Articles | Volume 6, issue 2
Earth Syst. Sci. Data, 6, 375–384, 2014
https://doi.org/10.5194/essd-6-375-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Earth Syst. Sci. Data, 6, 375–384, 2014
https://doi.org/10.5194/essd-6-375-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
18 Dec 2014
Review article
| 18 Dec 2014
ObsPack: a framework for the preparation, delivery, and attribution of atmospheric greenhouse gas measurements
K. A. Masarie et al.
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Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
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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
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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.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
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In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech., 13, 4295–4315, https://doi.org/10.5194/amt-13-4295-2020, https://doi.org/10.5194/amt-13-4295-2020, 2020
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With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2018 to track worldwide changes in photosynthetic activity by vegetation.
Getachew Agmuas Adnew, Thijs L. Pons, Gerbrand Koren, Wouter Peters, and Thomas Röckmann
Biogeosciences, 17, 3903–3922, https://doi.org/10.5194/bg-17-3903-2020, https://doi.org/10.5194/bg-17-3903-2020, 2020
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We measured the effect of photosynthesis, the largest flux in the carbon cycle, on the triple oxygen isotope composition of atmospheric CO2 at the leaf level during gas exchange using three plant species. The main factors that limit the impact of land vegetation on the triple oxygen isotope composition of atmospheric CO2 are identified, characterized and discussed. The effect of photosynthesis on the isotopic composition of CO2 is commonly quantified as discrimination (ΔA).
Ingrid Super, Hugo A. C. Denier van der Gon, Michiel K. van der Molen, Stijn N. C. Dellaert, and Wouter Peters
Geosci. Model Dev., 13, 2695–2721, https://doi.org/10.5194/gmd-13-2695-2020, https://doi.org/10.5194/gmd-13-2695-2020, 2020
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Understanding urban CO2 fluxes is increasingly important to support emission reduction policies. In this work we extended an existing framework for emission verification to increase its suitability for urban areas and source-sector-based decision-making by using a dynamic emission model. We find that the dynamic emission model provides a better understanding of emissions at small scales and their uncertainties. By including co-emitted species, emission can be related to specific source sectors.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Truls Andersen, Bert Scheeren, Wouter Peters, and Huilin Chen
Atmos. Meas. Tech., 11, 2683–2699, https://doi.org/10.5194/amt-11-2683-2018, https://doi.org/10.5194/amt-11-2683-2018, 2018
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We developed and field-tested a UAV-based active AirCore for atmospheric measurements of CO2, CH4, and CO. AirCore is an innovative tool that passively samples air using the atmospheric pressure gradient during descent. Here we have taken further steps to change the “active” sampling process with a pump, miniaturize it, and deploy it on a UAV. The active AirCore system opens up a wide variety of opportunities, e.g., quantifying CH4 emissions from wetlands, landfills, other CH4 hot spots.
Ivar R. van der Velde, John B. Miller, Michiel K. van der Molen, Pieter P. Tans, Bruce H. Vaughn, James W. C. White, Kevin Schaefer, and Wouter Peters
Geosci. Model Dev., 11, 283–304, https://doi.org/10.5194/gmd-11-283-2018, https://doi.org/10.5194/gmd-11-283-2018, 2018
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We explored an inverse modeling technique to interpret global atmospheric measurements of CO2 and the ratio of its stable carbon isotopes (δ13C). We detected the possible underestimation of drought stress in biosphere models after applying combined atmospheric CO2 and δ13C constraints. This study highlights the importance of improving the representation of the biosphere in carbon–climate models, in particular in a world where droughts become more extreme and more frequent.
Xin Lan, Pieter Tans, Colm Sweeney, Arlyn Andrews, Andrew Jacobson, Molly Crotwell, Edward Dlugokencky, Jonathan Kofler, Patricia Lang, Kirk Thoning, and Sonja Wolter
Atmos. Chem. Phys., 17, 15151–15165, https://doi.org/10.5194/acp-17-15151-2017, https://doi.org/10.5194/acp-17-15151-2017, 2017
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We analyze spatial patterns of column CO2 over North America using well-calibrated aircraft and tall tower measurements. We find that the long-term averaged spatial gradients of column CO2 across North America show a smooth pattern that mainly reflects the large-scale circulation. Our results can serve as a good reference for evaluating current and future column CO2 retrievals from both ground and satellite platforms.
Ingrid Super, Hugo A. C. Denier van der Gon, Michiel K. van der Molen, Hendrika A. M. Sterk, Arjan Hensen, and Wouter Peters
Atmos. Chem. Phys., 17, 13297–13316, https://doi.org/10.5194/acp-17-13297-2017, https://doi.org/10.5194/acp-17-13297-2017, 2017
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In this research we examined the use of different models to simulate CO2 concentrations in and around urban areas. We find that in the presence of large stack emissions in a gridded model is insufficient to represent the small dimensions of the CO2 plumes. A plume model improves this representation up to 10–14 km from the stack. Better model results can improve the estimate of CO2 emissions from urban areas and assist in identifying efficient emission reduction policies.
Ingrid T. van der Laan-Luijkx, Ivar R. van der Velde, Emma van der Veen, Aki Tsuruta, Karolina Stanislawska, Arne Babenhauserheide, Hui Fang Zhang, Yu Liu, Wei He, Huilin Chen, Kenneth A. Masarie, Maarten C. Krol, and Wouter Peters
Geosci. Model Dev., 10, 2785–2800, https://doi.org/10.5194/gmd-10-2785-2017, https://doi.org/10.5194/gmd-10-2785-2017, 2017
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The CarbonTracker Data Assimilation Shell (CTDAS) is the new modular implementation of the CarbonTracker Europe (CTE) data assimilation system. We present and document CTDAS and demonstrate its ability to estimate global carbon sources and sinks. We present the latest CTE results including the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show the versatility of CTDAS with an overview of the wide range of other applications.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters
Geosci. Model Dev., 10, 1261–1289, https://doi.org/10.5194/gmd-10-1261-2017, https://doi.org/10.5194/gmd-10-1261-2017, 2017
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In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
Jinwoong Kim, Hyun Mee Kim, Chun-Ho Cho, Kyung-On Boo, Andrew R. Jacobson, Motoki Sasakawa, Toshinobu Machida, Mikhail Arshinov, and Nikolay Fedoseev
Atmos. Chem. Phys., 17, 2881–2899, https://doi.org/10.5194/acp-17-2881-2017, https://doi.org/10.5194/acp-17-2881-2017, 2017
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To investigate the effect of CO2 observations in Siberia on the surface CO2 flux analyses, two experiments using observation data sets with and without Siberian measurements were performed. While the magnitude of the optimized surface CO2 flux uptake in Siberia decreased, that in the other regions of the Northern Hemisphere increased for the experiment with Siberian observations. It is expected that the Siberian observations play an important role in estimating surface CO2 flux in the future.
Ingrid Super, Hugo A. C. Denier van der Gon, Michiel K. van der Molen, Hendrika A. M. Sterk, Arjan Hensen, and Wouter Peters
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-807, https://doi.org/10.5194/acp-2016-807, 2016
Revised manuscript not accepted
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, and Wouter Peters
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-181, https://doi.org/10.5194/gmd-2016-181, 2016
Revised manuscript has not been submitted
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In this study, we found that methane emission estimates, driven by the CTE-CH4 model, depend on model setups and inputs, especially for regional estimates. An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role. The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
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In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
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
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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.
M. K. van der Molen, R. A. M. de Jeu, W. Wagner, I. R. van der Velde, P. Kolari, J. Kurbatova, A. Varlagin, T. C. Maximov, A. V. Kononov, T. Ohta, A. Kotani, M. C. Krol, and W. Peters
Hydrol. Earth Syst. Sci., 20, 605–624, https://doi.org/10.5194/hess-20-605-2016, https://doi.org/10.5194/hess-20-605-2016, 2016
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Boreal Eurasia contains extensive forests, which play an important role in the terrestrial carbon cycle. Droughts can modify this cycle considerably, although very few ground-based observations are available in the region. We test whether satellite-observed soil moisture may be used to improve carbon cycle models in this region. This paper explains when and where this works best. The interpretation of satellite soil moisture is best in summer conditions, and is hampered by snow, ice and ponding.
S. X. Fang, P. P. Tans, M. Steinbacher, L. X. Zhou, and T. Luan
Atmos. Meas. Tech., 8, 5301–5313, https://doi.org/10.5194/amt-8-5301-2015, https://doi.org/10.5194/amt-8-5301-2015, 2015
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The identification of atmospheric CO2 observation data which are minimally influenced by very local emissions/removals is essential for trend analysis and for the estimation of regional sources and sinks. We compared four data filtering regimes based on the observation records at Lin'an station in China, and found that the use of meteorological parameters was the most favorable. This conclusion will aid regional data selection at the Lin'an station.
J. M. Barlow, P. I. Palmer, L. M. Bruhwiler, and P. Tans
Atmos. Chem. Phys., 15, 13739–13758, https://doi.org/10.5194/acp-15-13739-2015, https://doi.org/10.5194/acp-15-13739-2015, 2015
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The major results from our analysis include (1) a significant revision to previously reported estimates of phase changes in the seasonal cycle atmospheric CO2, which are more closely related to changes in the terrestrial biosphere; and (2) an indirect observation that is consistent with high northern latitude ecosystems progressively taking up more CO2 during spring and early summer.
C. Rödenbeck, D. C. E. Bakker, N. Gruber, Y. Iida, A. R. Jacobson, S. Jones, P. Landschützer, N. Metzl, S. Nakaoka, A. Olsen, G.-H. Park, P. Peylin, K. B. Rodgers, T. P. Sasse, U. Schuster, J. D. Shutler, V. Valsala, R. Wanninkhof, and J. Zeng
Biogeosciences, 12, 7251–7278, https://doi.org/10.5194/bg-12-7251-2015, https://doi.org/10.5194/bg-12-7251-2015, 2015
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This study investigates variations in the CO2 uptake of the ocean from year to year. These variations have been calculated from measurements of the surface-ocean carbon content by various different interpolation methods. The equatorial Pacific is estimated to be the region with the strongest year-to-year variations, tied to the El Nino phase. The global ocean CO2 uptake gradually increased from about the year 2000. The comparison of the interpolation methods identifies these findings as robust.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
A. Babenhauserheide, S. Basu, S. Houweling, W. Peters, and A. Butz
Atmos. Chem. Phys., 15, 9747–9763, https://doi.org/10.5194/acp-15-9747-2015, https://doi.org/10.5194/acp-15-9747-2015, 2015
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We compare two different data assimilation systems for estimating sources and sinks of CO_2 from concentration measurements. The systems are CarbonTracker and TM5-4DVar, which have both been used in a number of scientific studies. We analyze the differences between both models as well as the sensitivity of the estimated sources and sinks to the observation coverage. The results provide a lower limit for the uncertainty of surface carbon fluxes with the current measurement network.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
A. P. Ballantyne, R. Andres, R. Houghton, B. D. Stocker, R. Wanninkhof, W. Anderegg, L. A. Cooper, M. DeGrandpre, P. P. Tans, J. B. Miller, C. Alden, and J. W. C. White
Biogeosciences, 12, 2565–2584, https://doi.org/10.5194/bg-12-2565-2015, https://doi.org/10.5194/bg-12-2565-2015, 2015
M. Combe, J. Vilà-Guerau de Arellano, H. G. Ouwersloot, C. M. J. Jacobs, and W. Peters
Biogeosciences, 12, 103–123, https://doi.org/10.5194/bg-12-103-2015, https://doi.org/10.5194/bg-12-103-2015, 2015
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This study investigates the interactions among the carbon, water and heat cycles above a maize field at the diurnal scale. We couple two land-surface schemes, corresponding to two different modelling approaches, to the same atmospheric boundary-layer (ABL) model. We find the simpler meteorological approach best reproduces the surface and upper-air observations. Finally, we show that the interaction of subsidence with ABL dynamics is key to explain the daytime atmospheric CO2 budget.
Y. Wei, S. Liu, D. N. Huntzinger, A. M. Michalak, N. Viovy, W. M. Post, C. R. Schwalm, K. Schaefer, A. R. Jacobson, C. Lu, H. Tian, D. M. Ricciuto, R. B. Cook, J. Mao, and X. Shi
Geosci. Model Dev., 7, 2875–2893, https://doi.org/10.5194/gmd-7-2875-2014, https://doi.org/10.5194/gmd-7-2875-2014, 2014
I. R. van der Velde, J. B. Miller, K. Schaefer, G. R. van der Werf, M. C. Krol, and W. Peters
Biogeosciences, 11, 6553–6571, https://doi.org/10.5194/bg-11-6553-2014, https://doi.org/10.5194/bg-11-6553-2014, 2014
M. Inoue, I. Morino, O. Uchino, Y. Miyamoto, T. Saeki, Y. Yoshida, T. Yokota, C. Sweeney, P. P. Tans, S. C. Biraud, T. Machida, J. V. Pittman, E. A. Kort, T. Tanaka, S. Kawakami, Y. Sawa, K. Tsuboi, and H. Matsueda
Atmos. Meas. Tech., 7, 2987–3005, https://doi.org/10.5194/amt-7-2987-2014, https://doi.org/10.5194/amt-7-2987-2014, 2014
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
D. Bozhinova, M. K. van der Molen, I. R. van der Velde, M. C. Krol, S. van der Laan, H. A. J. Meijer, and W. Peters
Atmos. Chem. Phys., 14, 7273–7290, https://doi.org/10.5194/acp-14-7273-2014, https://doi.org/10.5194/acp-14-7273-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
H. F. Zhang, B. Z. Chen, I. T. van der Laan-Luijk, T. Machida, H. Matsueda, Y. Sawa, Y. Fukuyama, R. Langenfelds, M. van der Schoot, G. Xu, J. W. Yan, M. L. Cheng, L. X. Zhou, P. P. Tans, and W. Peters
Atmos. Chem. Phys., 14, 5807–5824, https://doi.org/10.5194/acp-14-5807-2014, https://doi.org/10.5194/acp-14-5807-2014, 2014
S. X. Fang, L. X. Zhou, P. P. Tans, P. Ciais, M. Steinbacher, L. Xu, and T. Luan
Atmos. Chem. Phys., 14, 2541–2554, https://doi.org/10.5194/acp-14-2541-2014, https://doi.org/10.5194/acp-14-2541-2014, 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
D. Helmig, V. Petrenko, P. Martinerie, E. Witrant, T. Röckmann, A. Zuiderweg, R. Holzinger, J. Hueber, C. Thompson, J. W. C. White, W. Sturges, A. Baker, T. Blunier, D. Etheridge, M. Rubino, and P. Tans
Atmos. Chem. Phys., 14, 1463–1483, https://doi.org/10.5194/acp-14-1463-2014, https://doi.org/10.5194/acp-14-1463-2014, 2014
D. N. Huntzinger, C. Schwalm, A. M. Michalak, K. Schaefer, A. W. King, Y. Wei, A. Jacobson, S. Liu, R. B. Cook, W. M. Post, G. Berthier, D. Hayes, M. Huang, A. Ito, H. Lei, C. Lu, J. Mao, C. H. Peng, S. Peng, B. Poulter, D. Riccuito, X. Shi, H. Tian, W. Wang, N. Zeng, F. Zhao, and Q. Zhu
Geosci. Model Dev., 6, 2121–2133, https://doi.org/10.5194/gmd-6-2121-2013, https://doi.org/10.5194/gmd-6-2121-2013, 2013
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
P. Peylin, R. M. Law, K. R. Gurney, F. Chevallier, A. R. Jacobson, T. Maki, Y. Niwa, P. K. Patra, W. Peters, P. J. Rayner, C. Rödenbeck, I. T. van der Laan-Luijkx, and X. Zhang
Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, https://doi.org/10.5194/bg-10-6699-2013, 2013
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
F. Deng, J. M. Chen, Y. Pan, W. Peters, R. Birdsey, K. McCullough, and J. Xiao
Biogeosciences, 10, 5335–5348, https://doi.org/10.5194/bg-10-5335-2013, https://doi.org/10.5194/bg-10-5335-2013, 2013
Y. Plancherel, K. B. Rodgers, R. M. Key, A. R. Jacobson, and J. L. Sarmiento
Biogeosciences, 10, 4801–4831, https://doi.org/10.5194/bg-10-4801-2013, https://doi.org/10.5194/bg-10-4801-2013, 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
M. Krol, W. Peters, P. Hooghiemstra, M. George, C. Clerbaux, D. Hurtmans, D. McInerney, F. Sedano, P. Bergamaschi, M. El Hajj, J. W. Kaiser, D. Fisher, V. Yershov, and J.-P. Muller
Atmos. Chem. Phys., 13, 4737–4747, https://doi.org/10.5194/acp-13-4737-2013, https://doi.org/10.5194/acp-13-4737-2013, 2013
H. Chen, A. Karion, C. W. Rella, J. Winderlich, C. Gerbig, A. Filges, T. Newberger, C. Sweeney, and P. P. Tans
Atmos. Meas. Tech., 6, 1031–1040, https://doi.org/10.5194/amt-6-1031-2013, https://doi.org/10.5194/amt-6-1031-2013, 2013
S. C. Biraud, M. S. Torn, J. R. Smith, C. Sweeney, W. J. Riley, and P. P. Tans
Atmos. Meas. Tech., 6, 751–763, https://doi.org/10.5194/amt-6-751-2013, https://doi.org/10.5194/amt-6-751-2013, 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
G. R. van der Werf, W. Peters, T. T. van Leeuwen, and L. Giglio
Clim. Past, 9, 289–306, https://doi.org/10.5194/cp-9-289-2013, https://doi.org/10.5194/cp-9-289-2013, 2013
Related subject area
Atmospheric chemistry and physics
Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure
Full-coverage 250 m monthly aerosol optical depth dataset (2000–2019) amended with environmental covariates by an ensemble machine learning model over arid and semi-arid areas, NW China
Global Carbon Budget 2022
The polar mesospheric cloud dataset of the Balloon Lidar Experiment (BOLIDE)
Multiyear emissions of carbonaceous aerosols from cooking, fireworks, sacrificial incense, joss paper burning, and barbecue as well as their key driving forces in China
Impacts of the proposal of the CNG2020 strategy on aircraft emissions of China–foreign routes
Northern hemispheric atmospheric ethane trends in the upper troposphere and lower stratosphere (2006–2016) with reference to methane and propane
New contributions of measurements in Europe to the global inventory of the stable isotopic composition of methane
International Monitoring System infrasound data products for atmospheric studies and civilian applications
A benchmark dataset of diurnal- and seasonal-scale radiation, heat, and CO2 fluxes in a typical East Asian monsoon region
Attenuated atmospheric backscatter profiles measured by the CO2 Sounder lidar in the 2017 ASCENDS/ABoVE airborne campaign
Climatology of aerosol component concentrations derived from multi-angular polarimetric POLDER-3 observations using GRASP algorithm
Reconstructing 6-hourly PM2.5 datasets from 1960 to 2020 in China
A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO2 retrievals (GCAS2021)
Multispecies and high-spatiotemporal-resolution database of vehicular emissions in Brazil
The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016)
The WGLC global gridded lightning climatology and time series, 2022 update
European primary emissions of criteria pollutants and greenhouse gases in 2020 modulated by the COVID-19 pandemic disruptions
Historical reconstruction of background air pollution over France for 2000–2015
Methane, carbon dioxide, hydrogen sulfide, and isotopic ratios of methane observations from the Permian Basin tower network
Observations of the lower atmosphere from the 2021 WiscoDISCO campaign
A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS
Aircraft measurements of water vapor heavy isotope ratios in the marine boundary layer and lower troposphere during ORACLES
A global land aerosol fine-mode fraction dataset (2001–2020) retrieved from MODIS using hybrid physical and deep learning approaches
Two decades of flask observations of atmospheric δ(O2∕N2), CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland), and 3 years from Halley station (Antarctica)
LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion
Design and description of the MUSICA IASI full retrieval product
Reactive nitrogen fluxes over peatland and forest ecosystems using micrometeorological measurement techniques
An extensive data set for in situ microphysical characterization of low-level clouds in a Finnish sub-Arctic site
CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling
An 11-year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm
High-resolution biogenic global emission inventory for the time period 2000–2019 for air quality modelling
Measurements from the University of Colorado RAAVEN Uncrewed Aircraft System during ATOMIC
ML-TOMCAT: machine-learning-based satellite-corrected global stratospheric ozone profile data set from a chemical transport model
The first global 883 GHz cloud ice survey: IceCube Level 1 data calibration, processing and analysis
The global and multi-annual MUSICA IASI {H2O, δD} pair dataset
The OH (3-1) nightglow volume emission rate retrieved from OSIRIS measurements: 2001 to 2015
Advanced NO2 retrieval technique for the Brewer spectrophotometer applied to the 20-year record in Rome, Italy
Total column ozone measurements by the Dobson spectrophotometer at Belsk (Poland) for the period 1963–2019: homogenization and adjustment to the Brewer spectrophotometer
Recovery of the first ever multi-year lidar dataset of the stratospheric aerosol layer, from Lexington, MA, and Fairbanks, AK, January 1964 to July 1965
Observations of the downwelling far-infrared atmospheric emission at the Zugspitze observatory
UV-Indien network: ground-based measurements dedicated to the monitoring of UV radiation over the western Indian Ocean
Changes in global air pollutant emissions during the COVID-19 pandemic: a dataset for atmospheric modeling
A global total column ozone climate data record
A global dataset of atmospheric 7Be and 210Pb measurements: annual air concentration and depositional flux
Atmospheric aerosol, gases, and meteorological parameters measured during the LAPSE-RATE campaign by the Finnish Meteorological Institute and Kansas State University
Changes in China's anthropogenic emissions and air quality during the COVID-19 pandemic in 2020
Long-term trends of ambient nitrate (NO3−) concentrations across China based on ensemble machine-learning models
The winter 2019 air pollution (PM2.5) measurement campaign in Christchurch, New Zealand
Monthly resolved modelled oceanic emissions of carbonyl sulphide and carbon disulphide for the period 2000–2019
Haris Rahadianto, Hirokazu Tatano, Masato Iguchi, Hiroshi L. Tanaka, Tetsuya Takemi, and Sudip Roy
Earth Syst. Sci. Data, 14, 5309–5332, https://doi.org/10.5194/essd-14-5309-2022, https://doi.org/10.5194/essd-14-5309-2022, 2022
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We simulated the Taisho (1914) eruption of Sakurajima volcano under various weather conditions to show how a similar eruption would affect contemporary Japan in a worst-case scenario. We provide the dataset of projected airborne ash concentration and deposit over all of Japan to support risk assessment and planning for disaster management. Our work extends previous analyses of local risks to cover distal locations in Japan where a large population could be exposed to devastating impacts.
Xiangyue Chen, Hongchao Zuo, Zipeng Zhang, Xiaoyi Cao, Jikai Duan, Chuanmei Zhu, Zhe Zhang, and Jingzhe Wang
Earth Syst. Sci. Data, 14, 5233–5252, https://doi.org/10.5194/essd-14-5233-2022, https://doi.org/10.5194/essd-14-5233-2022, 2022
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Arid and semi-arid areas are data-scarce aerosol areas. We provide path-breaking, high-resolution, full coverage, and long time series AOD datasets (FEC AOD) to support the atmosphere and related studies in northwestern China. The FEC AOD effectively compensates for the deficiency and constraints of in situ observations and satellite AOD products. Meanwhile, FEC AOD products demonstrate a reliable accuracy and ability to capture long-term change information.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Natalie Kaifler, Bernd Kaifler, Markus Rapp, and David C. Fritts
Earth Syst. Sci. Data, 14, 4923–4934, https://doi.org/10.5194/essd-14-4923-2022, https://doi.org/10.5194/essd-14-4923-2022, 2022
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We measured polar mesospheric clouds (PMCs), our Earth’s highest clouds at the edge of space, with a Rayleigh lidar from a stratospheric balloon. We describe how we derive the cloud’s brightness and discuss the stability of the gondola pointing and the sensitivity of our measurements. We present our high-resolution PMC dataset that is used to study dynamical processes in the upper mesosphere, e.g. regarding gravity waves, mesospheric bores, vortex rings, and Kelvin–Helmholtz instabilities.
Yi Cheng, Shaofei Kong, Liquan Yao, Huang Zheng, Jian Wu, Qin Yan, Shurui Zheng, Yao Hu, Zhenzhen Niu, Yingying Yan, Zhenxing Shen, Guofeng Shen, Dantong Liu, Shuxiao Wang, and Shihua Qi
Earth Syst. Sci. Data, 14, 4757–4775, https://doi.org/10.5194/essd-14-4757-2022, https://doi.org/10.5194/essd-14-4757-2022, 2022
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This work establishes the first emission inventory of carbonaceous aerosols from cooking, fireworks, sacrificial incense, joss paper burning, and barbecue, using multi-source datasets and tested emission factors. These emissions were concentrated in specific periods and areas. Positive and negative correlations between income and emissions were revealed in urban and rural regions. The dataset will be helpful for improving modeling studies and modifying corresponding emission control policies.
Qiang Cui, Yilin Lei, and Bin Chen
Earth Syst. Sci. Data, 14, 4419–4433, https://doi.org/10.5194/essd-14-4419-2022, https://doi.org/10.5194/essd-14-4419-2022, 2022
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This paper calculates the emissions of six kinds of emissions from China’s foreign routes from 2014 to 2019, enriching the existing database. This paper applies the improved BFFM2-FOA-FPM method and ICAO method to calculate the emissions, which can combine CO2 and non-CO2 emissions calculations and calculate the aircraft types' emission intensity.
Mengze Li, Andrea Pozzer, Jos Lelieveld, and Jonathan Williams
Earth Syst. Sci. Data, 14, 4351–4364, https://doi.org/10.5194/essd-14-4351-2022, https://doi.org/10.5194/essd-14-4351-2022, 2022
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We present a northern hemispheric airborne measurement dataset of atmospheric ethane, propane and methane and temporal trends for the time period 2006–2016 in the upper troposphere and lower stratosphere. The growth rates of ethane, methane, and propane in the upper troposphere are -2.24, 0.33, and -0.78 % yr-1, respectively, and in the lower stratosphere they are -3.27, 0.26, and -4.91 % yr-1, respectively, in 2006–2016.
Malika Menoud, Carina van der Veen, Dave Lowry, Julianne M. Fernandez, Semra Bakkaloglu, James L. France, Rebecca E. Fisher, Hossein Maazallahi, Mila Stanisavljević, Jarosław Nęcki, Katarina Vinkovic, Patryk Łakomiec, Janne Rinne, Piotr Korbeń, Martina Schmidt, Sara Defratyka, Camille Yver-Kwok, Truls Andersen, Huilin Chen, and Thomas Röckmann
Earth Syst. Sci. Data, 14, 4365–4386, https://doi.org/10.5194/essd-14-4365-2022, https://doi.org/10.5194/essd-14-4365-2022, 2022
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Emission sources of methane (CH4) can be distinguished with measurements of CH4 stable isotopes. We present new measurements of isotope signatures of various CH4 sources in Europe, mainly anthropogenic, sampled from 2017 to 2020. The present database also contains the most recent update of the global signature dataset from the literature. The dataset improves CH4 source attribution and the understanding of the global CH4 budget.
Patrick Hupe, Lars Ceranna, Alexis Le Pichon, Robin S. Matoza, and Pierrick Mialle
Earth Syst. Sci. Data, 14, 4201–4230, https://doi.org/10.5194/essd-14-4201-2022, https://doi.org/10.5194/essd-14-4201-2022, 2022
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Sound waves with frequencies below the human hearing threshold can travel long distances through the atmosphere. A global network of sensors records such infrasound to detect clandestine nuclear tests in the atmosphere. These data are generally not public. This study provides four data products based on global infrasound signal detections to make infrasound data available to a broad community. This will advance the use of infrasound observations for scientific studies and civilian applications.
Zexia Duan, Zhiqiu Gao, Qing Xu, Shaohui Zhou, Kai Qin, and Yuanjian Yang
Earth Syst. Sci. Data, 14, 4153–4169, https://doi.org/10.5194/essd-14-4153-2022, https://doi.org/10.5194/essd-14-4153-2022, 2022
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Land–atmosphere interactions over the Yangtze River Delta (YRD) in China are becoming more varied and complex, as the area is experiencing rapid land use changes. In this paper, we describe a dataset of microclimate and eddy covariance variables at four sites in the YRD. This dataset has potential use cases in multiple research fields, such as boundary layer parametrization schemes, evaluation of remote sensing algorithms, and development of climate models in typical East Asian monsoon regions.
Xiaoli Sun, Paul T. Kolbeck, James B. Abshire, Stephan R. Kawa, and Jianping Mao
Earth Syst. Sci. Data, 14, 3821–3833, https://doi.org/10.5194/essd-14-3821-2022, https://doi.org/10.5194/essd-14-3821-2022, 2022
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We describe the measurement and data processing of the atmospheric backscatter profile data by our CO2 Sounder lidar from the 2017 ASCENDS/ABoVE airborne campaign. It is an additional data set from the column average CO2 mixing ratio measurements from laser sounding. It not only helps to interpret the CO2 mixing ratio measurement but also give a standalone data set for atmosphere backscattering study at 1572 nm wavelength.
Lei Li, Yevgeny Derimian, Cheng Chen, Xindan Zhang, Huizheng Che, Gregory L. Schuster, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Christian Matar, Fabrice Ducos, Yana Karol, Benjamin Torres, Ke Gui, Yu Zheng, Yuanxin Liang, Yadong Lei, Jibiao Zhu, Lei Zhang, Junting Zhong, Xiaoye Zhang, and Oleg Dubovik
Earth Syst. Sci. Data, 14, 3439–3469, https://doi.org/10.5194/essd-14-3439-2022, https://doi.org/10.5194/essd-14-3439-2022, 2022
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A climatology of aerosol composition concentration derived from POLDER-3 observations using GRASP/Component is presented. The conceptual specifics of the GRASP/Component approach are in the direct retrieval of aerosol speciation without intermediate retrievals of aerosol optical characteristics. The dataset of satellite-derived components represents scarce but imperative information for validation and potential adjustment of chemical transport models.
Junting Zhong, Xiaoye Zhang, Ke Gui, Jie Liao, Ye Fei, Lipeng Jiang, Lifeng Guo, Liangke Liu, Huizheng Che, Yaqiang Wang, Deying Wang, and Zijiang Zhou
Earth Syst. Sci. Data, 14, 3197–3211, https://doi.org/10.5194/essd-14-3197-2022, https://doi.org/10.5194/essd-14-3197-2022, 2022
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Historical long-term PM2.5 records with high temporal resolution are essential but lacking for research and environmental management. Here, we reconstruct site-based and gridded PM2.5 datasets at 6-hour intervals from 1960 to 2020 that combine visibility, meteorological data, and emissions based on a machine learning model with extracted spatial features. These two PM2.5 datasets will lay the foundation of research studies associated with air pollution, climate change, and aerosol reanalysis.
Fei Jiang, Weimin Ju, Wei He, Mousong Wu, Hengmao Wang, Jun Wang, Mengwei Jia, Shuzhuang Feng, Lingyu Zhang, and Jing M. Chen
Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, https://doi.org/10.5194/essd-14-3013-2022, 2022
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A 10-year (2010–2019) global monthly terrestrial NEE dataset (GCAS2021) was inferred from the GOSAT ACOS v9 XCO2 product. It shows strong carbon sinks over eastern N. America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia. It has good quality and can reflect the impacts of extreme climates and large-scale climate anomalies on carbon fluxes well. We believe that this dataset can contribute to regional carbon budget assessment and carbon dynamics research.
Leonardo Hoinaski, Thiago Vieira Vasques, Camilo Bastos Ribeiro, and Bianca Meotti
Earth Syst. Sci. Data, 14, 2939–2949, https://doi.org/10.5194/essd-14-2939-2022, https://doi.org/10.5194/essd-14-2939-2022, 2022
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In Brazil, goods are essentially transported by a growing vehicular fleet. However, the atmospheric emissions of this prime source of air pollution are still unknown in most places. In this paper, we present the BRAzilian Vehicular Emissions inventory Software (BRAVES) database, containing detailed information on vehicular emissions of multiple types of air pollutants and covering the entire Brazilian territory. These data are crucial to understanding the air pollution in Brazil.
Enza Di Tomaso, Jerónimo Escribano, Sara Basart, Paul Ginoux, Francesca Macchia, Francesca Barnaba, Francesco Benincasa, Pierre-Antoine Bretonnière, Arnau Buñuel, Miguel Castrillo, Emilio Cuevas, Paola Formenti, María Gonçalves, Oriol Jorba, Martina Klose, Lucia Mona, Gilbert Montané Pinto, Michail Mytilinaios, Vincenzo Obiso, Miriam Olid, Nick Schutgens, Athanasios Votsis, Ernest Werner, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2785–2816, https://doi.org/10.5194/essd-14-2785-2022, https://doi.org/10.5194/essd-14-2785-2022, 2022
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MONARCH reanalysis of desert dust aerosols extends the existing observation-based information for mineral dust monitoring by providing 3-hourly upper-air, surface and total column key geophysical variables of the dust cycle over Northern Africa, the Middle East and Europe, at a 0.1° horizontal resolution in a rotated grid, from 2007 to 2016. This work provides evidence of the high accuracy of this data set and its suitability for air quality and health and climate service applications.
Jed O. Kaplan and Katie Hong-Kiu Lau
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-88, https://doi.org/10.5194/essd-2022-88, 2022
Revised manuscript accepted for ESSD
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Global lightning strokes are recorded continuously by a network of ground-based stations. We consolidated these point observations into map form and provide these as electronic datasets for research purposes. Here we extend our dataset to include lightning observations from 2021.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Jukka-Pekka Jalkanen, Elisa Majamäki, Lasse Johansson, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2521–2552, https://doi.org/10.5194/essd-14-2521-2022, https://doi.org/10.5194/essd-14-2521-2022, 2022
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To control the spread of the COVID-19 disease, European governments implemented mobility restriction measures that resulted in an unprecedented drop in anthropogenic emissions. This work presents a dataset of emission adjustment factors that allows quantifying changes in 2020 European primary emissions per country and pollutant sector at the daily scale. The resulting dataset can be used as input in modelling studies aiming at quantifying the impact of COVID-19 on air quality levels.
Elsa Real, Florian Couvidat, Anthony Ung, Laure Malherbe, Blandine Raux, Alicia Gressent, and Augustin Colette
Earth Syst. Sci. Data, 14, 2419–2443, https://doi.org/10.5194/essd-14-2419-2022, https://doi.org/10.5194/essd-14-2419-2022, 2022
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This paper describes a 16-year (2000–2015) dataset of air pollution concentrations and air quality indicators over France combining background measurements and modeling. Hourly concentrations and regulatory indicators of NO2, O3, PM10 and PM2.5 are produced with 4 km spatial resolution. The overall dataset has been cross-validated and showed overall very good results. We hope that this open-access publication will facilitate further studies on the impacts of air pollution.
Vanessa C. Monteiro, Natasha L. Miles, Scott J. Richardson, Zachary Barkley, Bernd J. Haupt, David Lyon, Benjamin Hmiel, and Kenneth J. Davis
Earth Syst. Sci. Data, 14, 2401–2417, https://doi.org/10.5194/essd-14-2401-2022, https://doi.org/10.5194/essd-14-2401-2022, 2022
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We describe a network of five ground-based in situ towers, equipped to measure concentrations of methane, carbon dioxide, hydrogen sulfide, and the isotopic ratio of methane, in the Permian Basin, United States. The main goal is to use methane concentrations with atmospheric models to determine methane emissions from one of the Permian sub-basins. These datasets can improve emissions estimations, leading to best practices in the oil and natural gas industry, and policies for emissions reduction.
Patricia A. Cleary, Gijs de Boer, Joseph P. Hupy, Steven Borenstein, Jonathan Hamilton, Ben Kies, Dale Lawrence, R. Bradley Pierce, Joe Tirado, Aidan Voon, and Timothy Wagner
Earth Syst. Sci. Data, 14, 2129–2145, https://doi.org/10.5194/essd-14-2129-2022, https://doi.org/10.5194/essd-14-2129-2022, 2022
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A field campaign, WiscoDISCO-21, was conducted at the shoreline of Lake Michigan to better understand the role of marine air in pollutants. Two uncrewed aircraft systems were equipped with sensors for meteorological variables and ozone. A Doppler lidar instrument at a ground station measured horizontal and vertical winds. The overlap of observations from multiple instruments allowed for a unique mapping of the meteorology and pollutants as a marine air mass moved over land.
Jianping Guo, Jian Zhang, Tianmeng Chen, Kaixu Bai, Jia Shao, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-150, https://doi.org/10.5194/essd-2022-150, 2022
Revised manuscript accepted for ESSD
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A global continental merged high-resolution (PBLH) dataset with a good accuracy compared to radiosonde is generated via machine learning algorithms, covering a time period from 2011 to 2021 with a 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input while PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Dean Henze, David Noone, and Darin Toohey
Earth Syst. Sci. Data, 14, 1811–1829, https://doi.org/10.5194/essd-14-1811-2022, https://doi.org/10.5194/essd-14-1811-2022, 2022
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The heavy isotope ratios of water vapor can provide information on the movement of water in the atmosphere, such as water vapor's origin of evaporation (e.g., land vs. sea), or detection of prior precipitation in an air mass. This paper presents the water vapor isotope dataset collected via aircraft as part of the NASA ORACLES project. The data are presented to demonstrate their potential for providing a comprehensive perspective on moisture transport in this region.
Xing Yan, Zhou Zang, Zhanqing Li, Nana Luo, Chen Zuo, Yize Jiang, Dan Li, Yushan Guo, Wenji Zhao, Wenzhong Shi, and Maureen Cribb
Earth Syst. Sci. Data, 14, 1193–1213, https://doi.org/10.5194/essd-14-1193-2022, https://doi.org/10.5194/essd-14-1193-2022, 2022
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This study developed a new satellite-based global land daily FMF dataset (Phy-DL FMF) by synergizing the advantages of physical and deep learning methods at a 1° spatial resolution by covering the period from 2001 to 2020. The Phy-DL FMF was extensively evaluated against ground-truth AERONET data and tested on a global scale against conventional satellite-based FMF products to demonstrate its superiority in accuracy.
Linh N. T. Nguyen, Harro A. J. Meijer, Charlotte van Leeuwen, Bert A. M. Kers, Hubertus A. Scheeren, Anna E. Jones, Neil Brough, Thomas Barningham, Penelope A. Pickers, Andrew C. Manning, and Ingrid T. Luijkx
Earth Syst. Sci. Data, 14, 991–1014, https://doi.org/10.5194/essd-14-991-2022, https://doi.org/10.5194/essd-14-991-2022, 2022
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We present 20-year flask sample records of atmospheric CO2, O2, and APO from the stations Lutjewad (the Netherlands), Mace Head (Ireland), and Halley (Antarctica). Data from Lutjewad and Mace Head show similar long-term trends and seasonal cycles, agreeing with measurements from another station (Weybourne, UK). Measurements from Halley agree partly with those conducted by other institutes. From our 2002–2018 Lutjewad and Mace Head records, we find good agreement for global ocean carbon uptake.
Kaixu Bai, Ke Li, Mingliang Ma, Kaitao Li, Zhengqiang Li, Jianping Guo, Ni-Bin Chang, Zhuo Tan, and Di Han
Earth Syst. Sci. Data, 14, 907–927, https://doi.org/10.5194/essd-14-907-2022, https://doi.org/10.5194/essd-14-907-2022, 2022
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The Long-term Gap-free High-resolution Air Pollutant concentration dataset, providing gap-free aerosol optical depth (AOD) and PM2.5 and PM10 concentration with a daily 1 km resolution for 2000–2020 in China, is generated and made publicly available. This is the first long-term gap-free high-resolution aerosol dataset in China and has great potential to trigger multidisciplinary applications in Earth observations, climate change, public health, ecosystem assessment, and environment management.
Matthias Schneider, Benjamin Ertl, Christopher J. Diekmann, Farahnaz Khosrawi, Andreas Weber, Frank Hase, Michael Höpfner, Omaira E. García, Eliezer Sepúlveda, and Douglas Kinnison
Earth Syst. Sci. Data, 14, 709–742, https://doi.org/10.5194/essd-14-709-2022, https://doi.org/10.5194/essd-14-709-2022, 2022
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We present atmospheric H2O, HDO / H2O ratio, N2O, CH4, and HNO3 data generated by the MUSICA IASI processor using thermal nadir spectra measured by the IASI satellite instrument. The data have global daily coverage and are available for the period between October 2014 and June 2021. Multiple possibilities of data reuse are offered by providing each individual data product together with information about retrieval settings and the products' uncertainty and vertical representativeness.
Christian Brümmer, Jeremy J. Rüffer, Jean-Pierre Delorme, Pascal Wintjen, Frederik Schrader, Burkhard Beudert, Martijn Schaap, and Christof Ammann
Earth Syst. Sci. Data, 14, 743–761, https://doi.org/10.5194/essd-14-743-2022, https://doi.org/10.5194/essd-14-743-2022, 2022
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Field campaigns were carried out to investigate the biosphere–atmosphere exchange of selected reactive nitrogen compounds over different land surfaces using two different analytical devices for ammonia and total reactive nitrogen. The datasets improve our understanding of the temporal variability of surface–atmosphere exchange in different ecosystems, thereby providing validation opportunities for inferential models simulating the exchange of reactive nitrogen.
Konstantinos Matthaios Doulgeris, Heikki Lihavainen, Anti-Pekka Hyvärinen, Veli-Matti Kerminen, and David Brus
Earth Syst. Sci. Data, 14, 637–649, https://doi.org/10.5194/essd-14-637-2022, https://doi.org/10.5194/essd-14-637-2022, 2022
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We produced and summarized data sets obtained from two cloud ground-based spectrometers (CAPS and FSSP-100 ground setups) during 8 years of Pallas Cloud Experiment campaigns conducted in autumn from 2004 until 2019 along with several meteorological variables. The campaigns took place in the Finnish sub-Arctic region in a clear environment in temperatures that were usually below zero. This data set provides a helpful contribution to cloud microphysics processes.
Jeroen Kuenen, Stijn Dellaert, Antoon Visschedijk, Jukka-Pekka Jalkanen, Ingrid Super, and Hugo Denier van der Gon
Earth Syst. Sci. Data, 14, 491–515, https://doi.org/10.5194/essd-14-491-2022, https://doi.org/10.5194/essd-14-491-2022, 2022
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This paper presents an 18-year time series for anthropogenic emissions for the main air pollutants in Europe, distinguishing 15 main source categories. It provides a complete overview of emissions to air and is designed to support air quality modelling. The data build where possible on official country total emissions used in the policy processes, but where necessary alternative data were used. The emission data are spatially distributed at high resolution (~ 6 km x 6 km) in a consistent way.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Katerina Sindelarova, Jana Markova, David Simpson, Peter Huszar, Jan Karlicky, Sabine Darras, and Claire Granier
Earth Syst. Sci. Data, 14, 251–270, https://doi.org/10.5194/essd-14-251-2022, https://doi.org/10.5194/essd-14-251-2022, 2022
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Three new datasets of global emissions of biogenic volatile organic compounds (BVOCs) emitted into the atmosphere from terrestrial vegetation were developed for air quality modelling using the Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1) driven by European Centre for Medium-Range Weather Forecasts meteorological reanalyses for the years 2000–2019. The datasets include updates of the isoprene emission factors in Europe and study the impact of land cover change on emissions.
Gijs de Boer, Steven Borenstein, Radiance Calmer, Christopher Cox, Michael Rhodes, Christopher Choate, Jonathan Hamilton, Jackson Osborn, Dale Lawrence, Brian Argrow, and Janet Intrieri
Earth Syst. Sci. Data, 14, 19–31, https://doi.org/10.5194/essd-14-19-2022, https://doi.org/10.5194/essd-14-19-2022, 2022
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This article provides a summary of the collection of atmospheric data over the near-coastal zone upwind of Barbados during the ATOMIC and EUREC4A field campaigns. These data were collected to improve our understanding of the structure and dynamics of the lower atmosphere in the tropical trade-wind regime over the Atlantic Ocean and the influence of that portion of the atmosphere on the development and maintenance of clouds.
Sandip S. Dhomse, Carlo Arosio, Wuhu Feng, Alexei Rozanov, Mark Weber, and Martyn P. Chipperfield
Earth Syst. Sci. Data, 13, 5711–5729, https://doi.org/10.5194/essd-13-5711-2021, https://doi.org/10.5194/essd-13-5711-2021, 2021
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High-quality long-term ozone profile data sets are key to estimating short- and long-term ozone variability. Almost all the satellite (and chemical model) data sets show some kind of bias with respect to each other. This is because of differences in measurement methodologies as well as simplified processes in the models. We use satellite data sets and chemical model output to generate 42 years of ozone profile data sets using a random-forest machine-learning algorithm that is named ML-TOMCAT.
Jie Gong, Dong L. Wu, and Patrick Eriksson
Earth Syst. Sci. Data, 13, 5369–5387, https://doi.org/10.5194/essd-13-5369-2021, https://doi.org/10.5194/essd-13-5369-2021, 2021
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Launched from the International Space Station, the IceCube radiometer orbited the Earth for 15 months and collected the first spaceborne radiance measurements at 874–883 GHz. This channel is uniquely important to fill in the sensitivity gap between operational visible–infrared and microwave remote sensing for atmospheric cloud ice and snow. This paper delivers the IceCube Level 1 radiance data processing algorithm and provides a data quality evaluation and discussion on its scientific merit.
Christopher J. Diekmann, Matthias Schneider, Benjamin Ertl, Frank Hase, Omaira García, Farahnaz Khosrawi, Eliezer Sepúlveda, Peter Knippertz, and Peter Braesicke
Earth Syst. Sci. Data, 13, 5273–5292, https://doi.org/10.5194/essd-13-5273-2021, https://doi.org/10.5194/essd-13-5273-2021, 2021
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The joint analysis of different stable water isotopes in water vapour is a powerful tool for investigating atmospheric moisture pathways. This paper presents a novel global and multi-annual dataset of H2O and HDO in mid-tropospheric water vapour by using data from the satellite sensor Metop/IASI. Due to its unique combination of coverage and resolution in space and time, this dataset is highly promising for studying the hydrological cycle and its representation in weather and climate models.
Anqi Li, Chris Z. Roth, Adam E. Bourassa, Douglas A. Degenstein, Kristell Pérot, Ole Martin Christensen, and Donal P. Murtagh
Earth Syst. Sci. Data, 13, 5115–5126, https://doi.org/10.5194/essd-13-5115-2021, https://doi.org/10.5194/essd-13-5115-2021, 2021
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The nightglow emission originating from the vibrationally excited hydroxyl layer (about 85 km altitude) has been measured by the infrared imager (IRI) on the Odin satellite for more than 15 years. In this study, we document the retrieval steps, the resulting volume emission rates and the layer characteristics. Finally, we use the monthly zonal averages to demonstrate the fidelity of the data set. This unique, long-term data set will be valuable for studying various topics near the mesopause.
Henri Diémoz, Anna Maria Siani, Stefano Casadio, Anna Maria Iannarelli, Giuseppe Rocco Casale, Vladimir Savastiouk, Alexander Cede, Martin Tiefengraber, and Moritz Müller
Earth Syst. Sci. Data, 13, 4929–4950, https://doi.org/10.5194/essd-13-4929-2021, https://doi.org/10.5194/essd-13-4929-2021, 2021
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A 20-year (1996–2017) record of nitrogen dioxide column densities collected in Rome by a Brewer spectrophotometer is presented, together with the novel algorithm employed to re-evaluate the series. The high quality of the data is demonstrated by comparison with reference instrumentation, including a co-located Pandora spectrometer. The data can be used for satellite validation and identification of NO2 trends. The method can be replicated on other instruments of the international Brewer network.
Janusz W. Krzyścin, Bonawentura Rajewska-Więch, and Janusz Jarosławski
Earth Syst. Sci. Data, 13, 4425–4436, https://doi.org/10.5194/essd-13-4425-2021, https://doi.org/10.5194/essd-13-4425-2021, 2021
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The article presents a dataset comprising all manual observations of total column ozone taken at Belsk (Poland) from 23 March 1963 up to 31 December 2019 by the Dobson spectrophotometer. The dataset contains results of ~115 000 intraday measurements. The original data can be used for trend analyses as the instrument's aging has not been detected. For comparative research with other ozone data sources, correction procedures (for adjustments to the Brewer spectrophotometer output) are proposed.
Juan-Carlos Antuña-Marrero, Graham W. Mann, John Barnes, Albeht Rodríguez-Vega, Sarah Shallcross, Sandip S. Dhomse, Giorgio Fiocco, and Gerald W. Grams
Earth Syst. Sci. Data, 13, 4407–4423, https://doi.org/10.5194/essd-13-4407-2021, https://doi.org/10.5194/essd-13-4407-2021, 2021
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The first multi-year stratospheric aerosol lidar dataset was recovered and recalibrated. The vertical profile dataset, January 1964 to August 1965 at Lexington, MA, and July to August 1964 at Fairbanks, AK, provides info on volcanic forcing after the 1963 Agung eruption. Applying two-way transmittance correction to the original dataset reveals data variations, with corrected stratospheric aerosol optical depth (sAOD) highest in 1965 with the highest 532 nm sAOD peak at 0.07 in March 1965.
Luca Palchetti, Marco Barucci, Claudio Belotti, Giovanni Bianchini, Bertrand Cluzet, Francesco D'Amato, Samuele Del Bianco, Gianluca Di Natale, Marco Gai, Dina Khordakova, Alessio Montori, Hilke Oetjen, Markus Rettinger, Christian Rolf, Dirk Schuettemeyer, Ralf Sussmann, Silvia Viciani, Hannes Vogelmann, and Frank Gunther Wienhold
Earth Syst. Sci. Data, 13, 4303–4312, https://doi.org/10.5194/essd-13-4303-2021, https://doi.org/10.5194/essd-13-4303-2021, 2021
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The FIRMOS far-infrared (IR) prototype, developed for the preparation of the ESA FORUM mission, was deployed for the first time at Mt. Zugspitze at 3000 m altitude to measure the far-IR spectrum of atmospheric emissions. The measurements, including co-located radiometers, lidars, radio soundings, weather, and surface properties, provide a unique dataset to study radiative properties of water vapour, cirrus clouds, and snow emissivity over the IR emissions, including the under-explored far-IR.
Kevin Lamy, Thierry Portafaix, Colette Brogniez, Kaisa Lakkala, Mikko R. A. Pitkänen, Antti Arola, Jean-Baptiste Forestier, Vincent Amelie, Mohamed Abdoulwahab Toihir, and Solofoarisoa Rakotoniaina
Earth Syst. Sci. Data, 13, 4275–4301, https://doi.org/10.5194/essd-13-4275-2021, https://doi.org/10.5194/essd-13-4275-2021, 2021
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This paper is about the presentation of the UV-Indien measurement network. This network measures the ultraviolet radiation emitted by the Sun received at the Earth's surface and the clouding above each station. It has been deployed at several sites in the Indian Ocean region representing different environmental conditions. A description of the instruments and their calibration, maintenance, and data processing is presented in this paper along with a valuation of the data quality.
Thierno Doumbia, Claire Granier, Nellie Elguindi, Idir Bouarar, Sabine Darras, Guy Brasseur, Benjamin Gaubert, Yiming Liu, Xiaoqin Shi, Trissevgeni Stavrakou, Simone Tilmes, Forrest Lacey, Adrien Deroubaix, and Tao Wang
Earth Syst. Sci. Data, 13, 4191–4206, https://doi.org/10.5194/essd-13-4191-2021, https://doi.org/10.5194/essd-13-4191-2021, 2021
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Most countries around the world have implemented control measures to combat the spread of the COVID-19 pandemic, resulting in significant changes in economic and personal activities. We developed the CONFORM (COvid-19 adjustmeNt Factors fOR eMissions) dataset to account for changes in emissions during lockdowns. This dataset was created with the intention of being directly applicable to existing global and regional inventories used in chemical transport models.
Greg E. Bodeker, Jan Nitzbon, Jordis S. Tradowsky, Stefanie Kremser, Alexander Schwertheim, and Jared Lewis
Earth Syst. Sci. Data, 13, 3885–3906, https://doi.org/10.5194/essd-13-3885-2021, https://doi.org/10.5194/essd-13-3885-2021, 2021
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Ozone in Earth's atmosphere has undergone significant changes since first measured systematically from space in the late 1970s. The purpose of the paper is to present a new, spatially filled, global total column ozone climate data record spanning from October 1978 to December 2016. The database is compiled from measurements from 17 different satellite-based instruments where offsets and drifts between the instruments have been corrected using ground-based measurements.
Fule Zhang, Jinlong Wang, Mark Baskaran, Qiangqiang Zhong, Yali Wang, Jussi Paatero, and Jinzhou Du
Earth Syst. Sci. Data, 13, 2963–2994, https://doi.org/10.5194/essd-13-2963-2021, https://doi.org/10.5194/essd-13-2963-2021, 2021
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Here we present a global dataset of air concentration and depositional flux measurements of atmospheric 7Be and 210Pb. The dataset could be used to better understand the transport processes of air masses and depositional processes of aerosols. This dataset not only lays a solid foundation to develop better parameterizations contributing to future modeling efforts but also supplies a basic parameter for tracing soil erosion, particle dynamics, and ocean surface process using 7Be and/or 210Pb.
David Brus, Jani Gustafsson, Osku Kemppinen, Gijs de Boer, and Anne Hirsikko
Earth Syst. Sci. Data, 13, 2909–2922, https://doi.org/10.5194/essd-13-2909-2021, https://doi.org/10.5194/essd-13-2909-2021, 2021
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This publication summarizes measurements collected and datasets generated by the Finnish Meteorological Institute and Kansas State University teams during the LAPSE-RATE campaign that took place in San Luis Valley, Colorado, during summer 2018. We provide an overview of the rotorcraft and offer insights into the payloads that were used. We describe the teams’ scientific goals, flight strategies, and the datasets, including a description of the measurement validation techniques applied.
Bo Zheng, Qiang Zhang, Guannan Geng, Cuihong Chen, Qinren Shi, Mengshi Cui, Yu Lei, and Kebin He
Earth Syst. Sci. Data, 13, 2895–2907, https://doi.org/10.5194/essd-13-2895-2021, https://doi.org/10.5194/essd-13-2895-2021, 2021
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Here we report the monthly anthropogenic pollutant emissions in China during the COVID-19 pandemic by using a bottom-up approach based on near-real-time data. The COVID lockdowns were estimated to have reduced China's emissions substantially between January and March in 2020, with the largest reduction in February. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to levels comparable to those of 2019 through December 2020.
Rui Li, Lulu Cui, Yilong Zhao, Wenhui Zhou, and Hongbo Fu
Earth Syst. Sci. Data, 13, 2147–2163, https://doi.org/10.5194/essd-13-2147-2021, https://doi.org/10.5194/essd-13-2147-2021, 2021
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A unique monthly NO3− dataset at 0.25° resolution over China during 2005–2015 was developed by assimilating multi-source variables. The newly developed product featured an excellent cross-validation R2 value (0.78) and relatively lower RMSE (1.19 μg N m−3) and mean absolute error (MAE: 0.81 μg N m−3). The dataset also exhibited relatively robust performance at the spatial and temporal scales. The dataset over China could deepen knowledge of the status of N pollution in China.
Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, Greg E. Bodeker, Leroy J. Bird, Gustavo Olivares, Guy Coulson, Elizabeth Somervell, Woodrow Pattinson, Jonathan Barte, Jan-Niklas Schmidt, Nariefa Abrahim, Adrian J. McDonald, and Peter Kuma
Earth Syst. Sci. Data, 13, 2053–2075, https://doi.org/10.5194/essd-13-2053-2021, https://doi.org/10.5194/essd-13-2053-2021, 2021
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MAPM is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from PM concentration measurements. In support of MAPM, we conducted a winter field campaign in New Zealand. In addition to two types of instruments measuring PM, an array of other meteorological sensors were deployed, measuring temperature and wind speed as well as probing the vertical structure of the lower atmosphere. In this article, we present the measurements taken during this campaign.
Sinikka T. Lennartz, Michael Gauss, Marc von Hobe, and Christa A. Marandino
Earth Syst. Sci. Data, 13, 2095–2110, https://doi.org/10.5194/essd-13-2095-2021, https://doi.org/10.5194/essd-13-2095-2021, 2021
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This study provides a marine emission inventory for the sulphur gases carbonyl sulphide (OCS) and carbon disulphide (CS2), derived from a numerical model of the surface ocean at monthly resolution for the period 2000–2019. Comparison with a database of seaborne observations reveals very good agreement for OCS. Interannual variability in both gases seems to be mainly driven by the amount of chromophoric dissolved organic matter present in surface water.
Cited articles
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Gloor, M., Fan, S.-M., Pacala, S., and Sarmiento, J.: Optimal sampling of the atmosphere for purpose of inverse modeling: A model study, Global Biogeochem. Cy., 14, 407–428, https://doi.org/10.1029/1999GB900052, 2000.
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Maksyutov, S., Takagi, H., Valsala, V. K., Saito, M., Oda, T., Saeki, T., Belikov, D. A., Saito, R., Ito, A., Yoshida, Y., Morino, I., Uchino, O., Andres, R. J., and Yokota, T.: Regional CO2 flux estimates for 2009–2010 based on GOSAT and ground-based CO2 observations, Atmos. Chem. Phys., 13, 9351–9373, https://doi.org/10.5194/acp-13-9351-2013, 2013.
Masarie, K. A. and Tans, P. P.: Extension and integration of atmospheric carbon dioxide data into a globally consistent measurement record, J. Geophys. Res.-Atmos., 100, 11593–11610, 1995.
Nevison, C. D., Mahowald, N. M., Doney, S. C., Lima, I. D., van der Werf, G. R., Randerson, J. T., Baker, D. F., Kasibhatla, P., and McKinley, G. A.: Contribution of ocean, fossil fuel, land biosphere, and biomass burning carbon fluxes to seasonal and interannual variability in atmospheric CO2, J. Geophys. Res., 113, G01010, https://doi.org/10.1029/2007JG000408, 2008.
Niwa, Y., Machida, T., Sawa, Y., Matsueda, H., Schuck, T. J., Brenninkmeijer, C. A. M., Imasu, R., and Satoh, M.: Imposing strong constraints on tropical terrestrial CO2 fluxes using passenger aircraft based measurements, J. Geophys. Res., 117, D11303, https://doi.org/10.1029/2012JD017474, 2012.
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A., Conway, T. J., Masarie, K. A., Miller, J. B., Bruhwiler, L., Petron, G., Hirsch, A., Worthy, D., van der Werf, G., Randerson, J. T., Wennberg, P., Krol, M., and Tans, P. P.: An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker, P. Natl. Acad. Sci., 104, 18925–18930, https://doi.org/10.1073/pnas.0708986104, 2007.
Short summary
Observation Package (ObsPack) is a framework designed to bring together atmospheric greenhouse gas measurements from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. The framework includes a unique distribution stategy designed to improve communication between product users and data providers. The concepts presented are general and may be easily applied to other scientific data.
Observation Package (ObsPack) is a framework designed to bring together atmospheric greenhouse...
