Patricia Lang, Kirk Thoning, and Sonja Wolter
Atmos. Chem. Phys., 17, 15151–15165, https://doi.org/10.5194/acp-17-15151-2017, https://doi.org/10.5194/acp-17-15151-2017, 2017
Short summary
Short summary
We analyze spatial patterns of column CO2 over North America using well-calibrated aircraft and tall tower measurements. We find that the long-term averaged spatial gradients of column CO2 across North America show a smooth pattern that mainly reflects the large-scale circulation. Our results can serve as a good reference for evaluating current and future column CO2 retrievals from both ground and satellite platforms.
Nils Hase, Scot M. Miller, Peter Maaß, Justus Notholt, Mathias Palm, and Thorsten Warneke
Geosci. Model Dev., 10, 3695–3713, https://doi.org/10.5194/gmd-10-3695-2017, https://doi.org/10.5194/gmd-10-3695-2017, 2017
Short summary
Short summary
Inverse modeling uses atmospheric measurements to estimate emissions of greenhouse gases, which are key to understand the climate system. However, the measurement information alone is typically insufficient to provide reasonable emission estimates. Additional information is required. This article applies modern mathematical inversion techniques to formulate such additional knowledge. It is a prime example of how such tools can improve the quality of estimates compared to commonly used methods.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 17, 3963–3985, https://doi.org/10.5194/acp-17-3963-2017, https://doi.org/10.5194/acp-17-3963-2017, 2017
Short summary
Short summary
We reviewed recent efforts to estimate state- and national-scale carbon dioxide and methane emissions from individual anthropogenic source sectors in the United States. State and federal greenhouse gas regulations almost always target reductions from specific source sectors, and reliable emission estimates are important to support and evaluate these policies. We also describe a number of forward-looking opportunities that would improve sector-specific estimates.
Jovan M. Tadić, Xuemei Qiu, Scot Miller, and Anna M. Michalak
Geosci. Model Dev., 10, 709–720, https://doi.org/10.5194/gmd-10-709-2017, https://doi.org/10.5194/gmd-10-709-2017, 2017
Short summary
Short summary
We developed a new method to create contiguous maps from sparse and/or noisy satellite observations. This approach could be used to produce retroactive or real-time estimates of environmental data observed by satellites which exhibit spatio-temporal autocorrelations. The method could be applied in a standalone mode or as part of a broader satellite data processing package. Maps produced in this way could then be incorporated into physical and biogeochemical models of the Earth system.
Congsheng Fu, Xuhui Lee, Timothy J. Griffis, Edward J. Dlugokencky, and Arlyn E. Andrews
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-761, https://doi.org/10.5194/acp-2016-761, 2016
Revised manuscript not accepted
Short summary
Short summary
To the best of our knowledge, no modeling studies have been published on the relationship between the spatial characteristics of agricultural N2O emissions and the atmospheric N2O mixing ratio at the regional scale. To fill this gap, we proposed a simple inverse analysis method based on tower measurements and an Eulerian model. According to our study, the N2O emissions from the U. S. Corn Belt is clearly estimated by IPCC, and such underestimate is not dependent on tower measurement location.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
Short summary
Short summary
In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Joshua B. Fisher, Munish Sikka, Deborah N. Huntzinger, Christopher Schwalm, and Junjie Liu
Biogeosciences, 13, 4271–4277, https://doi.org/10.5194/bg-13-4271-2016, https://doi.org/10.5194/bg-13-4271-2016, 2016
Short summary
Short summary
Atmospheric models of CO2 require estimates of land CO2 fluxes at relatively high temporal resolutions because of the high rate of atmospheric mixing and wind heterogeneity. However, land CO2 fluxes are often provided at monthly time steps. Here, we describe a new dataset created from 15 global land models and 4 combined products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), which we have converted from monthly to 3-hourly output.
Anna Karion, Colm Sweeney, John B. Miller, Arlyn E. Andrews, Roisin Commane, Steven Dinardo, John M. Henderson, Jacob Lindaas, John C. Lin, Kristina A. Luus, Tim Newberger, Pieter Tans, Steven C. Wofsy, Sonja Wolter, and Charles E. Miller
Atmos. Chem. Phys., 16, 5383–5398, https://doi.org/10.5194/acp-16-5383-2016, https://doi.org/10.5194/acp-16-5383-2016, 2016
Short summary
Short summary
Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Here we use carbon dioxide and methane measurements from a tower near Fairbanks AK to investigate regional Alaskan fluxes of CO2 and CH4 for 2012–2014.
Scot M. Miller, Roisin Commane, Joe R. Melton, Arlyn E. Andrews, Joshua Benmergui, Edward J. Dlugokencky, Greet Janssens-Maenhout, Anna M. Michalak, Colm Sweeney, and Doug E. J. Worthy
Biogeosciences, 13, 1329–1339, https://doi.org/10.5194/bg-13-1329-2016, https://doi.org/10.5194/bg-13-1329-2016, 2016
Short summary
Short summary
We use atmospheric data from the US and Canada to examine seven wetland methane flux estimates. Relative to existing estimates, we find a methane source that is smaller in magnitude with a broader seasonal cycle. Furthermore, we estimate the largest fluxes over the Hudson Bay Lowlands, a spatial distribution that differs from commonly used remote sensing estimates of wetland location.
J. R. Worden, A. J. Turner, A. Bloom, S. S. Kulawik, J. Liu, M. Lee, R. Weidner, K. Bowman, C. Frankenberg, R. Parker, and V. H. Payne
Atmos. Meas. Tech., 8, 3433–3445, https://doi.org/10.5194/amt-8-3433-2015, https://doi.org/10.5194/amt-8-3433-2015, 2015
Short summary
Short summary
Here we demonstrate the potential for estimating lower tropospheric CH4 concentrations through the combination of free-tropospheric methane measurements from the Aura Tropospheric Emission Spectrometer (TES) and XCH4 (dry-mole air fraction of methane) from the Greenhouse Gases Observing Satellite - Thermal And Near-infrared for carbon Observation (GOSAT TANSO).
A. J. Turner, D. J. Jacob, K. J. Wecht, J. D. Maasakkers, E. Lundgren, A. E. Andrews, S. C. Biraud, H. Boesch, K. W. Bowman, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, A. Kuze, J. Notholt, H. Ohyama, R. Parker, V. H. Payne, R. Sussmann, C. Sweeney, V. A. Velazco, T. Warneke, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 15, 7049–7069, https://doi.org/10.5194/acp-15-7049-2015, https://doi.org/10.5194/acp-15-7049-2015, 2015
L. Bruhwiler, E. Dlugokencky, K. Masarie, M. Ishizawa, A. Andrews, J. Miller, C. Sweeney, P. Tans, and D. Worthy
Atmos. Chem. Phys., 14, 8269–8293, https://doi.org/10.5194/acp-14-8269-2014, https://doi.org/10.5194/acp-14-8269-2014, 2014
G. W. Santoni, B. C. Daube, E. A. Kort, R. Jiménez, S. Park, J. V. Pittman, E. Gottlieb, B. Xiang, M. S. Zahniser, D. D. Nelson, J. B. McManus, J. Peischl, T. B. Ryerson, J. S. Holloway, A. E. Andrews, C. Sweeney, B. Hall, E. J. Hintsa, F. L. Moore, J. W. Elkins, D. F. Hurst, B. B. Stephens, J. Bent, and S. C. Wofsy
Atmos. Meas. Tech., 7, 1509–1526, https://doi.org/10.5194/amt-7-1509-2014, https://doi.org/10.5194/amt-7-1509-2014, 2014
A. E. Andrews, J. D. Kofler, M. E. Trudeau, J. C. Williams, D. H. Neff, K. A. Masarie, D. Y. Chao, D. R. Kitzis, P. C. Novelli, C. L. Zhao, E. J. Dlugokencky, P. M. Lang, M. J. Crotwell, M. L. Fischer, M. J. Parker, J. T. Lee, D. D. Baumann, A. R. Desai, C. O. Stanier, S. F. J. De Wekker, D. E. Wolfe, J. W. Munger, and P. P. Tans
Atmos. Meas. Tech., 7, 647–687, https://doi.org/10.5194/amt-7-647-2014, https://doi.org/10.5194/amt-7-647-2014, 2014
S. M. Miller, A. M. Michalak, and P. J. Levi
Geosci. Model Dev., 7, 303–315, https://doi.org/10.5194/gmd-7-303-2014, https://doi.org/10.5194/gmd-7-303-2014, 2014
B. W. LaFranchi, G. Pétron, J. B. Miller, S. J. Lehman, A. E. Andrews, E. J. Dlugokencky, B. Hall, B. R. Miller, S. A. Montzka, W. Neff, P. C. Novelli, C. Sweeney, J. C. Turnbull, D. E. Wolfe, P. P. Tans, K. R. Gurney, and T. P. Guilderson
Atmos. Chem. Phys., 13, 11101–11120, https://doi.org/10.5194/acp-13-11101-2013, https://doi.org/10.5194/acp-13-11101-2013, 2013
M. Inoue, I. Morino, O. Uchino, Y. Miyamoto, Y. Yoshida, T. Yokota, T. Machida, Y. Sawa, H. Matsueda, C. Sweeney, P. P. Tans, A. E. Andrews, S. C. Biraud, T. Tanaka, S. Kawakami, and P. K. Patra
Atmos. Chem. Phys., 13, 9771–9788, https://doi.org/10.5194/acp-13-9771-2013, https://doi.org/10.5194/acp-13-9771-2013, 2013
S. Basu, S. Guerlet, A. Butz, S. Houweling, O. Hasekamp, I. Aben, P. Krummel, P. Steele, R. Langenfelds, M. Torn, S. Biraud, B. Stephens, A. Andrews, and D. Worthy
Atmos. Chem. Phys., 13, 8695–8717, https://doi.org/10.5194/acp-13-8695-2013, https://doi.org/10.5194/acp-13-8695-2013, 2013
Y. Miyamoto, M. Inoue, I. Morino, O. Uchino, T. Yokota, T. Machida, Y. Sawa, H. Matsueda, C. Sweeney, P. P. Tans, A. E. Andrews, and P. K. Patra
Atmos. Chem. Phys., 13, 5265–5275, https://doi.org/10.5194/acp-13-5265-2013, https://doi.org/10.5194/acp-13-5265-2013, 2013
A. Karion, C. Sweeney, S. Wolter, T. Newberger, H. Chen, A. Andrews, J. Kofler, D. Neff, and P. Tans
Atmos. Meas. Tech., 6, 511–526, https://doi.org/10.5194/amt-6-511-2013, https://doi.org/10.5194/amt-6-511-2013, 2013
Related subject area
Subject: Biosphere Interactions | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Why do inverse models disagree? A case study with two European CO2 inversions
Net ecosystem exchange (NEE) estimates 2006–2019 over Europe from a pre-operational ensemble-inversion system
Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models
Distinguishing the impacts of natural and anthropogenic aerosols on global gross primary productivity through diffuse fertilization effect
Was Australia a sink or source of CO2 in 2015? Data assimilation using OCO-2 satellite measurements
CO2-equivalence metrics for surface albedo change based on the radiative forcing concept: a critical review
Effects of aerosol dynamics and gas–particle conversion on dry deposition of inorganic reactive nitrogen in a temperate forest
Ozone–vegetation feedback through dry deposition and isoprene emissions in a global chemistry–carbon–climate model
Pathway dependence of ecosystem responses in China to 1.5 °C global warming
A model-based analysis of foliar NOx deposition
Quantifying the UK's carbon dioxide flux: an atmospheric inverse modelling approach using a regional measurement network
Prediction of photosynthesis in Scots pine ecosystems across Europe by a needle-level theory
Technical note: How are NH3 dry deposition estimates affected by combining the LOTOS-EUROS model with IASI-NH3 satellite observations?
Isoprene and monoterpene emissions in south-east Australia: comparison of a multi-layer canopy model with MEGAN and with atmospheric observations
Particulate matter air pollution may offset ozone damage to global crop production
Sensitivity of stomatal conductance to soil moisture: implications for tropospheric ozone
The influence of idealized surface heterogeneity on virtual turbulent flux measurements
Technical Note: Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: methodology and system evaluation
Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: quantification of the European terrestrial CO2 fluxes
Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks
Future inhibition of ecosystem productivity by increasing wildfire pollution over boreal North America
Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook
Modeling soil organic carbon dynamics and their driving factors in the main global cereal cropping systems
A wedge strategy for mitigation of urban warming in future climate scenarios
The boundary condition for vertical velocity and its interdependence with surface gas exchange
Pan-Eurasian Experiment (PEEX): towards a holistic understanding of the feedbacks and interactions in the land–atmosphere–ocean–society continuum in the northern Eurasian region
Greenhouse gas simulations with a coupled meteorological and transport model: the predictability of CO2
Increasing summer net CO2 uptake in high northern ecosystems inferred from atmospheric inversions and comparisons to remote-sensing NDVI
A study of the influence of forest gaps on fire–atmosphere interactions
Stratospheric sulfate geoengineering could enhance the terrestrial photosynthesis rate
Distinguishing the drivers of trends in land carbon fluxes and plant volatile emissions over the past 3 decades
Granger causality from changes in level of atmospheric CO2 to global surface temperature and the El Niño–Southern Oscillation, and a candidate mechanism in global photosynthesis
MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe
Stably stratified canopy flow in complex terrain
Fire emission heights in the climate system – Part 1: Global plume height patterns simulated by ECHAM6-HAM2
Fire emission heights in the climate system – Part 2: Impact on transport, black carbon concentrations and radiation
Reliable, robust and realistic: the three R's of next-generation land-surface modelling
Carbon balance of China constrained by CONTRAIL aircraft CO2 measurements
Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case
Sensitivity analysis of an updated bidirectional air–surface exchange model for elemental mercury vapor
Nitrous oxide emissions 1999 to 2009 from a global atmospheric inversion
Quantifying the constraint of biospheric process parameters by CO2 concentration and flux measurement networks through a carbon cycle data assimilation system
Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model
Present and future nitrogen deposition to national parks in the United States: critical load exceedances
Global mapping of maximum emission heights and resulting vertical profiles of wildfire emissions
Scorched Earth: how will changes in the strength of the vegetation sink to ozone deposition affect human health and ecosystems?
The effect of climate and climate change on ammonia emissions in Europe
Observing the continental-scale carbon balance: assessment of sampling complementarity and redundancy in a terrestrial assimilation system by means of quantitative network design
CO2 flux estimation errors associated with moist atmospheric processes
DO3SE modelling of soil moisture to determine ozone flux to forest trees
Saqr Munassar, Guillaume Monteil, Marko Scholze, Ute Karstens, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, and Christoph Gerbig
Atmos. Chem. Phys., 23, 2813–2828, https://doi.org/10.5194/acp-23-2813-2023, https://doi.org/10.5194/acp-23-2813-2023, 2023
Short summary
Short summary
Using different transport models results in large errors in optimized fluxes in the atmospheric inversions. Boundary conditions and inversion system configurations lead to a smaller but non-negligible impact. The findings highlight the importance to validate transport models for further developments but also to properly account for such errors in inverse modelling. This will help narrow the convergence of gas estimates reported in the scientific literature from different inversion frameworks.
Saqr Munassar, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, Michał Gałkowski, Sophia Walther, and Christoph Gerbig
Atmos. Chem. Phys., 22, 7875–7892, https://doi.org/10.5194/acp-22-7875-2022, https://doi.org/10.5194/acp-22-7875-2022, 2022
Short summary
Short summary
The results obtained from ensembles of inversions over 13 years show the largest spread in the a posteriori fluxes over the station set ensemble. Using different prior fluxes in the inversions led to a smaller impact. Drought occurrences in 2018 and 2019 affected CO2 fluxes as seen in net ecosystem exchange estimates. Our study highlights the importance of expanding the atmospheric site network across Europe to better constrain CO2 fluxes in inverse modelling.
Sally S.-C. Wang, Yun Qian, L. Ruby Leung, and Yang Zhang
Atmos. Chem. Phys., 22, 3445–3468, https://doi.org/10.5194/acp-22-3445-2022, https://doi.org/10.5194/acp-22-3445-2022, 2022
Short summary
Short summary
This study develops an interpretable machine learning (ML) model predicting monthly PM2.5 fire emission over the contiguous US at 0.25° resolution and compares the prediction skills of the ML and process-based models. The comparison facilitates attributions of model biases and better understanding of the strengths and uncertainties in the two types of models at regional scales, for informing future model development and their applications in fire emission projection.
Hao Zhou, Xu Yue, Yadong Lei, Chenguang Tian, Jun Zhu, Yimian Ma, Yang Cao, Xixi Yin, and Zhiding Zhang
Atmos. Chem. Phys., 22, 693–709, https://doi.org/10.5194/acp-22-693-2022, https://doi.org/10.5194/acp-22-693-2022, 2022
Short summary
Short summary
Aerosols enhance plant photosynthesis by increasing diffuse radiation. In this study, we found that the aerosol impacts are quite different for varied species. Scattering aerosols such as sulfate and organic carbon promote photosynthesis while absorbing aerosols such as black carbon have negative impacts. Earth system models should consider the impacts of cloud and aerosol species on terrestrial ecosystems so as to better predict carbon cycles under different emission scenarios.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 21, 17453–17494, https://doi.org/10.5194/acp-21-17453-2021, https://doi.org/10.5194/acp-21-17453-2021, 2021
Short summary
Short summary
Semi-arid ecosystems such as those in Australia are evolving and might play an essential role in the future of climate change. We use carbon dioxide concentrations derived from the OCO-2 satellite instrument and a regional transport model to understand if Australia was a carbon sink or source of CO2 in 2015. Our research's main findings suggest that Australia acted as a carbon sink of about −0.41 ± 0.08 petagrams of carbon in 2015, driven primarily by savanna and sparsely vegetated ecosystems.
Ryan M. Bright and Marianne T. Lund
Atmos. Chem. Phys., 21, 9887–9907, https://doi.org/10.5194/acp-21-9887-2021, https://doi.org/10.5194/acp-21-9887-2021, 2021
Short summary
Short summary
Humans affect the reflective properties (albedo) of Earth's surface and the amount of solar energy that it absorbs, in turn affecting climate. In recent years, a variety of climate metrics have been applied to characterize albedo perturbations in terms of their
CO2-equivalenteffects, despite the lack of scientific consensus surrounding the methods behind them. We review these metrics, evaluate their (de)merits, provide guidance for future application, and suggest avenues for future research.
Genki Katata, Kazuhide Matsuda, Atsuyuki Sorimachi, Mizuo Kajino, and Kentaro Takagi
Atmos. Chem. Phys., 20, 4933–4949, https://doi.org/10.5194/acp-20-4933-2020, https://doi.org/10.5194/acp-20-4933-2020, 2020
Short summary
Short summary
This work quantified the role of aerosol dynamics and gas–particle conversion processes in the dry deposition of inorganic reactive nitrogen using a new multilayer land surface model. It also revealed a potential impact of the above processes on improving the predictive accuracy of chemical transport models.
Cheng Gong, Yadong Lei, Yimian Ma, Xu Yue, and Hong Liao
Atmos. Chem. Phys., 20, 3841–3857, https://doi.org/10.5194/acp-20-3841-2020, https://doi.org/10.5194/acp-20-3841-2020, 2020
Short summary
Short summary
We evaluate ozone–vegetation feedback using a fully coupled chemistry–carbon–climate global model (ModelE2-YIBs). Ozone damage to photosynthesis, stomatal conductance, and isoprene emissions parameterized by different schemes and sensitivities is jointly considered. In general, surface ozone concentrations are increased due to ozone–vegetation interactions, especially over the regions with a high ambient ozone level such as the eastern US, eastern China, and western Europe.
Xu Yue, Hong Liao, Huijun Wang, Tianyi Zhang, Nadine Unger, Stephen Sitch, Zhaozhong Feng, and Jia Yang
Atmos. Chem. Phys., 20, 2353–2366, https://doi.org/10.5194/acp-20-2353-2020, https://doi.org/10.5194/acp-20-2353-2020, 2020
Short summary
Short summary
We explore ecosystem responses in China to 1.5 °C global warming under stabilized versus transient pathways. Remarkably, GPP shows 30 % higher enhancement in the stabilized than the transient pathway because of the lower ozone (smaller damages to photosynthesis) and fewer aerosols (higher light availability) in the former pathway. Our analyses suggest that an associated reduction of CO2 and pollution emissions brings more benefits to ecosystems in China via 1.5 °C global warming.
Erin R. Delaria and Ronald C. Cohen
Atmos. Chem. Phys., 20, 2123–2141, https://doi.org/10.5194/acp-20-2123-2020, https://doi.org/10.5194/acp-20-2123-2020, 2020
Short summary
Short summary
Uptake of nitrogen dioxide (NO2) through pores in the surfaces of leaves has been identified as a significant, but inadequately understood, loss process of atmospheric nitrogen oxides. We have constructed a simple model for examining the impact of NO2 foliar uptake on the atmospheric chemistry of nitrogen oxides. We show that an accurate representation in atmospheric models of the effects of weather and soil conditions on leaf NO2 uptake may be important for accurately predicting NO2 deposition.
Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
Atmos. Chem. Phys., 19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019, https://doi.org/10.5194/acp-19-4345-2019, 2019
Short summary
Short summary
Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
Pertti Hari, Steffen Noe, Sigrid Dengel, Jan Elbers, Bert Gielen, Veli-Matti Kerminen, Bart Kruijt, Liisa Kulmala, Anders Lindroth, Ivan Mammarella, Tuukka Petäjä, Guy Schurgers, Anni Vanhatalo, Markku Kulmala, and Jaana Bäck
Atmos. Chem. Phys., 18, 13321–13328, https://doi.org/10.5194/acp-18-13321-2018, https://doi.org/10.5194/acp-18-13321-2018, 2018
Short summary
Short summary
The development of eddy-covariance measurements of ecosystem CO2 fluxes began a new era in the field studies of photosynthesis. The interpretation of the very variable CO2 fluxes in evergreen forests has been problematic especially in seasonal transition times. We apply two theoretical needle-level equations and show they can predict photosynthetic CO2 flux between the atmosphere and Scots pine forests. This has strong implications for the interpretation of the global change and boreal forests.
Shelley C. van der Graaf, Enrico Dammers, Martijn Schaap, and Jan Willem Erisman
Atmos. Chem. Phys., 18, 13173–13196, https://doi.org/10.5194/acp-18-13173-2018, https://doi.org/10.5194/acp-18-13173-2018, 2018
Short summary
Short summary
A combination of NH3 satellite observations from IASI and the LOTOS-EUROS model is used to derive NH3 surface concentrations and dry deposition fluxes over Europe. The results were evaluated using surface measurements (EMEP, LML, MAN) and a sensitivity study. This is a first step in further integration of surface measurements, satellite observations and an atmospheric transport model to derive accurate NH3 surface concentrations and dry deposition fluxes on a large scale.
Kathryn M. Emmerson, Martin E. Cope, Ian E. Galbally, Sunhee Lee, and Peter F. Nelson
Atmos. Chem. Phys., 18, 7539–7556, https://doi.org/10.5194/acp-18-7539-2018, https://doi.org/10.5194/acp-18-7539-2018, 2018
Short summary
Short summary
We compare the CSIRO in-house biogenic emissions model (ABCGEM) with the Model of Emissions of Gases and Aerosols from Nature (MEGAN), for eucalypt-rich south-east Australia. Differences in emissions are not only due to the emission factors, but also how these emission factors are processed. ABCGEM assumes monoterpenes are not light dependent, whilst MEGAN does. Comparison with observations suggests that Australian monoterpenes may not be as light dependent as other vegetation globally.
Luke D. Schiferl and Colette L. Heald
Atmos. Chem. Phys., 18, 5953–5966, https://doi.org/10.5194/acp-18-5953-2018, https://doi.org/10.5194/acp-18-5953-2018, 2018
Short summary
Short summary
Global population growth and industrialization have contributed to poor air quality worldwide, and increasing population will put pressure on global food production. We therefore assess how air pollution may impact crop growth. Ozone has previously been shown to damage crops. We demonstrate that the impact of particles associated with enhanced light scattering promotes growth, offsetting much, if not all, ozone damage. This has implications for air quality management and global food security.
Alessandro Anav, Chiara Proietti, Laurent Menut, Stefano Carnicelli, Alessandra De Marco, and Elena Paoletti
Atmos. Chem. Phys., 18, 5747–5763, https://doi.org/10.5194/acp-18-5747-2018, https://doi.org/10.5194/acp-18-5747-2018, 2018
Short summary
Short summary
Soil moisture and water stress play a pivotal role in regulating stomatal behaviour of plants; however, the role of water availability is often neglected in atmospheric chemistry modelling studies.
We show how dry deposition significantly declines when soil moisture is used to regulate the stomatal opening, mainly in semi-arid environments. Despite the fact that dry deposition occurs from the top of canopy to ground level, it affects the concentration of gases remaining in the lower atmosphere.
Frederik De Roo and Matthias Mauder
Atmos. Chem. Phys., 18, 5059–5074, https://doi.org/10.5194/acp-18-5059-2018, https://doi.org/10.5194/acp-18-5059-2018, 2018
Short summary
Short summary
We investigate the mismatch between incoming energy and the turbulent flux of sensible heat at the Earth's surface and how surface heterogeneity affects this imbalance. To resolve the turbulent fluxes we employ large-eddy simulations. We study terrain with different heterogeneity lengths and quantify the contributions of advection by the mean flow and horizontal flux-divergence in the surface energy budget. We find that the latter contributions depend on the scale of the heterogeneity length.
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas Frank Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3027–3045, https://doi.org/10.5194/acp-18-3027-2018, https://doi.org/10.5194/acp-18-3027-2018, 2018
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas F. Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3047–3064, https://doi.org/10.5194/acp-18-3047-2018, https://doi.org/10.5194/acp-18-3047-2018, 2018
Sara C. Pryor, Ryan C. Sullivan, and Justin T. Schoof
Atmos. Chem. Phys., 17, 14457–14471, https://doi.org/10.5194/acp-17-14457-2017, https://doi.org/10.5194/acp-17-14457-2017, 2017
Short summary
Short summary
The air temperature and water vapor content are increasing globally due to the increased concentration of "heat-trapping" (greenhouse) gases. But not all regions are warming at the same rate. This analysis is designed to improve understanding of the causes of recent trends and year-to-year variability in summertime heat indices over the eastern US and to present a new model that can be used to make projections of future events that may cause loss of life and/or decreased human well-being.
Xu Yue, Susanna Strada, Nadine Unger, and Aihui Wang
Atmos. Chem. Phys., 17, 13699–13719, https://doi.org/10.5194/acp-17-13699-2017, https://doi.org/10.5194/acp-17-13699-2017, 2017
Short summary
Short summary
Climate change will significantly increase wildfire emissions in boreal North America by the midcentury, leading to increased surface ozone and atmospheric aerosols. These air pollutants can affect vegetation photosynthesis through stomatal uptake (for ozone) and radiative and climatic perturbations (for aerosols). Using a carbon–chemistry–climate model, we estimate trivial ozone vegetation damages but significant aerosol-induced reduction in ecosystem productivity by the 2050s.
Mikhail Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou
Atmos. Chem. Phys., 17, 12341–12360, https://doi.org/10.5194/acp-17-12341-2017, https://doi.org/10.5194/acp-17-12341-2017, 2017
Short summary
Short summary
This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service forecasts of olive pollen distribution in Europe. It is shown that the models can predict the main features of the observed pollen distribution but have more difficulties in capturing the season start and end, which appeared shifted by a few days. We also demonstrated that the combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
Guocheng Wang, Wen Zhang, Wenjuan Sun, Tingting Li, and Pengfei Han
Atmos. Chem. Phys., 17, 11849–11859, https://doi.org/10.5194/acp-17-11849-2017, https://doi.org/10.5194/acp-17-11849-2017, 2017
Short summary
Short summary
Cropland soil carbon sequestration contribute to not only climate change mitigation but also to sustainable agricultural production. This paper investigates soil carbon dynamics across the global main cereal cropping systems at a fine spatial resolution, using a modeling approach based on state-of-the-art databases of soil and climate. The key environmental controls on soil carbon changes were also identified.
Lei Zhao, Xuhui Lee, and Natalie M. Schultz
Atmos. Chem. Phys., 17, 9067–9080, https://doi.org/10.5194/acp-17-9067-2017, https://doi.org/10.5194/acp-17-9067-2017, 2017
Short summary
Short summary
Heat stress associated with climate change is one of most severe threats to human society. The problem is further compounded in urban areas by urban heat islands (UHIs). We use an urban climate model to evaluate the cooling benefits of active urban heat mitigation strategies both individually and collectively. We show that by forming UHI mitigation wedges, these strategies have the potential to significantly reduce the UHI effect plus warming induced by greenhouse gases.
Andrew S. Kowalski
Atmos. Chem. Phys., 17, 8177–8187, https://doi.org/10.5194/acp-17-8177-2017, https://doi.org/10.5194/acp-17-8177-2017, 2017
Short summary
Short summary
An analysis based on physical conservation law demonstrates that surface–atmosphere exchanges include a non-diffusive component. This implies the need to revise flux gradient relationships including eddy diffusivities in micrometeorology and stomatal conductances in plant physiology.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
Short summary
Short summary
After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Saroja M. Polavarapu, Michael Neish, Monique Tanguay, Claude Girard, Jean de Grandpré, Kirill Semeniuk, Sylvie Gravel, Shuzhan Ren, Sébastien Roche, Douglas Chan, and Kimberly Strong
Atmos. Chem. Phys., 16, 12005–12038, https://doi.org/10.5194/acp-16-12005-2016, https://doi.org/10.5194/acp-16-12005-2016, 2016
Short summary
Short summary
CO2 predictions are used to compute model–data mismatches when estimating surfaces fluxes using atmospheric observations together with an atmospheric transport model. By isolating the component of transport error which is due to uncertain meteorological analyses, it is demonstrated that CO2 can only be defined on large spatial scales. Thus, there is a spatial scale below which we cannot infer fluxes simply due to the fact that meteorological analyes are imperfect.
Lisa R. Welp, Prabir K. Patra, Christian Rödenbeck, Rama Nemani, Jian Bi, Stephen C. Piper, and Ralph F. Keeling
Atmos. Chem. Phys., 16, 9047–9066, https://doi.org/10.5194/acp-16-9047-2016, https://doi.org/10.5194/acp-16-9047-2016, 2016
Short summary
Short summary
Boreal and arctic ecosystems have been responding to elevated temperatures and atmospheric CO2 over the last decades. It is not clear if these ecosystems are sequestering more carbon or possibly becoming sources. This is an important feedback of the carbon cycle to global warming. We studied monthly biological land CO2 fluxes inferred from atmospheric CO2 concentrations using inverse models and found that net summer CO2 uptake increased, resulting in a small increase in annual CO2 uptake.
Michael T. Kiefer, Warren E. Heilman, Shiyuan Zhong, Joseph J. Charney, and Xindi Bian
Atmos. Chem. Phys., 16, 8499–8509, https://doi.org/10.5194/acp-16-8499-2016, https://doi.org/10.5194/acp-16-8499-2016, 2016
Short summary
Short summary
Studies of fire–atmosphere interactions in horizontally heterogeneous forests are limited in number. This study considers the sensitivity of fire-perturbed variables (e.g., vertical velocity, turbulent kinetic energy) to gaps in forest cover using ARPS-CANOPY, an atmospheric numerical model with a canopy sub-model. Results show that the atmosphere is most sensitive to the fire when the gap is centered on the fire and least sensitive when the gap is upstream of the fire.
L. Xia, A. Robock, S. Tilmes, and R. R. Neely III
Atmos. Chem. Phys., 16, 1479–1489, https://doi.org/10.5194/acp-16-1479-2016, https://doi.org/10.5194/acp-16-1479-2016, 2016
Short summary
Short summary
Climate model simulations show that stratospheric sulfate geoengineering could impact the terrestrial carbon cycle by enhancing the carbon sink. Enhanced downward diffuse radiation, combined with cooling, could stimulate plants to grow more and absorb more carbon dioxide. This beneficial impact of stratospheric sulfate geoengineering would need to be balanced by a large number of potential risks in any future decisions about implementation of geoengineering.
X. Yue, N. Unger, and Y. Zheng
Atmos. Chem. Phys., 15, 11931–11948, https://doi.org/10.5194/acp-15-11931-2015, https://doi.org/10.5194/acp-15-11931-2015, 2015
Short summary
Short summary
We estimate decadal trends in land carbon fluxes and emissions of biogenic volatile organic compounds (BVOCs) during 1982-2011, with a focus on the feedback from biosphere (such as tree growth and phenology). Increases of LAI at peak season accounts for ~25% of the trends in GPP and isoprene emissions at the northern lands. However, phenological change alone does not promote regional carbon uptake and BVOC emissions.
L. M. W. Leggett and D. A. Ball
Atmos. Chem. Phys., 15, 11571–11592, https://doi.org/10.5194/acp-15-11571-2015, https://doi.org/10.5194/acp-15-11571-2015, 2015
Short summary
Short summary
The previously expected linear relationship between atmospheric CO2 and climate variables including temperature is showing an increasing mismatch. This paper nonetheless provides fresh and possibly definitive support for a major relationship between CO2 and climate. Granger causality analysis provides evidence that change in level not level of CO2 primarily influences both global temperature and the El Niño–Southern Oscillation. The results may contribute to the prediction of future climate.
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, https://doi.org/10.5194/acp-15-8115-2015, 2015
Short summary
Short summary
The paper presents the first ensemble modelling experiment for forecasting the atmospheric dispersion of birch pollen in Europe. The study included 7 models of MACC-ENS tested over the season of 2010 and applied for 2013 in forecasting and reanalysis modes. The results were compared with observations in 11 countries, members of European Aeroallergen Network. The models successfully reproduced the timing of the unusually late season of 2013 but had more difficulties with absolute concentration.
X. Xu, C. Yi, and E. Kutter
Atmos. Chem. Phys., 15, 7457–7470, https://doi.org/10.5194/acp-15-7457-2015, https://doi.org/10.5194/acp-15-7457-2015, 2015
A. Veira, S. Kloster, S. Wilkenskjeld, and S. Remy
Atmos. Chem. Phys., 15, 7155–7171, https://doi.org/10.5194/acp-15-7155-2015, https://doi.org/10.5194/acp-15-7155-2015, 2015
Short summary
Short summary
We discuss the representation of wildfire emission heights in global climate models. Our implementation of a simple, semi-empirical plume height parametrization in the aerosol-climate model ECHAM6-HAM2 shows reasonable agreement with observations and with a more complex plume rise model. In contrast, prescribed emission heights, which do not consider the intensity of individual fires, fail to adequately simulate global plume height patterns. Diurnal and seasonal cycles are of minor importance.
A. Veira, S. Kloster, N. A. J. Schutgens, and J. W. Kaiser
Atmos. Chem. Phys., 15, 7173–7193, https://doi.org/10.5194/acp-15-7173-2015, https://doi.org/10.5194/acp-15-7173-2015, 2015
Short summary
Short summary
Global aerosol-climate models usually prescribe wildfire emission injections at fixed atmospheric levels. Here, we quantify the impact of prescribed and parametrized emission heights on aerosol long-range transport and radiation. For global emission height changes of 1.5-3.5km, we find a top-of-atmosphere radiative forcing of 0.05-0.1Wm-2. Replacing prescribed emission heights by a simple plume height parametrization only marginally improves the model performance in aerosol optical thickness.
I. C. Prentice, X. Liang, B. E. Medlyn, and Y.-P. Wang
Atmos. Chem. Phys., 15, 5987–6005, https://doi.org/10.5194/acp-15-5987-2015, https://doi.org/10.5194/acp-15-5987-2015, 2015
Short summary
Short summary
Land surface models (LSMs) describe how carbon and water fluxes react to environmental change. They are key component of climate models, yet they differ enormously. Many perform poorly, despite having many parameters. We outline a development strategy emphasizing robustness, reliability and realism, none of which is guaranteed by complexity alone. We propose multiple constraints, benchmarking and data assimilation, and representing unresolved processes stochastically, as tools in this endeavour.
F. Jiang, H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 10133–10144, https://doi.org/10.5194/acp-14-10133-2014, https://doi.org/10.5194/acp-14-10133-2014, 2014
T. Ziehn, A. Nickless, P. J. Rayner, R. M. Law, G. Roff, and P. Fraser
Atmos. Chem. Phys., 14, 9363–9378, https://doi.org/10.5194/acp-14-9363-2014, https://doi.org/10.5194/acp-14-9363-2014, 2014
X. Wang, C.-J. Lin, and X. Feng
Atmos. Chem. Phys., 14, 6273–6287, https://doi.org/10.5194/acp-14-6273-2014, https://doi.org/10.5194/acp-14-6273-2014, 2014
R. L. Thompson, F. Chevallier, A. M. Crotwell, G. Dutton, R. L. Langenfelds, R. G. Prinn, R. F. Weiss, Y. Tohjima, T. Nakazawa, P. B. Krummel, L. P. Steele, P. Fraser, S. O'Doherty, K. Ishijima, and S. Aoki
Atmos. Chem. Phys., 14, 1801–1817, https://doi.org/10.5194/acp-14-1801-2014, https://doi.org/10.5194/acp-14-1801-2014, 2014
E. N. Koffi, P. J. Rayner, M. Scholze, F. Chevallier, and T. Kaminski
Atmos. Chem. Phys., 13, 10555–10572, https://doi.org/10.5194/acp-13-10555-2013, https://doi.org/10.5194/acp-13-10555-2013, 2013
N. Unger, K. Harper, Y. Zheng, N. Y. Kiang, I. Aleinov, A. Arneth, G. Schurgers, C. Amelynck, A. Goldstein, A. Guenther, B. Heinesch, C. N. Hewitt, T. Karl, Q. Laffineur, B. Langford, K. A. McKinney, P. Misztal, M. Potosnak, J. Rinne, S. Pressley, N. Schoon, and D. Serça
Atmos. Chem. Phys., 13, 10243–10269, https://doi.org/10.5194/acp-13-10243-2013, https://doi.org/10.5194/acp-13-10243-2013, 2013
R. A. Ellis, D. J. Jacob, M. P. Sulprizio, L. Zhang, C. D. Holmes, B. A. Schichtel, T. Blett, E. Porter, L. H. Pardo, and J. A. Lynch
Atmos. Chem. Phys., 13, 9083–9095, https://doi.org/10.5194/acp-13-9083-2013, https://doi.org/10.5194/acp-13-9083-2013, 2013
M. Sofiev, R. Vankevich, T. Ermakova, and J. Hakkarainen
Atmos. Chem. Phys., 13, 7039–7052, https://doi.org/10.5194/acp-13-7039-2013, https://doi.org/10.5194/acp-13-7039-2013, 2013
L. D. Emberson, N. Kitwiroon, S. Beevers, P. Büker, and S. Cinderby
Atmos. Chem. Phys., 13, 6741–6755, https://doi.org/10.5194/acp-13-6741-2013, https://doi.org/10.5194/acp-13-6741-2013, 2013
C. A. Skjøth and C. Geels
Atmos. Chem. Phys., 13, 117–128, https://doi.org/10.5194/acp-13-117-2013, https://doi.org/10.5194/acp-13-117-2013, 2013
T. Kaminski, P. J. Rayner, M. Voßbeck, M. Scholze, and E. Koffi
Atmos. Chem. Phys., 12, 7867–7879, https://doi.org/10.5194/acp-12-7867-2012, https://doi.org/10.5194/acp-12-7867-2012, 2012
N. C. Parazoo, A. S. Denning, S. R. Kawa, S. Pawson, and R. Lokupitiya
Atmos. Chem. Phys., 12, 6405–6416, https://doi.org/10.5194/acp-12-6405-2012, https://doi.org/10.5194/acp-12-6405-2012, 2012
P. Büker, T. Morrissey, A. Briolat, R. Falk, D. Simpson, J.-P. Tuovinen, R. Alonso, S. Barth, M. Baumgarten, N. Grulke, P. E. Karlsson, J. King, F. Lagergren, R. Matyssek, A. Nunn, R. Ogaya, J. Peñuelas, L. Rhea, M. Schaub, J. Uddling, W. Werner, and L. D. Emberson
Atmos. Chem. Phys., 12, 5537–5562, https://doi.org/10.5194/acp-12-5537-2012, https://doi.org/10.5194/acp-12-5537-2012, 2012
Cited articles
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.
Chen, H., Zhou, T., Neale, R. B., Wu, X., and Zhang, G. J.: Performance of the New NCAR CAM3.5 in East Asian Summer Monsoon Simulations: Sensitivity to Modifications of the Convection Scheme, J. Climate, 23, 3657–3675, https://doi.org/10.1175/2010JCLI3022.1, 2010.
Ciais, P., Rayner, P., Chevallier, F., Bousquet, P., Logan, M., Peylin, P., and Ramonet, M.: Atmospheric inversions for estimating CO2 fluxes: methods and perspectives, in: Greenhouse Gas Inventories, edited by: Jonas, M., Nahorski, Z., Nilsson, S., and Whiter, T., 69–92, Springer Netherlands, https://doi.org/10.1007/978-94-007-1670-4_6, 2011.
Collins, W. D., Bitz, C. M., Blackmon, M. L., Bonan, G. B., Bretherton, C. S., Carton, J. A., Chang, P., Doney, S. C., Hack, J. J., Henderson, T. B., Kiehl, J. T., Large, W. G., McKenna, D. S., Santer, B. D., and Smith, R. D.: The Community Climate System Model Version 3 (CCSM3)., J. Climate, 19, 2122–2143, https://doi.org/10.1175/JCLI3761.1, 2006.
Enting, I.: Inverse Problems in Atmospheric Constituent Transport, Cambridge Atmospheric and Space Science Series, Cambridge University Press, Cambridge, 2002.
Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens, B. B., Bakwin, P. S., and Grainger, C. A.: Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor-oriented framework, J. Geophys. Res.-Atmos., 108, 4757, https://doi.org/10.1029/2003jd003770, 2003.
Gerbig, C., Körner, S., and Lin, J. C.: Vertical mixing in atmospheric tracer transport models: error characterization and propagation, Atmos. Chem. Phys., 8, 591–602, https://doi.org/10.5194/acp-8-591-2008, 2008.
Gourdji, S. M., Mueller, K. L., Yadav, V., Huntzinger, D. N., Andrews, A. E., Trudeau, M., Petron, G., Nehrkorn, T., Eluszkiewicz, J., Henderson, J., Wen, D., Lin, J., Fischer, M., Sweeney, C., and Michalak, A. M.: North American CO2 exchange: inter-comparison of modeled estimates with results from a fine-scale atmospheric inversion, Biogeosciences, 9, 457–475, https://doi.org/10.5194/bg-9-457-2012, 2012.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y. H., Cials, P., Fan, S., Fung, I. Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Maki, T., Maksyutov, S., Masarie, K., Peylin, P., Prather, M., Pak, B. C., Randerson, J., 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, https://doi.org/10.1038/415626a, 2002.
Hunt, B. R., Kalnay, E., Kostelich, E. J., Ott, E., Patil, D. J., Sauer, T., Szunyogh, I., Yorke, J. A., and Zimin, A. V.: Four-dimensional ensemble Kalman filtering, Tellus A, 56, 273–277, https://doi.org/10.1111/j.1600-0870.2004.00066.x, 2004.
Hunt, B. R., Kostelich, E. J., and Szunyogh, I.: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter, Physica D, 230, 112–126, https://doi.org/10.1016/j.physd.2006.11.008, 2007.
Huntzinger, D., Post, W., Wei, Y., Michalak, A., West, T., Jacobson, A., Baker, I., Chen, J., Davis, K., Hayes, D., Hoffman, F., Jain, A., Liu, S., McGuire, A., Neilson, R., Potter, C., Poulter, B., Price, D., Raczka, B., Tian, H., Thornton, P., Tomelleri, E., Viovy, N., Xiao, J., Yuan, W., Zeng, N., Zhao, M., and Cook, R.: North American Carbon Program (NACP) regional interim synthesis: Terrestrial biospheric model intercomparison, Ecol. Model., 232, 144–157, https://doi.org/10.1016/j.ecolmodel.2012.02.004, 2012.
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S.-K., Hnilo, J. J., Fiorino, M., and Potter, G. L.: NCEP–DOE AMIP-II Reanalysis (R-2), B. Am. Meteorol. Soc., 83, 1631–1643, https://doi.org/10.1175/BAMS-83-11-1631, 2002.
Kretschmer, R., Gerbig, C., Karstens, U., and Koch, F.-T.: Error characterization of CO2 vertical mixing in the atmospheric transport model WRF-VPRM, Atmos. Chem. Phys., 12, 2441–2458, https://doi.org/10.5194/acp-12-2441-2012, 2012.
Kretschmer, R., Gerbig, C., Karstens, U., Biavati, G., Vermeulen, A., Vogel, F., Hammer, S., and Totsche, K. U.: Impact of optimized mixing heights on simulated regional atmospheric transport of CO2, Atmos. Chem. Phys., 14, 7149–7172, https://doi.org/10.5194/acp-14-7149-2014, 2014.
Lauvaux, T., Pannekoucke, O., Sarrat, C., Chevallier, F., Ciais, P., Noilhan, J., and Rayner, P. J.: Structure of the transport uncertainty in mesoscale inversions of CO2 sources and sinks using ensemble model simulations, Biogeosciences, 6, 1089–1102, https://doi.org/10.5194/bg-6-1089-2009, 2009.
Law, B., Falge, E., Gu, L., Baldocchi, D., Bakwin, P., Berbigier, P., Davis, K., Dolman, A., Falk, M., Fuentes, J., Goldstein, A., Granier, A., Grelle, A., Hollinger, D., Janssens, I., Jarvis, P., Jensen, N., Katul, G., Mahli, Y., Matteucci, G., Meyers, T., Monson, R., Munger, W., Oechel, W., Olson, R., Pilegaard, K., U, K. P., Thorgeirsson, H., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation, Agr. Forest Meteorol., 113, 97–120, https://doi.org/10.1016/S0168-1923(02)00104-1, 2002.
Li, H., Kalnay, E., and Miyoshi, T.: Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter, Q. J. Roy. Meteor. Soc., 135, 523–533, https://doi.org/10.1002/qj.371, 2009.
Lin, J. C. and Gerbig, C.: Accounting for the effect of transport errors on tracer inversions, Geophys. Res. Lett., 32, L01802, https://doi.org/10.1029/2004GL021127, 2005.
Lin, J. C., Pejam, M. R., Chan, E., Wofsy, S. C., Gottlieb, E. W., Margolis, H. A., and McCaughey, J. H.: Attributing uncertainties in simulated biospheric carbon fluxes to different error sources, Global Biogeochem. Cy., 25, GB2018, https://doi.org/10.1029/2010GB003884, 2011.
Liu, J., Fung, I., Kalnay, E., and Kang, J.-S.: CO2 transport uncertainties from the uncertainties in meteorological fields, Geophys. Res. Lett., 38, L12808, https://doi.org/10.1029/2011GL047213, 2011.
Liu, J., Fung, I., Kalnay, E., Kang, J.-S., Olsen, E. T., and Chen, L.: Simultaneous assimilation of AIRS XCO2 and meteorological observations in a carbon climate model with an ensemble Kalman filter, J. Geophys. Res.-Atmos., 117, D05309, https://doi.org/10.1029/2011JD016642, 2012.
Masarie, K. A., Pétron, G., Andrews, A., Bruhwiler, L., Conway, T. J., Jacobson, A. R., Miller, J. B., Tans, P. P., Worthy, D. E., and Peters, W.: Impact of CO}2 measurement bias on {CarbonTracker surface flux estimates, J. Geophys. Res.-Atmos., 116, D17305, https://doi.org/10.1029/2011JD016270, 2011.
Michalak, A., Bruhwiler, L., and Tans, P.: A geostatistical approach to surface flux estimation of atmospheric trace gases, J. Geophys. Res.-Atmos., 109, D14109, https://doi.org/10.1029/2003JD004422, 2004.
Michalak, A. M., Hirsch, A., Bruhwiler, L., Gurney, K. R., Peters, W., and Tans, P. P.: Maximum likelihood estimation of covariance parameters for Bayesian atmospheric trace gas surface flux inversions, J. Geophys. Res.-Atmos., 110, D24107, https://doi.org/10.1029/2005JD005970, 2005.
Miller, S. M., Kort, E. A., Hirsch, A. I., Dlugokencky, E. J., Andrews, A. E., Xu, X., Tian, H., Nehrkorn, T., Eluszkiewicz, J., Michalak, A. M., and Wofsy, S. C.: Regional sources of nitrous oxide over the United States: Seasonal variation and spatial distribution, J. Geophys. Res.-Atmos., 117, D06310, https://doi.org/10.1029/2011JD016951, 2012.
Miyoshi, T.: The Gaussian approach to adaptive covariance inflation and its implementation with the Local Ensemble Transform Kalman Filter, Mon. Weather Rev., 139, 1519–1535, https://doi.org/10.1175/2010MWR3570.1, 2011.
Oleson, K. W., Niu, G.-Y., Yang, Z.-L., Lawrence, D. M., Thornton, P. E., Lawrence, P. J., Stöckli, R., Dickinson, R. E., Bonan, G. B., Levis, S., Dai, A., and Qian, T.: Improvements to the Community Land Model and their impact on the hydrological cycle, J. Geophys. Res.-Biogeo., 113, G01021, https://doi.org/10.1029/2007JG000563, 2008.
Parazoo, N. C., Denning, A. S., Kawa, S. R., Pawson, S., and Lokupitiya, R.: CO2 flux estimation errors associated with moist atmospheric processes, Atmos. Chem. Phys., 12, 6405–6416, https://doi.org/10.5194/acp-12-6405-2012, 2012.
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., Werf, G. R. v. d., 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, with updates documented at http://carbontracker.noaa.gov, 104, 18925–18930, https://doi.org/10.1073/pnas.0708986104, 2007.
Pino, D., Vilà-Guerau de Arellano, J., Peters, W., Schröter, J., van Heerwaarden, C. C., and Krol, M. C.: A conceptual framework to quantify the influence of convective boundary layer development on carbon dioxide mixing ratios, Atmos. Chem. Phys., 12, 2969–2985, https://doi.org/10.5194/acp-12-2969-2012, 2012.
Raczka, B. M., Davis, K. J., Huntzinger, D., Neilson, R. P., Poulter, B., Richardson, A. D., Xiao, J., Baker, I., Ciais, P., Keenan, T. F., Law, B., Post, W. M., Ricciuto, D., Schaefer, K., Tian, H., Tomelleri, E., Verbeeck, H., and Viovy, N.: Evaluation of continental carbon cycle simulations with North American flux tower observations, Ecol. Monogr., 83, 531–556, https://doi.org/10.1890/12-0893.1, 2013.
Stephens, B. B., Gurney, K. R., Tans, P. P., Sweeney, C., Peters, W., Bruhwiler, L., Ciais, P., Ramonet, M., Bousquet, P., Nakazawa, T., Aoki, S., Machida, T., Inoue, G., Vinnichenko, N., Lloyd, J., Jordan, A., Heimann, M., Shibistova, O., Langenfelds, R. L., Steele, L. P., Francey, R. J., and Denning, A. S.: Weak Northern and Strong Tropical Land Carbon Uptake from Vertical Profiles of Atmospheric CO2, Science, 316, 1732–1735, https://doi.org/10.1126/science.1137004, 2007.
Tarantola, A.: Inverse Problem Theory and Methods for Model Parameter Estimation, Society for Industrial and Applied Mathematics, Philadelphia, 2005.
Williams, I. N., Riley, W. J., Torn, M. S., Berry, J. A., and Biraud, S. C.: Using boundary layer equilibrium to reduce uncertainties in transport models and CO2 flux inversions, Atmos. Chem. Phys., 11, 9631–9641, https://doi.org/10.5194/acp-11-9631-2011, 2011.
Altmetrics
Final-revised paper
Preprint