Search

Your search keyword '"Jacobson, Andrew R."' showing total 139 results
Start Over Author "Jacobson, Andrew R."
139 results on '"Jacobson, Andrew R."'

2. Global CO2 gridded flux fields from 14 atmospheric inversions in GCB2023

Author

Luijkx, Ingrid, Chevallier, Frederic, Roedenbeck, Christian, Niwa, Yosuke, Liu, Junjie, Feng, Liang, Palmer, Paul I., Bowman, Kevin, Peters, Wouter, Tian, Xiangjun, Piao, Shilong, Zheng, Bo, Lloret, Zoé, Cozic, Anne, Jacobson, Andrew R., Yun, Jeongmin, Byrne, Brendan, Bloom, Anthony, Jin, Zhe, Wang, Yilong, Zhang, Hongqin, Zhao, Min, Wang, Tao, Ding, Jinzhi, Liu, Zhiqiang, Jiang, Fei, Ju, Weimin, Yang, Dongxu, Chandra, Naveen, Patra, Prabir, Luijkx, Ingrid, Chevallier, Frederic, Roedenbeck, Christian, Niwa, Yosuke, Liu, Junjie, Feng, Liang, Palmer, Paul I., Bowman, Kevin, Peters, Wouter, Tian, Xiangjun, Piao, Shilong, Zheng, Bo, Lloret, Zoé, Cozic, Anne, Jacobson, Andrew R., Yun, Jeongmin, Byrne, Brendan, Bloom, Anthony, Jin, Zhe, Wang, Yilong, Zhang, Hongqin, Zhao, Min, Wang, Tao, Ding, Jinzhi, Liu, Zhiqiang, Jiang, Fei, Ju, Weimin, Yang, Dongxu, Chandra, Naveen, and Patra, Prabir

Abstract

In this file, we include the data from the GCB2023 inversions on 1x1 degrees latitude-longitude. The variables include the prior and posterior land biosphere and ocean carbon fluxes. The land biosphere fluxes have been adjusted to a common fossil fuel emissions dataset (land_flux_only_fossil_cement_adjusted). This allows the inverse estimates to be compared to each other within this ensemble. In this case, we apply a fossil fuel and cement adjustment to account for minor remaining differences to GridFED v2023_1 (this GridFED version includes emissions from cement production and a sink from cement carbonation). For a comparison with bottom-up estimates, further adjustments need to be made, for the lateral fluxes, specifically rivers. In contrast to the version of this file in GCB2022, we do not provide the lateral adjusted inverse estimates, since different lateral flux data sets are available and it depends on the use which lateral adjustment would be applied. We do provide data to make this adjustment for 2 specific datasets for land and ocean: - Lateral river flux adjustment on land as provided by Ronny Lauerwald (The file is based on GlobalNEWS2 for organic C and the weathering CO2 sink after Hartmann et al. 2009 as used in Zscheischler et al 2017. But in this version, the organic C loads after GlobalNEWS are twice rescaled: 1) to the latitudinal pattern from Resplandy et al. (2018 NatGeo) and 2) to a synthesis of global estimates of organic C exports of about 500 Tg C/yr (for this you could for the time being cite Regnier et al. 2013, Nat Geo).). - River adjustment for the oceans from Lacroix et al, as used in RECCAP2.

Published
2024

3. Global Carbon Budget 2023

Author

Friedlingstein, Pierre, primary, O'Sullivan, Michael, additional, Jones, Matthew W., additional, Andrew, Robbie M., additional, Bakker, Dorothee C. E., additional, Hauck, Judith, additional, Landschützer, Peter, additional, Le Quéré, Corinne, additional, Luijkx, Ingrid T., additional, Peters, Glen P., additional, Peters, Wouter, additional, Pongratz, Julia, additional, Schwingshackl, Clemens, additional, Sitch, Stephen, additional, Canadell, Josep G., additional, Ciais, Philippe, additional, Jackson, Robert B., additional, Alin, Simone R., additional, Anthoni, Peter, additional, Barbero, Leticia, additional, Bates, Nicholas R., additional, Becker, Meike, additional, Bellouin, Nicolas, additional, Decharme, Bertrand, additional, Bopp, Laurent, additional, Brasika, Ida Bagus Mandhara, additional, Cadule, Patricia, additional, Chamberlain, Matthew A., additional, Chandra, Naveen, additional, Chau, Thi-Tuyet-Trang, additional, Chevallier, Frédéric, additional, Chini, Louise P., additional, Cronin, Margot, additional, Dou, Xinyu, additional, Enyo, Kazutaka, additional, Evans, Wiley, additional, Falk, Stefanie, additional, Feely, Richard A., additional, Feng, Liang, additional, Ford, Daniel J., additional, Gasser, Thomas, additional, Ghattas, Josefine, additional, Gkritzalis, Thanos, additional, Grassi, Giacomo, additional, Gregor, Luke, additional, Gruber, Nicolas, additional, Gürses, Özgür, additional, Harris, Ian, additional, Hefner, Matthew, additional, Heinke, Jens, additional, Houghton, Richard A., additional, Hurtt, George C., additional, Iida, Yosuke, additional, Ilyina, Tatiana, additional, Jacobson, Andrew R., additional, Jain, Atul, additional, Jarníková, Tereza, additional, Jersild, Annika, additional, Jiang, Fei, additional, Jin, Zhe, additional, Joos, Fortunat, additional, Kato, Etsushi, additional, Keeling, Ralph F., additional, Kennedy, Daniel, additional, Klein Goldewijk, Kees, additional, Knauer, Jürgen, additional, Korsbakken, Jan Ivar, additional, Körtzinger, Arne, additional, Lan, Xin, additional, Lefèvre, Nathalie, additional, Li, Hongmei, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Ma, Lei, additional, Marland, Greg, additional, Mayot, Nicolas, additional, McGuire, Patrick C., additional, McKinley, Galen A., additional, Meyer, Gesa, additional, Morgan, Eric J., additional, Munro, David R., additional, Nakaoka, Shin-Ichiro, additional, Niwa, Yosuke, additional, O'Brien, Kevin M., additional, Olsen, Are, additional, Omar, Abdirahman M., additional, Ono, Tsuneo, additional, Paulsen, Melf, additional, Pierrot, Denis, additional, Pocock, Katie, additional, Poulter, Benjamin, additional, Powis, Carter M., additional, Rehder, Gregor, additional, Resplandy, Laure, additional, Robertson, Eddy, additional, Rödenbeck, Christian, additional, Rosan, Thais M., additional, Schwinger, Jörg, additional, Séférian, Roland, additional, Smallman, T. Luke, additional, Smith, Stephen M., additional, Sospedra-Alfonso, Reinel, additional, Sun, Qing, additional, Sutton, Adrienne J., additional, Sweeney, Colm, additional, Takao, Shintaro, additional, Tans, Pieter P., additional, Tian, Hanqin, additional, Tilbrook, Bronte, additional, Tsujino, Hiroyuki, additional, Tubiello, Francesco, additional, van der Werf, Guido R., additional, van Ooijen, Erik, additional, Wanninkhof, Rik, additional, Watanabe, Michio, additional, Wimart-Rousseau, Cathy, additional, Yang, Dongxu, additional, Yang, Xiaojuan, additional, Yuan, Wenping, additional, Yue, Xu, additional, Zaehle, Sönke, additional, Zeng, Jiye, additional, and Zheng, Bo, additional

Published
2023
Full Text
View/download PDF

5. Supplementary material to "Global Carbon Budget 2023"

Author

Friedlingstein, Pierre, primary, O'Sullivan, Michael, additional, Jones, Matthew W., additional, Andrew, Robbie M., additional, Bakker, Dorothee C. E., additional, Hauck, Judith, additional, Landschützer, Peter, additional, Le Quéré, Corinne, additional, Luijkx, Ingrid T., additional, Peters, Glen P., additional, Peters, Wouter, additional, Pongratz, Julia, additional, Schwingshackl, Clemens, additional, Sitch, Stephen, additional, Canadell, Josep G., additional, Ciais, Philippe, additional, Jackson, Robert B., additional, Alin, Simone R., additional, Anthoni, Peter, additional, Barbero, Leticia, additional, Bates, Nicholas R., additional, Becker, Meike, additional, Bellouin, Nicolas, additional, Decharme, Bertrand, additional, Bopp, Laurent, additional, Brasika, Ida Bagus Mandhara, additional, Cadule, Patricia, additional, Chamberlain, Matthew A., additional, Chandra, Naveen, additional, Chau, Thi-Tuyet-Trang, additional, Chevallier, Frédéric, additional, Chini, Louise P., additional, Cronin, Margot, additional, Dou, Xinyu, additional, Enyo, Kazutaka, additional, Evans, Wiley, additional, Falk, Stefanie, additional, Feely, Richard A., additional, Feng, Liang, additional, Ford, Daniel. J., additional, Gasser, Thomas, additional, Ghattas, Josefine, additional, Gkritzalis, Thanos, additional, Grassi, Giacomo, additional, Gregor, Luke, additional, Gruber, Nicolas, additional, Gürses, Özgür, additional, Harris, Ian, additional, Hefner, Matthew, additional, Heinke, Jens, additional, Houghton, Richard A., additional, Hurtt, George C., additional, Iida, Yosuke, additional, Ilyina, Tatiana, additional, Jacobson, Andrew R., additional, Jain, Atul, additional, Jarníková, Tereza, additional, Jersild, Annika, additional, Jiang, Fei, additional, Jin, Zhe, additional, Joos, Fortunat, additional, Kato, Etsushi, additional, Keeling, Ralph F., additional, Kennedy, Daniel, additional, Klein Goldewijk, Kees, additional, Knauer, Jürgen, additional, Korsbakken, Jan Ivar, additional, Körtzinger, Arne, additional, Lan, Xin, additional, Lefèvre, Nathalie, additional, Li, Hongmei, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Ma, Lei, additional, Marland, Greg, additional, Mayot, Nicolas, additional, McGuire, Patrick C., additional, McKinley, Galen A., additional, Meyer, Gesa, additional, Morgan, Eric J., additional, Munro, David R., additional, Nakaoka, Shin-Ichiro, additional, Niwa, Yosuke, additional, O'Brien, Kevin M., additional, Olsen, Are, additional, Omar, Abdirahman M., additional, Ono, Tsuneo, additional, Paulsen, Melf E., additional, Pierrot, Denis, additional, Pocock, Katie, additional, Poulter, Benjamin, additional, Powis, Carter M., additional, Rehder, Gregor, additional, Resplandy, Laure, additional, Robertson, Eddy, additional, Rödenbeck, Christian, additional, Rosan, Thais M., additional, Schwinger, Jörg, additional, Séférian, Roland, additional, Smallman, T. Luke, additional, Smith, Stephen M., additional, Sospedra-Alfonso, Reinel, additional, Sun, Qing, additional, Sutton, Adrienne J., additional, Sweeney, Colm, additional, Takao, Shintaro, additional, Tans, Pieter P., additional, Tian, Hanqin, additional, Tilbrook, Bronte, additional, Tsujino, Hiroyuki, additional, Tubiello, Francesco, additional, van der Werf, Guido R., additional, van Ooijen, Erik, additional, Wanninkhof, Rik, additional, Watanabe, Michio, additional, Wimart-Rousseau, Cathy, additional, Yang, Dongxu, additional, Yang, Xiaojuan, additional, Yuan, Wenping, additional, Yue, Xu, additional, Zaehle, Sönke, additional, Zeng, Jiye, additional, and Zheng, Bo, additional

Published
2023
Full Text
View/download PDF

7. National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake

Author

Byrne, Brendan, primary, Baker, David F., additional, Basu, Sourish, additional, Bertolacci, Michael, additional, Bowman, Kevin W., additional, Carroll, Dustin, additional, Chatterjee, Abhishek, additional, Chevallier, Frédéric, additional, Ciais, Philippe, additional, Cressie, Noel, additional, Crisp, David, additional, Crowell, Sean, additional, Deng, Feng, additional, Deng, Zhu, additional, Deutscher, Nicholas M., additional, Dubey, Manvendra K., additional, Feng, Sha, additional, García, Omaira E., additional, Griffith, David W. T., additional, Herkommer, Benedikt, additional, Hu, Lei, additional, Jacobson, Andrew R., additional, Janardanan, Rajesh, additional, Jeong, Sujong, additional, Johnson, Matthew S., additional, Jones, Dylan B. A., additional, Kivi, Rigel, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Maksyutov, Shamil, additional, Miller, John B., additional, Miller, Scot M., additional, Morino, Isamu, additional, Notholt, Justus, additional, Oda, Tomohiro, additional, O'Dell, Christopher W., additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Patra, Prabir K., additional, Peiro, Hélène, additional, Petri, Christof, additional, Philip, Sajeev, additional, Pollard, David F., additional, Poulter, Benjamin, additional, Remaud, Marine, additional, Schuh, Andrew, additional, Sha, Mahesh K., additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sweeney, Colm, additional, Té, Yao, additional, Tian, Hanqin, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, Warneke, Thorsten, additional, Worden, John R., additional, Wunch, Debra, additional, Yao, Yuanzhi, additional, Yun, Jeongmin, additional, Zammit-Mangion, Andrew, additional, and Zeng, Ning, additional

Published
2023
Full Text
View/download PDF

8. Global Carbon Budget 2023

Author

Friedlingstein, Pierre, O'Sullivan, Michael, Jones, Matthew W., Andrew, Robbie M., Bakker, Dorothee C. E., Hauck, Judith, Landschützer, Peter, Le Quéré, Corinne, Luijkx, Ingrid T., Peters, Glen P., Peters, Wouter, Pongratz, Julia, Schwingshackl, Clemens, Sitch, Stephen, Canadell, Josep G., Ciais, Philippe, Jackson, Robert B., Alin, Simone R., Anthoni, Peter, Barbero, Leticia, Bates, Nicholas R., Becker, Meike, Bellouin, Nicolas, Decharme, Bertrand, Bopp, Laurent, Brasika, Ida Bagus Mandhara, Cadule, Patricia, Chamberlain, Matthew A., Chandra, Naveen, Chau, Thi-Tuyet-Trang, Chevallier, Frédéric, Chini, Louise P., Cronin, Margot, Dou, Xinyu, Enyo, Kazutaka, Evans, Wiley, Falk, Stefanie, Feely, Richard A., Feng, Liang, Ford, Daniel J., Gasser, Thomas, Ghattas, Josefine, Gkritzalis, Thanos, Grassi, Giacomo, Gregor, Luke, Gruber, Nicolas, Gürses, Özgür, Harris, Ian, Hefner, Matthew, Heinke, Jens, Houghton, Richard A., Hurtt, George C., Iida, Yosuke, Ilyina, Tatiana, Jacobson, Andrew R., Jain, Atul, Jarníková, Tereza, Jersild, Annika, Jiang, Fei, Jin, Zhe, Joos, Fortunat, Kato, Etsushi, Keeling, Ralph F., Kennedy, Daniel, Klein Goldewijk, Kees, Knauer, Jürgen, Korsbakken, Jan Ivar, Körtzinger, Arne, Lan, Xin, Lefèvre, Nathalie, Li, Hongmei, Liu, Junjie, Liu, Zhiqiang, Ma, Lei, Marland, Greg, Mayot, Nicolas, McGuire, Patrick C., McKinley, Galen A., Meyer, Gesa, Morgan, Eric J., Munro, David R., Nakaoka, Shin-Ichiro, Niwa, Yosuke, O'Brien, Kevin M., Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Paulsen, Melf, Pierrot, Denis, Pocock, Katie, Poulter, Benjamin, Powis, Carter M., Rehder, Gregor, Resplandy, Laure, Robertson, Eddy, Rödenbeck, Christian, Rosan, Thais M., Schwinger, Jörg, Séférian, Roland, Smallman, T. Luke, Smith, Stephen M., Sospedra-Alfonso, Reinel, Sun, Qing, Sutton, Adrienne J., Sweeney, Colm, Takao, Shintaro, Tans, Pieter P., Tian, Hanqin, Tilbrook, Bronte, Tsujino, Hiroyuki, Tubiello, Francesco, van der Werf, Guido R., van Ooijen, Erik, Wanninkhof, Rik, Watanabe, Michio, Wimart-Rousseau, Cathy, Yang, Dongxu, Yang, Xiaojuan, Yuan, Wenping, Yue, Xu, Zaehle, Sönke, Zeng, Jiye, Zheng, Bo, Friedlingstein, Pierre, O'Sullivan, Michael, Jones, Matthew W., Andrew, Robbie M., Bakker, Dorothee C. E., Hauck, Judith, Landschützer, Peter, Le Quéré, Corinne, Luijkx, Ingrid T., Peters, Glen P., Peters, Wouter, Pongratz, Julia, Schwingshackl, Clemens, Sitch, Stephen, Canadell, Josep G., Ciais, Philippe, Jackson, Robert B., Alin, Simone R., Anthoni, Peter, Barbero, Leticia, Bates, Nicholas R., Becker, Meike, Bellouin, Nicolas, Decharme, Bertrand, Bopp, Laurent, Brasika, Ida Bagus Mandhara, Cadule, Patricia, Chamberlain, Matthew A., Chandra, Naveen, Chau, Thi-Tuyet-Trang, Chevallier, Frédéric, Chini, Louise P., Cronin, Margot, Dou, Xinyu, Enyo, Kazutaka, Evans, Wiley, Falk, Stefanie, Feely, Richard A., Feng, Liang, Ford, Daniel J., Gasser, Thomas, Ghattas, Josefine, Gkritzalis, Thanos, Grassi, Giacomo, Gregor, Luke, Gruber, Nicolas, Gürses, Özgür, Harris, Ian, Hefner, Matthew, Heinke, Jens, Houghton, Richard A., Hurtt, George C., Iida, Yosuke, Ilyina, Tatiana, Jacobson, Andrew R., Jain, Atul, Jarníková, Tereza, Jersild, Annika, Jiang, Fei, Jin, Zhe, Joos, Fortunat, Kato, Etsushi, Keeling, Ralph F., Kennedy, Daniel, Klein Goldewijk, Kees, Knauer, Jürgen, Korsbakken, Jan Ivar, Körtzinger, Arne, Lan, Xin, Lefèvre, Nathalie, Li, Hongmei, Liu, Junjie, Liu, Zhiqiang, Ma, Lei, Marland, Greg, Mayot, Nicolas, McGuire, Patrick C., McKinley, Galen A., Meyer, Gesa, Morgan, Eric J., Munro, David R., Nakaoka, Shin-Ichiro, Niwa, Yosuke, O'Brien, Kevin M., Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Paulsen, Melf, Pierrot, Denis, Pocock, Katie, Poulter, Benjamin, Powis, Carter M., Rehder, Gregor, Resplandy, Laure, Robertson, Eddy, Rödenbeck, Christian, Rosan, Thais M., Schwinger, Jörg, Séférian, Roland, Smallman, T. Luke, Smith, Stephen M., Sospedra-Alfonso, Reinel, Sun, Qing, Sutton, Adrienne J., Sweeney, Colm, Takao, Shintaro, Tans, Pieter P., Tian, Hanqin, Tilbrook, Bronte, Tsujino, Hiroyuki, Tubiello, Francesco, van der Werf, Guido R., van Ooijen, Erik, Wanninkhof, Rik, Watanabe, Michio, Wimart-Rousseau, Cathy, Yang, Dongxu, Yang, Xiaojuan, Yuan, Wenping, Yue, Xu, Zaehle, Sönke, Zeng, Jiye, and Zheng, Bo

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (E-FOS) are based on energy statistics and cement production data, while emissions from land-use change (E-LUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (G(ATM)) is computed from the annual changes in concentration. The ocean CO2 sink (S-OCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO(2) products. The terrestrial CO2 sink (S-LAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (B-IM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as +/- 1 sigma. For the year 2022, E-FOS increased by 0.9% relative to 2021, with fossil emissions at 9.9 +/- 0.5 GtC yr(-1) (10.2 +/- 0.5 GtC yr(-1) when the cement carbonation sink is not included), and E-LUC was 1.2 +/- 0.7 GtC yr(-1), for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 +/- 0.8 GtC yr(-1) (40.7 +/- 3.2 GtCO(2) yr(-1)). Also, for 2022, G(ATM) was 4.6 +/- 0.2 GtC yr(-1) (2.18 +/- 0.1 ppm yr(-1); ppm denotes parts per million), S-OCEAN was 2.8 +/- 0.4 GtC yr(-1)

Published
2023
Full Text
View/download PDF

9. National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake

Author

Byrne, Brendan, Baker, David F., Basu, Sourish, Bertolacci, Michael, Bowman, Kevin W., Carroll, Dustin, Chatterjee, Abhishek, Chevallier, Frédéric, Ciais, Philippe, Cressie, Noel, Crisp, David, Crowell, Sean, Deng, Feng, Deng, Zhu, Deutscher, Nicholas Michael, Dubey, Manvendra K., Feng, Sha, García Rodríguez, Omaira Elena, Griffith, David W. T., Herkommer, Benedikt, Hu, Lei, Jacobson, Andrew R., Janardanan, Rajesh, Jeong, Sujong, Johnson, Matthew S., Jones, Dylan B. A., Kivi, Rigel, Liu, Junjie, Liu, Zhiqiang, Maksyutov, Shamil, Miller, John B., Morino, Isamu, Notholt, Justus, Oda, Tomohiro, O'Dell, Christopher, Oh, Young-Suk, Ohyama, Hirofumi, Patra, Prabir K., Peiro, Hélène, Petri, Christof, Philip, Sajeev, Pollard, David F., Poulter, Benjamin, Remaud, Marine, Schuh, Andrew, Sha, Mahesh Kumar, Shiomi, Kei, Strong, Kimberly, Sweeney, Colm, Te, Yao, Tian, Hanqin, Velazco, Voltaire A., Vrekoussis, Mihalis, Warneke, Thorsten, Worden, John, Wunch, Debra, Yao, Yuamzhi, Yun, Jeongmin, Zammit Mangion, Andrew, and Zeng, Ning

Subjects
Temperature increase, Carbon dioxide emission, Climate change
Abstract

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries’ carbon budgets. These estimates are based on “top-down” NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (XCO2 ) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with “bottom-up” estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1◦ × 1 ◦ gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites’ (CEOS) website: https://doi.org/10.48588/npf6-sw92 (Byrne et al., 2022). Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 PgCO2 yr−1 (0.90–1.25 PgC yr−1 ). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems. This research has been supported by the European Commission, Horizon 2020 Framework Programme (CoCO2 (grant no. 958927 856612/EMME-CARE)) and Copernicus Atmosphere Monitoring Service (grant no. CAMS73), the Australian Research Council (grant nos. DP190100180, DE180100203, DP160100598, LE0668470, DP140101552, DP110103118, DP0879468 and FT180100327), the Environmental Restoration and Conservation Agency (grant no. JPMEERF21S20800), the Korea Meteorological Administration (grant no. KMA2018-00320), the National Aeronautics and Space Administration (grant nos. 20-OCOST20-0004, 80NSSC18K0908, 80NSSC18K0976, 80NSSC20K0006, 80NSSC21K1068, 80NSSC21K1073, 80NSSC21K1077, 80NSSC21K1080, 80HQTR21T0069, NAG512247, NNG05GD07G, NNH17ZDA001N-OCO2 and NNX15AG93G), and the National Oceanic and Atmospheric Administration (grant no. NA18OAR4310266).

Published
2023

12. Evaluating Global Atmospheric Inversions of Terrestrial Net Ecosystem Exchange CO 2 Over North America on Seasonal and Sub‐Continental Scales

Author

Cui, Yu Yan, primary, Zhang, Li, additional, Jacobson, Andrew R., additional, Johnson, Matthew S., additional, Philip, Sajeev, additional, Baker, David, additional, Chevallier, Frederic, additional, Schuh, Andrew E., additional, Liu, Junjie, additional, Crowell, Sean, additional, Peiro, Hélène E., additional, Deng, Feng, additional, Basu, Sourish, additional, and Davis, Kenneth J., additional

Published
2022
Full Text
View/download PDF

13. Uncertainty in parameterized convection remains a key obstacle for estimating surface fluxes of carbon dioxide.

Author

Schuh, Andrew E. and Jacobson, Andrew R.

Subjects
TRACE gases, GENERAL circulation model, ATMOSPHERIC boundary layer, CARBON dioxide, ATMOSPHERIC transport, VERTICAL motion
Abstract

The analysis of observed atmospheric trace-gas mole fractions to infer surface sources and sinks of chemical species relies heavily on simulated atmospheric transport. The chemical transport models (CTMs) used in flux-inversion models are commonly configured to reproduce the atmospheric transport of a general circulation model (GCM) as closely as possible. CTMs generally have the dual advantages of computational efficiency and improved tracer conservation compared to their parent GCMs, but they usually simplify the representations of important processes. This is especially the case for high-frequency vertical motions associated with diffusion and convection. Using common-flux experiments, we quantify the importance of parameterized vertical processes for explaining systematic differences in tracer transport between two commonly used CTMs. We find that differences in modeled column-average CO2 are strongly correlated with the differences in the models' convection. The parameterization of diffusion is more important near the surface due to its role in representing planetary-boundary-layer (PBL) mixing. Accordingly, simulated near-surface in situ measurements are more strongly impacted by this process than are simulated total-column averages. Both diffusive and convective vertical mixing tend to ventilate the lower atmosphere, so near-surface measurements may only constrain the net vertical mixing and not the balance between these two processes. Remote-sensing-based retrievals of total-column CO2 , with their increased sensitivity to convection, may provide important new constraints on parameterized vertical motions. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

14. Supplementary material to "National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the Global Stocktake"

Author

Byrne, Brendan, primary, Baker, David F., additional, Basu, Sourish, additional, Bertolacci, Michael, additional, Bowman, Kevin W., additional, Carroll, Dustin, additional, Chatterjee, Abhishek, additional, Chevallier, Frédéric, additional, Ciais, Philippe, additional, Cressie, Noel, additional, Crisp, David, additional, Crowell, Sean, additional, Deng, Feng, additional, Deng, Zhu, additional, Deutscher, Nicholas M., additional, Dubey, Manvendra, additional, Feng, Sha, additional, García, Omaira, additional, Griffith, David W. T., additional, Herkommer, Benedikt, additional, Hu, Lei, additional, Jacobson, Andrew R., additional, Janardanan, Rajesh, additional, Jeong, Sujong, additional, Johnson, Matthew S., additional, Jones, Dylan B. A., additional, Kivi, Rigel, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Maksyutov, Shamil, additional, Miller, John B., additional, Miller, Scot M., additional, Morino, Isamu, additional, Notholt, Justus, additional, Oda, Tomohiro, additional, O’Dell, Christopher W., additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Patra, Prabir K., additional, Peiro, Hélène, additional, Petri, Christof, additional, Philip, Sajeev, additional, Pollard, David F., additional, Poulter, Benjamin, additional, Remaud, Marine, additional, Schuh, Andrew, additional, Sha, Mahesh K., additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sweeney, Colm, additional, Té, Yao, additional, Tian, Hanqin, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, Warneke, Thorsten, additional, Worden, John R., additional, Wunch, Debra, additional, Yao, Yuanzhi, additional, Yun, Jeongmin, additional, Zammit-Mangion, Andrew, additional, and Zeng, Ning, additional

Published
2022
Full Text
View/download PDF

15. National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the Global Stocktake

Author

Byrne, Brendan, primary, Baker, David F., additional, Basu, Sourish, additional, Bertolacci, Michael, additional, Bowman, Kevin W., additional, Carroll, Dustin, additional, Chatterjee, Abhishek, additional, Chevallier, Frédéric, additional, Ciais, Philippe, additional, Cressie, Noel, additional, Crisp, David, additional, Crowell, Sean, additional, Deng, Feng, additional, Deng, Zhu, additional, Deutscher, Nicholas M., additional, Dubey, Manvendra, additional, Feng, Sha, additional, García, Omaira, additional, Griffith, David W. T., additional, Herkommer, Benedikt, additional, Hu, Lei, additional, Jacobson, Andrew R., additional, Janardanan, Rajesh, additional, Jeong, Sujong, additional, Johnson, Matthew S., additional, Jones, Dylan B. A., additional, Kivi, Rigel, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Maksyutov, Shamil, additional, Miller, John B., additional, Miller, Scot M., additional, Morino, Isamu, additional, Notholt, Justus, additional, Oda, Tomohiro, additional, O’Dell, Christopher W., additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Patra, Prabir K., additional, Peiro, Hélène, additional, Petri, Christof, additional, Philip, Sajeev, additional, Pollard, David F., additional, Poulter, Benjamin, additional, Remaud, Marine, additional, Schuh, Andrew, additional, Sha, Mahesh K., additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sweeney, Colm, additional, Té, Yao, additional, Tian, Hanqin, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, Warneke, Thorsten, additional, Worden, John R., additional, Wunch, Debra, additional, Yao, Yuanzhi, additional, Yun, Jeongmin, additional, Zammit-Mangion, Andrew, additional, and Zeng, Ning, additional

Published
2022
Full Text
View/download PDF

16. Iconic CO 2 Time Series at Risk

Author

HOUWELING, SANDER, BADAWY, BAKR, BAKER, DAVID F., BASU, SOURISH, BELIKOV, DMITRY, BERGAMASCHI, PETER, BOUSQUET, PHILIPPE, BROQUET, GREGOIRE, BUTLER, TIM, CANADELL, JOSEP G., CHEN, JING, CHEVALLIER, FREDERIC, CIAIS, PHILIPPE, COLLATZ, G. JAMES, DENNING, SCOTT, ENGELEN, RICHARD, ENTING, IAN G., FISCHER, MARC L., FRASER, ANNEMARIE, GERBIG, CHRISTOPH, GLOOR, MANUEL, JACOBSON, ANDREW R., JONES, DYLAN B. A., HEIMANN, MARTIN, KHALIL, ASLAM, KAMINSKI, THOMAS, KASIBHATLA, PRASAD S., KRAKAUER, NIR Y., KROL, MAARTEN, MAKI, TAKASHI, MAKSYUTOV, SHAMIL, MANNING, ANDREW, MEESTERS, ANTOON, MILLER, JOHN B., PALMER, PAUL I., PATRA, PRABIR, PETERS, WOUTER, PEYLIN, PHILIPPE, POUSSI, ZEGBEU, PRATHER, MICHAEL J., RANDERSON, JAMES T., RÖCKMANN, THOMAS, RÖDENBECK, CHRISTIAN, SARMIENTO, JORGE L., SCHIMEL, DAVID S., SCHOLZE, MARKO, SCHUH, ANDREW, SUNTHARALINGAM, PARV, TAKAHASHI, TARO, TURNBULL, JOCELYN, YURGANOV, LEONID, and VERMEULEN, ALEX

Published
2012
Full Text
View/download PDF

17. Multi‐Season Evaluation of CO₂ Weather in OCO-2 MIP Models

Author

Zhang, Li, Davis, Kenneth J., Schuh, Andrew E., Jacobson, Andrew R., Pal, Sandip, Cui, Yu Yan, Baker, David, Crowell, Sean, Chevallier, Frederic, Remaud, Marine, Liu, Junjie, Weir, Brad, Philip, Sajeev, Johnson, Matthew S., Deng, Feng, and Basu, Sourish

Abstract

The ability of current global models to simulate the transport of CO₂ by mid-latitude, synoptic-scale weather systems (i.e., CO₂ weather) is important for inverse estimates of regional and global carbon budgets but remains unclear without comparisons to targeted measurements. Here, we evaluate ten models that participated in the Orbiting Carbon Observatory-2 model intercomparison project (OCO-2 MIP version 9) with intensive aircraft measurements collected from the Atmospheric Carbon Transport (ACT)-America mission. We quantify model-data differences in the spatial variability of CO₂ mole fractions, mean winds, and boundary layer depths in 27 mid-latitude cyclones spanning four seasons over the central and eastern United States. We find that the OCO-2 MIP models are able to simulate observed CO₂ frontal differences with varying degrees of success in summer and spring, and most underestimate frontal differences in winter and autumn. The models may underestimate the observed boundary layer-to-free troposphere CO₂ differences in spring and autumn due to model errors in boundary layer height. Attribution of the causes of model biases in other seasons remains elusive. Transport errors, prior fluxes, and/or inversion algorithms appear to be the primary cause of these biases since model performance is not highly sensitive to the CO₂ data used in the inversion. The metrics presented here provide new benchmarks regarding the ability of atmospheric inversion systems to reproduce the CO₂ structure of mid-latitude weather systems. Controlled experiments are needed to link these metrics more directly to the accuracy of regional or global flux estimates.

Published
2022

19. Four years of global carbon cycle observed from the Orbiting Carbon Observatory 2 (OCO-2) version 9 and in situ data and comparison to OCO-2 version 7

Author

Peiro, Hélène, primary, Crowell, Sean, additional, Schuh, Andrew, additional, Baker, David F., additional, O'Dell, Chris, additional, Jacobson, Andrew R., additional, Chevallier, Frédéric, additional, Liu, Junjie, additional, Eldering, Annmarie, additional, Crisp, David, additional, Deng, Feng, additional, Weir, Brad, additional, Basu, Sourish, additional, Johnson, Matthew S., additional, Philip, Sajeev, additional, and Baker, Ian, additional

Published
2022
Full Text
View/download PDF

20. Multi‐Season Evaluation of CO2 Weather in OCO‐2 MIP Models

Author

Zhang, Li, primary, Davis, Kenneth J., additional, Schuh, Andrew E., additional, Jacobson, Andrew R., additional, Pal, Sandip, additional, Cui, Yu Yan, additional, Baker, David, additional, Crowell, Sean, additional, Chevallier, Frederic, additional, Remaud, Marine, additional, Liu, Junjie, additional, Weir, Brad, additional, Philip, Sajeev, additional, Johnson, Matthew S., additional, Deng, Feng, additional, and Basu, Sourish, additional

Published
2022
Full Text
View/download PDF

24. Uncertainty in Parameterized Convection Remains a Key Obstacle for Estimating Surface Fluxes of Carbon Dioxide.

Author

Schuh, Andrew E. and Jacobson, Andrew R.

Abstract

The analysis of observed atmospheric trace gas mole fractions to infer surface sources and sinks of chemical species relies heavily on simulated atmospheric transport. The chemical transport models (CTMs) used in flux inversion models are commonly configured to reproduce the atmospheric transport of a general circulation model (GCM) as closely as possible. CTMs generally have the dual advantages of computational efficiency and improved tracer conservation compared to their parent GCMs, but they usually simplify the representations of important processes. This is especially the case for high-frequency vertical motions associated with diffusion and convection. Using common-flux experiments, we quantify the importance of parameterized vertical processes for explaining systematic differences in tracer transport between two commonly-used CTMs. We find that differences in convection are strongly correlated with the differences in modeled column CO2. The parameterization of diffusion is more important near the surface due to its role in representing PBL mixing. Accordingly, near-surface in situ measurements are more strongly impacted by this process than are total-column retrievals. Both diffusive and convective vertical mixing tend to ventilate the lower atmosphere, so near-surface measurements may only constrain the net vertical mixing and not the balance between these two processes. Remote sensing-based retrievals of total column CO2, with their increased sensitivity to convection, may provide important new constraints on parameterized vertical motions. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

25. Evaluating Global Atmospheric Inversions of Terrestrial Net Ecosystem Exchange CO2 Over North America on Seasonal and Sub‐Continental Scales.

Author

Cui, Yu Yan, Zhang, Li, Jacobson, Andrew R., Johnson, Matthew S., Philip, Sajeev, Baker, David, Chevallier, Frederic, Schuh, Andrew E., Liu, Junjie, Crowell, Sean, Peiro, Hélène E., Deng, Feng, Basu, Sourish, and Davis, Kenneth J.

Subjects
SEASONS, ATMOSPHERE, ATMOSPHERIC carbon dioxide, ATMOSPHERIC transport, CARBON cycle, GOVERNMENT policy on climate change, CARBON dioxide
Abstract

Atmospheric inversion estimates of net ecosystem exchange (NEE) of CO2 are increasingly relevant to climate policy. We evaluated sub‐continental, seasonal estimates of CO2 NEE from nine global inversion systems that participated in the Orbiting Carbon Observatory‐2 model intercomparison project (OCO‐2 v9 MIP), using 98 research flights conducted over the central and eastern United States from 2016 to 2018 as part of the Atmospheric Carbon and Transport ‐ America mission. We found that the seasonal amplitude of NEE in the central and eastern United States is underestimated in these models and model‐data biases are largest for those inversions with the smallest seasonal flux amplitudes. These results were independent of whether the inversions used satellite or in situ data. The largest NEE biases were observed in the Midwest croplands and eastern forests. Future experiments are needed to determine the causes of the persistent biases and if they are associated with biases in annual flux estimates. Plain Language Summary: The exchange of CO2 between terrestrial ecosystems and the atmosphere is an important component of the Earth's climate system. Atmospheric budgets are used to quantify this exchange globally, but these estimates are difficult to evaluate on a regional basis. We used a unique set of aircraft data to evaluate a set of state‐of‐the‐science estimates of ecosystem‐atmosphere CO2 exchange in temperate North America. Nearly every estimate underestimated the seasonal amplitude of ecosystem‐atmosphere CO2 exchange (net photosynthesis too weak in the summer; respiration too weak in the winter) in this region. The source of atmospheric CO2 data did not influence this finding. More study is needed to determine both the cause of these seasonal biases and the impact of this bias on annual net CO2 flux estimates. Key Points: The seasonal amplitude of net ecosystem exchange (NEE) of CO2 in the central and eastern temperate North America is underestimated in global atmospheric inversionsThe seasonal bias is not significantly different between inversions using OCO‐2 v9 land nadir/glint observations and in situ observationsThe largest NEE biases are observed in U.S. croplands and eastern forests [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

26. Seasonal strength of terrestrial net ecosystem CO2 exchange from North America is underestimated in global inverse modeling

Author

Cui, Yuyan, primary, Zhang, Li, additional, Jacobson, Andrew R, additional, Johnson, Matthew S, additional, Philip, Sajeev, additional, Baker, David, additional, Chevallier, Frederic, additional, Schuh, Andrew E, additional, Liu, Junjie, additional, Crowell, Sean, additional, Peiro, Helene, additional, Deng, Feng, additional, Basu, Sourish, additional, and Davis, Kenneth J, additional

Published
2021
Full Text
View/download PDF

27. Four years of global carbon cycle observed from OCO-2 version 9 and in situ data, and comparison to OCO-2 v7

Author

Peiro, Hélène, primary, Crowell, Sean, additional, Schuh, Andrew, additional, Baker, David F., additional, O'Dell, Chris, additional, Jacobson, Andrew R., additional, Chevallier, Frédéric, additional, Liu, Junjie, additional, Eldering, Annmarie, additional, Crisp, David, additional, Deng, Feng, additional, Weir, Brad, additional, Basu, Sourish, additional, Johnson, Matthew S., additional, Philip, Sajeev, additional, and Baker, Ian, additional

Published
2021
Full Text
View/download PDF

28. Evaluation of CarbonTracker's Inverse Estimates of North American Net Ecosystem Exchange of CO 2 From Different Observing Systems Using ACT‐America Airborne Observations

Author

Cui, Yu Yan, primary, Jacobson, Andrew R., additional, Feng, Sha, additional, Wesloh, Daniel, additional, Barkley, Zachary R., additional, Zhang, Li, additional, Gerken, Tobias, additional, Keller, Klaus, additional, Baker, David, additional, and Davis, Kenneth J, additional

Published
2021
Full Text
View/download PDF

30. Iconic CO2 Time Series at Risk

Author

HOUWELING, SANDER, BADAWY, BAKR, BAKER, DAVID F., BASU, SOURISH, BELIKOV, DMITRY, BERGAMASCHI, PETER, BOUSQUET, PHILIPPE, BROQUET, GREGOIRE, BUTLER, TIM, CANADELL, JOSEP G., CHEN, JING, CHEVALLIER, FREDERIC, CIAIS, PHILIPPE, COLLATZ, JAMES G., DENNING, SCOTT, ENGELEN, RICHARD, ENTING, IAN G., FISCHER, MARC L., FRASER, ANNEMARIE, GERBIG, CHRISTOPH, GLOOR, MANUEL, JACOBSON, ANDREW R., JONES, DYLAN B. A., HEIMANN, MARTIN, KHALIL, ASLAM, KAMINSKI, THOMAS, KASIBHATLA, PRASAD S., KRAKAUER, NIR Y., KROL, MAARTEN, MAKI, TAKASHI, MAKSYUTOV, SHAMIL, MANNING, ANDREW, MEESTERS, ANTOON, MILLER, JOHN B., PALMER, PAUL I., PATRA, PRABIR, PETERS, WOUTER, PEYLIN, PHILIPPE, POUSSI, ZEGBEU, PRATHER, MICHAEL J., RANDERSON, JAMES T., RÖCKMANN, THOMAS, RÖDENBECK, CHRISTIAN, SARMIENTO, JORGE L., SCHIMEL, DAVID S., SCHOLZE, MARKO, SCHUH, ANDREW, SUNTHARALINGAM, PARV, TAKAHASHI, TARO, TURNBULL, JOCELYN, YURGANOV, LEONID, and VERMEULEN, ALEX

Published
2012

31. Multi‐Season Evaluation of CO2 Weather in OCO‐2 MIP Models.

Author

Zhang, Li, Davis, Kenneth J., Schuh, Andrew E., Jacobson, Andrew R., Pal, Sandip, Cui, Yu Yan, Baker, David, Crowell, Sean, Chevallier, Frederic, Remaud, Marine, Liu, Junjie, Weir, Brad, Philip, Sajeev, Johnson, Matthew S., Deng, Feng, and Basu, Sourish

Subjects
ATMOSPHERIC carbon dioxide, CARBON dioxide, WEATHER, ATMOSPHERIC chemistry, CARBON offsetting
Abstract

The ability of current global models to simulate the transport of CO2 by mid‐latitude, synoptic‐scale weather systems (i.e., CO2 weather) is important for inverse estimates of regional and global carbon budgets but remains unclear without comparisons to targeted measurements. Here, we evaluate ten models that participated in the Orbiting Carbon Observatory‐2 model intercomparison project (OCO‐2 MIP version 9) with intensive aircraft measurements collected from the Atmospheric Carbon Transport (ACT)‐America mission. We quantify model‐data differences in the spatial variability of CO2 mole fractions, mean winds, and boundary layer depths in 27 mid‐latitude cyclones spanning four seasons over the central and eastern United States. We find that the OCO‐2 MIP models are able to simulate observed CO2 frontal differences with varying degrees of success in summer and spring, and most underestimate frontal differences in winter and autumn. The models may underestimate the observed boundary layer‐to‐free troposphere CO2 differences in spring and autumn due to model errors in boundary layer height. Attribution of the causes of model biases in other seasons remains elusive. Transport errors, prior fluxes, and/or inversion algorithms appear to be the primary cause of these biases since model performance is not highly sensitive to the CO2 data used in the inversion. The metrics presented here provide new benchmarks regarding the ability of atmospheric inversion systems to reproduce the CO2 structure of mid‐latitude weather systems. Controlled experiments are needed to link these metrics more directly to the accuracy of regional or global flux estimates. Plain Language Summary: Global flux estimate systems use CO2 observations, atmospheric transport models, CO2 flux models (emissions and absorption), and mathematical optimization methods to estimate biosphere‐atmosphere CO2 exchange. Accurate representation of atmospheric transport is important for a reliable optimization of fluxes in these systems. We use intensive aircraft measurements of wind speed, boundary layer height, and horizontal and vertical differences of CO2 concentrations within 27 mid‐latitude cyclones collected by the Atmospheric Carbon Transport (ACT)‐America mission to evaluate the performance of ten global flux estimate systems from the Orbiting Carbon Observatory‐2 model intercomparison project (OCO‐2 MIP). We find the models can simulate observed horizontal CO2 differences between the warm and cold parts of cyclones with different degrees of success in summer and spring, but often underestimate the observed cross‐frontal and vertical differences in CO2 in winter and autumn. The models may underestimate the CO2 differences between the boundary layer and the free troposphere due to model errors in boundary layer height and surface fluxes. These weather‐oriented CO2 metrics provide benchmarks for testing simulations of the CO2 structure within cyclones. Future efforts are needed to link these metrics more directly to the accuracy of CO2 flux estimates. Key Points: Global inversion systems are able to simulate observed CO2 frontal differences but with varying degrees of successMost global inversion systems underestimate dormant‐season frontal and vertical CO2 differencesInversion systems appear to explain more of the model‐data differences in CO2 weather metrics than CO2 data sources [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

32. The 2015–2016 Carbon Cycle As Seen from OCO-2 and the Global In Situ Network

Author

Crowell, Sean, Baker, David, Schuh, Andrew, Basu, Sourish, Jacobson, Andrew R., Chevallier, Frederic, Liu, Junjie, Deng, Feng, Feng, Liang, Chatterjee, Abhishek, Crisp, David, Eldering, Annmarie, Jones, Dylan B., Mckain, Kathryn, Miller, John, Nassar, Ray, Oda, Tomohiro, O'dell, Christopher, Palmer, Paul I., Schimel, David, Stephens, Britton, and Sweeney, Colm

Abstract

The Orbiting Carbon Observatory-2 has been on orbit since 2014, and its global coverage holds the potential to reveal new information about the carbon cycle through the use of top-down atmospheric inversion methods combined with column average CO2 retrievals. We employ a large ensemble of atmospheric inversions utilizing different transport models, data assimilation techniques and prior flux distributions in order to quantify the satellite-informed fluxes from OCO-2 Version 7r land observations and their uncertainties at continental scales. Additionally, we use in situ measurements to provide a baseline against which to compare the satellite-constrained results. We find that within ensemble spread, in situ observations and satellite retrievals constrain a similar global total carbon sink of 3.7 ± 0.5 PgC, and 1.5 ± 0.6 PgC per year for global land, for the 2015–2016 annual mean. This agreement breaks down on smaller regions, and we discuss the differences between the experiments. Of particular interest is the difference between the different assimilation constraints in the tropics, with the largest differences occurring in tropical Africa, which could be an indication of the global perturbation from the 2015–2016 El Niño. Evaluation of posterior concentrations using TCCON and aircraft observations gives some limited insight into the quality of the different assimilation constraints, but the lack of such data in the tropics inhibits our ability to make strong conclusions there.

Published
2019
Full Text
View/download PDF

33. Four years of global carbon cycle observed from OCO-2 version 9 and in situ data, and comparison to OCO-2 v7.

Author

Peiro, Hélène, Crowell, Sean, Schuh, Andrew, Baker, David F., O'Dell, Chris, Jacobson, Andrew R., Chevallier, Frédéric, Liu, Junjie, Eldering, Annmarie, Crisp, David, Deng, Feng, Weir, Brad, Basu, Sourish, Johnson, Matthew S., Philip, Sajeev, and Baker, Ian

Abstract

The Orbiting Carbon Observatory 2 (OCO-2) satellite has been provided information to estimate carbon dioxide (CO2) fluxes at global and regional scales since 2014 through the combination of CO2 retrievals with top-down atmospheric inversion methods. Column average CO2 dry air mole fraction retrievals has been constantly improved. A bias correction has been applied in the OCO-2 version 9 retrievals compared to the previous OCO-2 version 7r improving data accuracy and coverage. We study an ensemble of ten atmospheric inversions all characterized by different transport models, data assimilation algorithm and prior fluxes using first OCO-2 v7 in 2015-2016 and then OCO-2 version 9 land observations for the longer period 2015- 2018. Inversions assimilating in situ (IS) measurements have been also used to provide a baseline against which to compare the satellite-driven results. The times series at different scales (going from global to regional scales) of the models emissions are analyzed and compared to each experiments using either OCO-2 or IS data. We then evaluate the inversion ensemble based on dataset from TCCON, aircraft, and in-situ observations, all independent from assimilated data. While we find a similar constraint of global total carbon emissions between the ensemble spread using IS and both OCO-2 retrievals, differences between the two retrieval versions appear over regional scales and particularly in tropical Africa. A difference in the carbon budget between v7 and v9 is found over this region which seems to show the impact of corrections applied in retrievals. However, the lack of data in the tropics limits our conclusions and the estimation of carbon emissions over tropical Africa require further analysis. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

34. Evaluation of CarbonTracker's Inverse Estimates of North American Net Ecosystem Exchange of CO2 From Different Observing Systems Using ACT‐America Airborne Observations.

Author

Cui, Yu Yan, Jacobson, Andrew R., Feng, Sha, Wesloh, Daniel, Barkley, Zachary R., Zhang, Li, Gerken, Tobias, Keller, Klaus, Baker, David, and Davis, Kenneth J

Subjects
CARBON dioxide, CARBON cycle, ATMOSPHERIC carbon dioxide, STANDARD deviations, LAGRANGIAN functions, ECOSYSTEMS
Abstract

Quantification of regional terrestrial carbon dioxide (CO2) fluxes is critical to our understanding of the carbon cycle. We evaluate inverse estimates of net ecosystem exchange (NEE) of CO2 fluxes in temperate North America, and their sensitivity to the observational data used to drive the inversions. Specifically, we consider the state‐of‐the‐science CarbonTracker global inversion system, which assimilates (a) in situ measurements (IS), (b) the Orbiting Carbon Observatory‐2 (OCO‐2) v9 column CO2 (XCO2) retrievals over land (LNLG), (c) OCO‐2 v9 XCO2 retrievals ocean‐glint (OG), and (d) a combination of all these observational constraints (LNLGOGIS). We use independent CO2 observations from the Atmospheric Carbon and Transport (ACT)—America aircraft mission to evaluate the inversions. We diagnose errors in the flux estimates using the differences between modeled and observed biogenic CO2 mole fractions, influence functions from a Lagrangian transport model, Bayesian inference, and root‐mean‐square error (RMSE) and bias metrics. The IS fluxes have the smallest RMSE among the four products, followed by LNLG. Both IS and LNLG outperform the OG and LNLGOGIS inversions with regard to RMSE. Regional errors do not differ markedly across the four sets of posterior fluxes. The CarbonTracker inversions appear to overestimate the seasonal cycle of NEE in the Midwest and Western Canada, and overestimate dormant season NEE across the Central and Eastern US. The CarbonTracker inversions may overestimate annual NEE in the Central and Eastern US. The success of the LNLG inversion with respect to independent observations bodes well for satellite‐based inversions in regions with more limited in situ observing networks. Plain Language Summary: Biological CO2 fluxes, an important component of the earth's climate system, remain uncertain, especially at continental and sub‐continental spatial domains. Different global CO2 observing systems imply significantly different net biological fluxes of CO2. We use independent CO2 measurements from an extensive multi‐seasonal aircraft campaign to evaluate biological CO2 flux estimates derived from four different observational systems entered into a common data analysis system. The observations include both ground and satellite‐based measurements. We found that one of the the satellite‐based CO2 estimates performs nearly as well as the estimates based on ground‐based measurements. This suggests that the satellite data may serve to estimate regional variations in biological CO2 fluxes in portions of the globe with more limited ground‐based observing networks. The inversions all appear to overestimate dormant season release of biological CO2 to the atmosphere, thus may underestimate the net uptake of CO2 by ecosystems in the Central and Eastern United States. Key Points: In situ measurements and the land nadir/land glint inversions are the most reliable products of CarbonTracker in temperate North America, superior to ocean‐glint or LNLGOGIS inversionsErrors in these CarbonTracker regional flux estimates are not strongly dependent on the observational data sourcesCarbonTracker overestimates seasonal net ecosystem exchange (NEE) for the Eastern and Central US, thus the annual NEE may underestimate continental uptake of CO2 [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

35. The 2015–2016 carbon cycle as seen from OCO-2 and the global in situ network

Author

Crowell, Sean, primary, Baker, David, additional, Schuh, Andrew, additional, Basu, Sourish, additional, Jacobson, Andrew R., additional, Chevallier, Frederic, additional, Liu, Junjie, additional, Deng, Feng, additional, Feng, Liang, additional, McKain, Kathryn, additional, Chatterjee, Abhishek, additional, Miller, John B., additional, Stephens, Britton B., additional, Eldering, Annmarie, additional, Crisp, David, additional, Schimel, David, additional, Nassar, Ray, additional, O'Dell, Christopher W., additional, Oda, Tomohiro, additional, Sweeney, Colm, additional, Palmer, Paul I., additional, and Jones, Dylan B. A., additional

Published
2019
Full Text
View/download PDF

36. Quantifying the Impact of Atmospheric Transport Uncertainty on CO2 Surface Flux Estimates

Author

Schuh, Andrew E., primary, Jacobson, Andrew R., additional, Basu, Sourish, additional, Weir, Brad, additional, Baker, David, additional, Bowman, Kevin, additional, Chevallier, Frédéric, additional, Crowell, Sean, additional, Davis, Kenneth J., additional, Deng, Feng, additional, Denning, Scott, additional, Feng, Liang, additional, Jones, Dylan, additional, Liu, Junjie, additional, and Palmer, Paul I., additional

Published
2019
Full Text
View/download PDF

37. The 2015–2016 Carbon Cycle As Seen from OCO-2 and the Global <i>In Situ</i> Network

Author

Crowell, Sean, primary, Baker, David, additional, Schuh, Andrew, additional, Basu, Sourish, additional, Jacobson, Andrew R., additional, Chevallier, Frederic, additional, Liu, Junjie, additional, Deng, Feng, additional, Feng, Liang, additional, Chatterjee, Abhishek, additional, Crisp, David, additional, Eldering, Annmarie, additional, Jones, Dylan B., additional, McKain, Kathryn, additional, Miller, John, additional, Nassar, Ray, additional, Oda, Tomohiro, additional, O'Dell, Christopher, additional, Palmer, Paul I., additional, Schimel, David, additional, Stephens, Britton, additional, and Sweeney, Colm, additional

Published
2019
Full Text
View/download PDF

38. Data-based estimates of the ocean carbon sink variability - results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

Author

Rödenbeck, Christian, Bakker, Dorothee C. E., Gruber, Nicolas, Iida, Yosuke, Jacobson, Andrew R., Jones, Steve, Landschützer, Peter, Metzl, Nicolas, Nakaoka, Shin-Ichiro, Olsen, Are, Park, Geun-Ha, Peylin, Philippe, Rodgers, Keith B., Sasse, Tristan P., Schuster, Ute, Shutler, James D., Valsala, Vinu, Wanninkhof, Rik H., Zeng, Jiye, Max-Planck-Institut, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), University of Colorado [Boulder], Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), University of East Anglia [Norwich] (UEA), Équipe CO2 (E-CO2), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), National Institute for Environmental Studies (NIES), University of Bergen (UiB), Natural Decisions, Pty Ltd, University of Texas Southwestern Medical Center [Dallas], University of New South Wales [Sydney] (UNSW), University of Exeter, Indian Institute of Tropical Meteorology (IITM), National Oceanic and Atmospheric Administration (NOAA), EGU, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636))

Subjects
[PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2016

40. Data-based estimates of the ocean carbon sink variability – First results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

Author

Rödenbeck, Christian, Bakker, Dorothee C. E., Gruber, Nicolas, Iida, Yosuke, Jacobson, Andrew R., Jones, S., Metzl, Nicolas, Nakaoka, Shin-Ichiro, Olsen, Are, Park, Geun-Ha, Peylin, Philippe, Rodgers, Keith B., Sasse, T. P., Schuster, Ute, Shutler, J. D., Valsala, Vinu, Wanninkhof, Rik H., Zeng, J., Max-Planck-Institut für Biogeochemie (MPI-BGC), University of East Anglia [Norwich] (UEA), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Japan Meteorological Agency (JMA), University of Colorado [Boulder], Institut de Physique de Rennes (IPR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Équipe CO2 (E-CO2), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), National Institute for Environmental Studies (NIES), University of Leeds, Chemistry Department [Massachusetts Institute of Technology], Massachusetts Institute of Technology (MIT), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Princeton University, University of New South Wales [Sydney] (UNSW), College of Life and Environmental Sciences [Exeter], University of Exeter, Centre for Climate Change Research [Pune] (CCCR), Indian Institute of Tropical Meteorology (IITM), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

Subjects
[PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

41. Quantifying the Impact of Atmospheric Transport Uncertainty on CO2 Surface Flux Estimates.

Author

Schuh, Andrew E., Jacobson, Andrew R., Basu, Sourish, Weir, Brad, Baker, David, Bowman, Kevin, Chevallier, Frédéric, Crowell, Sean, Davis, Kenneth J., Deng, Feng, Denning, Scott, Feng, Liang, Jones, Dylan, Liu, Junjie, and Palmer, Paul I.

Subjects
ATMOSPHERIC transport, ATMOSPHERIC methane, FLUX (Energy), VERTICAL motion, CARBON cycle, SULFUR hexafluoride
Abstract

We show that transport differences between two commonly used global chemical transport models, GEOS‐Chem and TM5, lead to systematic space‐time differences in modeled distributions of carbon dioxide and sulfur hexafluoride. The distribution of differences suggests inconsistencies between the transport simulated by the models, most likely due to the representation of vertical motion. We further demonstrate that these transport differences result in systematic differences in surface CO2 flux estimated by a collection of global atmospheric inverse models using TM5 and GEOS‐Chem and constrained by in situ and satellite observations. While the impact on inferred surface fluxes is most easily illustrated in the magnitude of the seasonal cycle of surface CO2 exchange, it is the annual carbon budgets that are particularly relevant for carbon cycle science and policy. We show that inverse model flux estimates for large zonal bands can have systematic biases of up to 1.7 PgC/year due to large‐scale transport uncertainty. These uncertainties will propagate directly into analysis of the annual meridional CO2 flux gradient between the tropics and northern midlatitudes, a key metric for understanding the location, and more importantly the processes, responsible for the annual global carbon sink. The research suggests that variability among transport models remains the largest source of uncertainty across global flux inversion systems and highlights the importance both of using model ensembles and of using independent constraints to evaluate simulated transport. Key Points: There are systematic differences in transport between two commonly used chemical transport models, TM5 and GEOS‐ChemThese systematic differences lead to significant and meaningful posterior flux uncertainties in atmospheric CO2 flux inversions [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

43. Quantifying the Impact of Atmospheric Transport Uncertainty on CO2Surface Flux Estimates

Author

Schuh, Andrew E., Jacobson, Andrew R., Basu, Sourish, Weir, Brad, Baker, David, Bowman, Kevin, Chevallier, Frédéric, Crowell, Sean, Davis, Kenneth J., Deng, Feng, Denning, Scott, Feng, Liang, Jones, Dylan, Liu, Junjie, and Palmer, Paul I.

Abstract

We show that transport differences between two commonly used global chemical transport models, GEOS‐Chem and TM5, lead to systematic space‐time differences in modeled distributions of carbon dioxide and sulfur hexafluoride. The distribution of differences suggests inconsistencies between the transport simulated by the models, most likely due to the representation of vertical motion. We further demonstrate that these transport differences result in systematic differences in surface CO2flux estimated by a collection of global atmospheric inverse models using TM5 and GEOS‐Chem and constrained by in situ and satellite observations. While the impact on inferred surface fluxes is most easily illustrated in the magnitude of the seasonal cycle of surface CO2exchange, it is the annual carbon budgets that are particularly relevant for carbon cycle science and policy. We show that inverse model flux estimates for large zonal bands can have systematic biases of up to 1.7 PgC/year due to large‐scale transport uncertainty. These uncertainties will propagate directly into analysis of the annual meridional CO2flux gradient between the tropics and northern midlatitudes, a key metric for understanding the location, and more importantly the processes, responsible for the annual global carbon sink. The research suggests that variability among transport models remains the largest source of uncertainty across global flux inversion systems and highlights the importance both of using model ensembles and of using independent constraints to evaluate simulated transport. There are systematic differences in transport between two commonly used chemical transport models, TM5 and GEOS‐ChemThese systematic differences lead to significant and meaningful posterior flux uncertainties in atmospheric CO2flux inversions

Published
2019
Full Text
View/download PDF

44. Oceanic sources, sinks, and transport of atmospheric CO2

Author

Gruber, Nicolas, Gloor, Manuel, Mikaloff Fletcher, Sara E., Doney, Scott C., Dutkiewicz, Stephanie, Follows, Michael J., Gerber, Markus, Jacobson, Andrew R., Joos, Fortunat, Lindsay, Keith, Menemenlis, Dimitris, Mouchet, Anne, Müller, Simon A., Sarmiento, Jorge L., and Takahashi, Taro

Subjects
carbon flux, anthropogenic CO2, air-sea carbon flux
Abstract

We synthesize estimates of the contemporary net air-sea CO2 flux on the basis of an inversion of interior ocean carbon observations using a suite of 10 ocean general circulation models (Mikaloff Fletcher et al., 2006, 2007) and compare them to estimates based on a new climatology of the air-sea difference of the partial pressure of CO2 (pCO(2)) (Takahashi et al., 2008). These two independent flux estimates reveal a consistent description of the regional distribution of annual mean sources and sinks of atmospheric CO2 for the decade of the 1990s and the early 2000s with differences at the regional level of generally less than 0.1 Pg C a(-1). This distribution is characterized by outgassing in the tropics, uptake in midlatitudes, and comparatively small fluxes in the high latitudes. Both estimates point toward a small(similar to -0.3 Pg C a(-1)) contemporary CO2 sink in the Southern Ocean (south of 44 degrees S), a result of the near cancellation between a substantial outgassing of natural CO2 and a strong uptake of anthropogenic CO2. A notable exception in the generally good agreement between the two estimates exists within the Southern Ocean: the ocean inversion suggests a relatively uniform uptake, while the pCO(2)-based estimate suggests strong uptake in the region between 58 degrees S and 44 degrees S, and a source in the region south of 58 degrees S. Globally and for a nominal period between 1995 and 2000, the contemporary net air-sea flux of CO2 is estimated to be -1.7 +/- 0.4 Pg C a(-1) (inversion) and -1.4 +/- 0.7 Pg C a(-1) (pCO(2)-climatology), respectively, consisting of an outgassing flux of river-derived carbon of similar to+0.5 Pg C a(-1), and an uptake flux of anthropogenic carbon of -2.2 +/- 0.3 Pg C a(-1) (inversion) and -1.9 +/- 0.7 Pg C a(-1) (pCO(2)-climatology). The two flux estimates also imply a consistent description of the contemporary meridional transport of carbon with southward ocean transport throughout most of the Atlantic basin, and strong equatorward convergence in the Indo-Pacific basins. Both transport estimates suggest a small hemispheric asymmetry with a southward transport of between -0.2 and -0.3 Pg C a(-1) across the equator. While the convergence of these two independent estimates is encouraging and suggests that it is now possible to provide relatively tight constraints for the net air-sea CO2 fluxes at the regional basis, both studies are limited by their lack of consideration of long-term changes in the ocean carbon cycle, such as the recent possible stalling in the expected growth of the Southern Ocean carbon sink.

Published
2009
Full Text
View/download PDF

45. Impact of Siberian observations on the optimization of surface CO2 flux.

Author

Jinwoong Kim, Hyun Mee Kim, Chun-Ho Cho, Kyung-On Boo, Jacobson, Andrew R., Sasakawa, Motoki, Machida, Toshinobu, Arshinov, Mikhail, and Fedoseev, Nikolay

Subjects
CLIMATOLOGY, CARBON dioxide & the environment, UNCERTAINTY, PROCESS optimization
Abstract

To investigate the effect of additional CO2 observations in the Siberia region on the Asian and global surface CO2 flux analyses, two experiments using different observation data sets were performed for 2000-2009. One experiment was conducted using a data set that includes additional observations of Siberian tower measurements (Japan-Russia Siberian Tall Tower Inland Observation Network: JRSTATION), and the other experiment was conducted using a data set without the above additional observations. The results show that the global balance of the sources and sinks of surface CO2 fluxes was maintained for both experiments with and without the additional observations. While the magnitude of the optimized surface CO2 flux uptake and flux uncertainty in Siberia decreased from -1.17 ± 0.93 to -0.77 ± 0.70 PgC yr-1, the magnitude of the optimized surface CO2 flux uptake in the other regions (e.g., Europe) of the Northern Hemisphere (NH) land increased for the experiment with the additional observations, which affect the longitudinal distribution of the total NH sinks. This change was mostly caused by changes in the magnitudes of surface CO2 flux in June and July. The observation impact measured by uncertainty reduction and self-sensitivity tests shows that additional observations provide useful information on the estimated surface CO2 flux. The average uncertainty reduction of the conifer forest of Eurasian boreal (EB) is 29.1% and the average self-sensitivities at the JR-STATION sites are approximately 60% larger than those at the towers in North America. It is expected that the Siberian observations play an important role in estimating surface CO2 flux in the NH land (e.g., Siberia and Europe) in the future. [ABSTRACT FROM AUTHOR]

Published
2017
Full Text
View/download PDF

48. Using altimetry to help explain patchy changes in hydrographic carbon measurements

Author

Rodgers, Keith B., Key, Robert M., Gnanadesikan, Anand, Sarmiento, Jorge L., Aumont, Olivier, Bopp, Laurent, Doney, Scott C., Dunne, John P., Glover, David M., Ishida, Akio, Ishii, Masao, Jacobson, Andrew R., Monaco, Claire Lo, Maier-Reimer, Ernst, Mercier, Herlé, Metzl, Nicolas, Perez, Fiz F., Rios, Aida F., Wanninkhof, Rik, Wetzel, Patrick, Winn, Christopher D., Yamanaka, Yasuhiro, Rodgers, Keith B., Key, Robert M., Gnanadesikan, Anand, Sarmiento, Jorge L., Aumont, Olivier, Bopp, Laurent, Doney, Scott C., Dunne, John P., Glover, David M., Ishida, Akio, Ishii, Masao, Jacobson, Andrew R., Monaco, Claire Lo, Maier-Reimer, Ernst, Mercier, Herlé, Metzl, Nicolas, Perez, Fiz F., Rios, Aida F., Wanninkhof, Rik, Wetzel, Patrick, Winn, Christopher D., and Yamanaka, Yasuhiro

Abstract

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C09013, doi:10.1029/2008JC005183., Here we use observations and ocean models to identify mechanisms driving large seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved oxygen (O2) in the upper ocean. We begin with observations linking variations in upper ocean DIC and O2 inventories with changes in the physical state of the ocean. Models are subsequently used to address the extent to which the relationships derived from short-timescale (6 months to 2 years) repeat measurements are representative of variations over larger spatial and temporal scales. The main new result is that convergence and divergence (column stretching) attributed to baroclinic Rossby waves can make a first-order contribution to DIC and O2 variability in the upper ocean. This results in a close correspondence between natural variations in DIC and O2 column inventory variations and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic part of the natural variability in the climate system and is elevated even in the absence of significant interannual variability in climate mode indices. The close correspondence between SSH and both DIC and O2 column inventories for many regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in reducing uncertainty in separating natural and anthropogenic DIC signals (using measurements from Climate Variability and Predictability's CO2/Repeat Hydrography program)., This report was prepared by K.B.R. under awards NA17RJ2612 and NA08OAR4320752, which includes support through the NOAA Office of Climate Observations (OCO). The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the U.S. Department of Commerce. Support for K.B.R. was also provided by the Carbon Mitigation Initiative (CMI) through the support of BP, Amaco, and Ford. R.M.K. was supported by NOAA grants NA17RJ2612, NA08OAR4320752, and NA08OAR4310820. F.F.P. was supported by the European Union FP6 CARBOOCEAN Integrated project (contract 51176), the French OVIDE project, and the Spanish Salvador de Madariaga program (PR2006– 0523). This work was also supported by the European NOCES project (EVK2-CT201-00134). Y.Y. and A.I. are partly supported by CREST, JST of Japan. The long-term OISO observational program in the South Indian Ocean is supported by the following three French institutes: INSU (Institut National des Sciences de l’Univers), IPSL (Institute Pierre-Simon Laplace), and IPEV (Institut Paul-Emile Victor).

Published
2010

49. Inverse estimates of anthropogenic CO2 uptake, transport, and storage by the ocean

Author

Mikaloff Fletcher, Sara E., Gruber, Nicolas, Jacobson, Andrew R., Doney, Scott C., Dutkiewicz, Stephanie, Gerber, Markus, Follows, Michael J., Joos, Fortunat, Lindsay, Keith, Menemenlis, Dimitris, Mouchet, Anne, Muller, Simon A., Sarmiento, Jorge L., Mikaloff Fletcher, Sara E., Gruber, Nicolas, Jacobson, Andrew R., Doney, Scott C., Dutkiewicz, Stephanie, Gerber, Markus, Follows, Michael J., Joos, Fortunat, Lindsay, Keith, Menemenlis, Dimitris, Mouchet, Anne, Muller, Simon A., and Sarmiento, Jorge L.

Abstract

Author Posting. © American Geophysical Union, 2006. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 20 (2006): GB2002, doi:10.1029/2005GB002530., Regional air-sea fluxes of anthropogenic CO2 are estimated using a Green's function inversion method that combines data-based estimates of anthropogenic CO2 in the ocean with information about ocean transport and mixing from a suite of Ocean General Circulation Models (OGCMs). In order to quantify the uncertainty associated with the estimated fluxes owing to modeled transport and errors in the data, we employ 10 OGCMs and three scenarios representing biases in the data-based anthropogenic CO2 estimates. On the basis of the prescribed anthropogenic CO2 storage, we find a global uptake of 2.2 ± 0.25 Pg C yr−1, scaled to 1995. This error estimate represents the standard deviation of the models weighted by a CFC-based model skill score, which reduces the error range and emphasizes those models that have been shown to reproduce observed tracer concentrations most accurately. The greatest anthropogenic CO2 uptake occurs in the Southern Ocean and in the tropics. The flux estimates imply vigorous northward transport in the Southern Hemisphere, northward cross-equatorial transport, and equatorward transport at high northern latitudes. Compared with forward simulations, we find substantially more uptake in the Southern Ocean, less uptake in the Pacific Ocean, and less global uptake. The large-scale spatial pattern of the estimated flux is generally insensitive to possible biases in the data and the models employed. However, the global uptake scales approximately linearly with changes in the global anthropogenic CO2 inventory. Considerable uncertainties remain in some regions, particularly the Southern Ocean., This research was financially supported by the National Aeronautics and Space Administration under grant NAG5- 12528. N. G. also acknowledges support by the National Science Foundation (OCE-0137274). Climate and Environmental Physics, Bern acknowledges support by the European Union through the Integrated Project CarboOcean and the Swiss National Science Foundation.

Published
2010

50. Correction to “Using altimetry to help explain patchy changes in hydrographic carbon measurements”

Author

Rodgers, Keith B., Key, Robert M., Gnanadesikan, Anand, Sarmiento, Jorge L., Aumont, Olivier, Bopp, Laurent, Doney, Scott C., Dunne, John P., Glover, David M., Ishida, Akio, Ishii, Masao, Jacobson, Andrew R., Monaco, Claire Lo, Maier-Reimer, Ernst, Mercier, Herlé, Metzl, Nicolas, Perez, Fiz F., Rios, Aida F., Wanninkhof, Rik, Wetzel, Patrick, Winn, Christopher D., Yamanaka, Yasuhiro, Rodgers, Keith B., Key, Robert M., Gnanadesikan, Anand, Sarmiento, Jorge L., Aumont, Olivier, Bopp, Laurent, Doney, Scott C., Dunne, John P., Glover, David M., Ishida, Akio, Ishii, Masao, Jacobson, Andrew R., Monaco, Claire Lo, Maier-Reimer, Ernst, Mercier, Herlé, Metzl, Nicolas, Perez, Fiz F., Rios, Aida F., Wanninkhof, Rik, Wetzel, Patrick, Winn, Christopher D., and Yamanaka, Yasuhiro

Abstract

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C12099, doi:10.1029/2009JC005835.

Published
2010

Catalog

Books, media, physical & digital resources
See catalog results