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Amanda R. Fay

Other affiliations: University of Wisconsin-Madison
Bio: Amanda R. Fay is an academic researcher from Lamont–Doherty Earth Observatory. The author has contributed to research in topics: Carbon sink & Carbon. The author has an hindex of 14, co-authored 21 publications receiving 788 citations. Previous affiliations of Amanda R. Fay include University of Wisconsin-Madison.

Papers
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Journal ArticleDOI
TL;DR: In this paper, trends in oceanic and atmospheric carbon dioxide concentrations converge on a multidecadal timescale, according to an analysis of North Atlantic surface waters, and they show that oceanic uptake of carbon dioxide reduces the rate at which anthropogenic carbon accumulates in the atmosphere.
Abstract: Oceanic uptake of carbon dioxide reduces the rate at which anthropogenic carbon accumulates in the atmosphere. Trends in oceanic and atmospheric carbon dioxide concentrations converge on a multidecadal timescale, according to an analysis of North Atlantic surface waters.

141 citations

Journal ArticleDOI
TL;DR: In this paper, trends in globally observed surface ocean partial pressure of CO2 (pCO2s.ocean) are evaluated over 16 gyre-scale biomes covering the globe.
Abstract: [1] Ocean carbon uptake substantially reduces the rate of anthropogenic carbon accumulation in the atmosphere and thus slows global climate change. In the interest of understanding how this ocean carbon sink has responded to climate variability and climate change in recent decades, trends in globally observed surface ocean partial pressure of CO2 (pCO2s.ocean) are evaluated over 16 gyre-scale biomes covering the globe. Trends from decadal to multidecadal timescales between 1981 and 2010 are considered. On decadal timescales, pCO2s.ocean trends have been of variable magnitude and sensitive to the chosen start and end years. On longer time frames, several regions of the tropics and subtropics display pCO2s.ocean trends that are parallel to or shallower than trends in atmospheric pCO2, consistent with the ocean's long-term response to carbon accumulation in the atmosphere and with the supply of waters with low anthropogenic carbon from the deep ocean. Data are too sparse in the high latitudes to determine this long-term response. In many biomes, pCO2s.ocean trends steeper than atmospheric trends do occur on shorter timescales, which is consistent with forcing by climatic variability. In the Southern Ocean, the influence of a positive trend in the Southern Annular Mode has waned and the carbon sink has strengthened since the early 2000s. In North Atlantic subtropical and equatorial biomes, warming has become a significant and persistent contributor to the observed increase in pCO2s.ocean since the mid-2000s. This long-term warming, previously attributed to both multidecadal climate variability and anthropogenic forcing, is beginning to reduce ocean carbon uptake.

131 citations

Journal ArticleDOI
TL;DR: In this article, the authors quantify the net sea-air CO2 flux, for the first time, across different methodologies for consistent time and space scales for the Atlantic and Arctic basins.
Abstract: The Atlantic and Arctic Oceans are critical components of the global carbon cycle Here we quantify the net sea–air CO2 flux, for the first time, across different methodologies for consistent time and space scales for the Atlantic and Arctic basins We present the long-term mean, seasonal cycle, interannual variability and trends in sea–air CO2 flux for the period 1990 to 2009, and assign an uncertainty to each We use regional cuts from global observations and modeling products, specifically a pCO2-based CO2 flux climatology, flux estimates from the inversion of oceanic and atmospheric data, and results from six ocean biogeochemical models Additionally, we use basin-wide flux estimates from surface ocean pCO2 observations based on two distinct methodologies Our estimate of the contemporary sea–air flux of CO2 (sum of anthropogenic and natural components) by the Atlantic between 40° S and 79° N is −049 ± 005 Pg C yr−1, and by the Arctic it is −012 ± 006 Pg C yr−1, leading to a combined sea–air flux of −061 ± 006 Pg C yr−1 for the two decades (negative reflects ocean uptake) We do find broad agreement amongst methodologies with respect to the seasonal cycle in the subtropics of both hemispheres, but not elsewhere Agreement with respect to detailed signals of interannual variability is poor, and correlations to the North Atlantic Oscillation are weaker in the North Atlantic and Arctic than in the equatorial region and southern subtropics Linear trends for 1995 to 2009 indicate increased uptake and generally correspond between methodologies in the North Atlantic, but there is disagreement amongst methodologies in the equatorial region and southern subtropics

127 citations

Journal ArticleDOI
TL;DR: In this article, the authors defined 17 open-ocean biomes classified from four observational data sets: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl a), ice fraction, and maximum mixed layer depth (maxMLD) on a 1° × 1° grid.
Abstract: . Large-scale studies of ocean biogeochemistry and carbon cycling have often partitioned the ocean into regions along lines of latitude and longitude despite the fact that spatially more complex boundaries would be closer to the true biogeography of the ocean. Herein, we define 17 open-ocean biomes classified from four observational data sets: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl a), ice fraction, and maximum mixed layer depth (maxMLD) on a 1° × 1° grid (available at doi:10.1594/PANGAEA.828650 ). By considering interannual variability for each input, we create dynamic ocean biome boundaries that shift annually between 1998 and 2010. Additionally we create a core biome map, which includes only the grid cells that do not change biome assignment across the 13 years of the time-varying biomes. These biomes can be used in future studies to distinguish large-scale ocean regions based on biogeochemical function.

113 citations

Journal ArticleDOI
25 Feb 2016-Nature
TL;DR: It is unlikely that changes in the rate of anthropogenic carbon uptake can be directly observed in most oceanic regions at present, but that this may become possible between 2020 and 2050 in some regions.
Abstract: The ocean has absorbed 41 per cent of all anthropogenic carbon emitted as a result of fossil fuel burning and cement manufacture. The magnitude and the large-scale distribution of the ocean carbon sink is well quantified for recent decades. In contrast, temporal changes in the oceanic carbon sink remain poorly understood. It has proved difficult to distinguish between air-to-sea carbon flux trends that are due to anthropogenic climate change and those due to internal climate variability. Here we use a modelling approach that allows for this separation, revealing how the ocean carbon sink may be expected to change throughout this century in different oceanic regions. Our findings suggest that, owing to large internal climate variability, it is unlikely that changes in the rate of anthropogenic carbon uptake can be directly observed in most oceanic regions at present, but that this may become possible between 2020 and 2050 in some regions.

107 citations


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Book ChapterDOI
01 Jan 2014
TL;DR: For base year 2010, anthropogenic activities created ~210 (190 to 230) TgN of reactive nitrogen Nr from N2 as discussed by the authors, which is at least 2 times larger than the rate of natural terrestrial creation of ~58 Tg N (50 to 100 Tg nr yr−1) (Table 6.9, Section 1a).
Abstract: For base year 2010, anthropogenic activities created ~210 (190 to 230) TgN of reactive nitrogen Nr from N2. This human-caused creation of reactive nitrogen in 2010 is at least 2 times larger than the rate of natural terrestrial creation of ~58 TgN (50 to 100 TgN yr−1) (Table 6.9, Section 1a). Note that the estimate of natural terrestrial biological fixation (58 TgN yr−1) is lower than former estimates (100 TgN yr−1, Galloway et al., 2004), but the ranges overlap, 50 to 100 TgN yr−1 vs. 90 to 120 TgN yr−1, respectively). Of this created reactive nitrogen, NOx and NH3 emissions from anthropogenic sources are about fourfold greater than natural emissions (Table 6.9, Section 1b). A greater portion of the NH3 emissions is deposited to the continents rather than to the oceans, relative to the deposition of NOy, due to the longer atmospheric residence time of the latter. These deposition estimates are lower limits, as they do not include organic nitrogen species. New model and measurement information (Kanakidou et al., 2012) suggests that incomplete inclusion of emissions and atmospheric chemistry of reduced and oxidized organic nitrogen components in current models may lead to systematic underestimates of total global reactive nitrogen deposition by up to 35% (Table 6.9, Section 1c). Discharge of reactive nitrogen to the coastal oceans is ~45 TgN yr−1 (Table 6.9, Section 1d). Denitrification converts Nr back to atmospheric N2. The current estimate for the production of atmospheric N2 is 110 TgN yr−1 (Bouwman et al., 2013).

1,967 citations

Journal ArticleDOI
Pierre Friedlingstein1, Pierre Friedlingstein2, Michael O'Sullivan1, Matthew W. Jones3, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters4, Wouter Peters5, Julia Pongratz6, Julia Pongratz7, Stephen Sitch2, Corinne Le Quéré3, Josep G. Canadell8, Philippe Ciais9, Robert B. Jackson10, Simone R. Alin11, Luiz E. O. C. Aragão2, Luiz E. O. C. Aragão12, Almut Arneth, Vivek K. Arora, Nicholas R. Bates13, Nicholas R. Bates14, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp15, Selma Bultan7, Naveen Chandra16, Naveen Chandra17, Frédéric Chevallier9, Louise Chini18, Wiley Evans, Liesbeth Florentie4, Piers M. Forster19, Thomas Gasser20, Marion Gehlen9, Dennis Gilfillan, Thanos Gkritzalis21, Luke Gregor22, Nicolas Gruber22, Ian Harris23, Kerstin Hartung7, Kerstin Hartung24, Vanessa Haverd8, Richard A. Houghton25, Tatiana Ilyina6, Atul K. Jain26, Emilie Joetzjer27, Koji Kadono28, Etsushi Kato, Vassilis Kitidis29, Jan Ivar Korsbakken, Peter Landschützer6, Nathalie Lefèvre30, Andrew Lenton31, Sebastian Lienert32, Zhu Liu33, Danica Lombardozzi34, Gregg Marland35, Nicolas Metzl30, David R. Munro36, David R. Munro11, Julia E. M. S. Nabel6, S. Nakaoka16, Yosuke Niwa16, Kevin D. O'Brien11, Kevin D. O'Brien37, Tsuneo Ono, Paul I. Palmer, Denis Pierrot38, Benjamin Poulter, Laure Resplandy39, Eddy Robertson40, Christian Rödenbeck6, Jörg Schwinger, Roland Séférian27, Ingunn Skjelvan, Adam J. P. Smith3, Adrienne J. Sutton11, Toste Tanhua41, Pieter P. Tans11, Hanqin Tian42, Bronte Tilbrook31, Bronte Tilbrook43, Guido R. van der Werf44, N. Vuichard9, Anthony P. Walker45, Rik Wanninkhof38, Andrew J. Watson2, David R. Willis23, Andy Wiltshire40, Wenping Yuan46, Xu Yue47, Sönke Zaehle6 
École Normale Supérieure1, University of Exeter2, Norwich Research Park3, Wageningen University and Research Centre4, University of Groningen5, Max Planck Society6, Ludwig Maximilian University of Munich7, Commonwealth Scientific and Industrial Research Organisation8, Université Paris-Saclay9, Stanford University10, National Oceanic and Atmospheric Administration11, National Institute for Space Research12, Bermuda Institute of Ocean Sciences13, University of Southampton14, PSL Research University15, National Institute for Environmental Studies16, Japan Agency for Marine-Earth Science and Technology17, University of Maryland, College Park18, University of Leeds19, International Institute of Minnesota20, Flanders Marine Institute21, ETH Zurich22, University of East Anglia23, German Aerospace Center24, Woods Hole Research Center25, University of Illinois at Urbana–Champaign26, University of Toulouse27, Japan Meteorological Agency28, Plymouth Marine Laboratory29, University of Paris30, Hobart Corporation31, Oeschger Centre for Climate Change Research32, Tsinghua University33, National Center for Atmospheric Research34, Appalachian State University35, University of Colorado Boulder36, University of Washington37, Atlantic Oceanographic and Meteorological Laboratory38, Princeton University39, Met Office40, Leibniz Institute of Marine Sciences41, Auburn University42, University of Tasmania43, VU University Amsterdam44, Oak Ridge National Laboratory45, Sun Yat-sen University46, Nanjing University47
TL;DR: In this paper, the authors describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important 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 (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), 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 (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), 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 understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ± 0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quere et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).

1,764 citations

Journal ArticleDOI
Corinne Le Quéré1, Robbie M. Andrew, Pierre Friedlingstein2, Stephen Sitch2, Judith Hauck3, Julia Pongratz4, Julia Pongratz5, Penelope A. Pickers1, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell6, Almut Arneth7, Vivek K. Arora, Leticia Barbero8, Leticia Barbero9, Ana Bastos4, Laurent Bopp10, Frédéric Chevallier11, Louise Chini12, Philippe Ciais11, Scott C. Doney13, Thanos Gkritzalis14, Daniel S. Goll11, Ian Harris1, Vanessa Haverd6, Forrest M. Hoffman15, Mario Hoppema3, Richard A. Houghton16, George C. Hurtt12, Tatiana Ilyina5, Atul K. Jain17, Truls Johannessen18, Chris D. Jones19, Etsushi Kato, Ralph F. Keeling20, Kees Klein Goldewijk21, Kees Klein Goldewijk22, Peter Landschützer5, Nathalie Lefèvre23, Sebastian Lienert24, Zhu Liu25, Zhu Liu1, Danica Lombardozzi26, Nicolas Metzl23, David R. Munro27, Julia E. M. S. Nabel5, Shin-Ichiro Nakaoka28, Craig Neill29, Craig Neill30, Are Olsen18, T. Ono, Prabir K. Patra31, Anna Peregon11, Wouter Peters32, Wouter Peters33, Philippe Peylin11, Benjamin Pfeil18, Benjamin Pfeil34, Denis Pierrot9, Denis Pierrot8, Benjamin Poulter35, Gregor Rehder36, Laure Resplandy37, Eddy Robertson19, Matthias Rocher11, Christian Rödenbeck5, Ute Schuster2, Jörg Schwinger34, Roland Séférian11, Ingunn Skjelvan34, Tobias Steinhoff38, Adrienne J. Sutton39, Pieter P. Tans39, Hanqin Tian40, Bronte Tilbrook30, Bronte Tilbrook29, Francesco N. Tubiello41, Ingrid T. van der Laan-Luijkx33, Guido R. van der Werf42, Nicolas Viovy11, Anthony P. Walker15, Andy Wiltshire19, Rebecca Wright1, Sönke Zaehle5, Bo Zheng11 
University of East Anglia1, University of Exeter2, Alfred Wegener Institute for Polar and Marine Research3, Ludwig Maximilian University of Munich4, Max Planck Society5, Commonwealth Scientific and Industrial Research Organisation6, Karlsruhe Institute of Technology7, Atlantic Oceanographic and Meteorological Laboratory8, Cooperative Institute for Marine and Atmospheric Studies9, École Normale Supérieure10, Centre national de la recherche scientifique11, University of Maryland, College Park12, University of Virginia13, Flanders Marine Institute14, Oak Ridge National Laboratory15, Woods Hole Research Center16, University of Illinois at Urbana–Champaign17, Geophysical Institute, University of Bergen18, Met Office19, University of California, San Diego20, Netherlands Environmental Assessment Agency21, Utrecht University22, University of Paris23, Oeschger Centre for Climate Change Research24, Tsinghua University25, National Center for Atmospheric Research26, Institute of Arctic and Alpine Research27, National Institute for Environmental Studies28, Cooperative Research Centre29, Hobart Corporation30, Japan Agency for Marine-Earth Science and Technology31, University of Groningen32, Wageningen University and Research Centre33, Bjerknes Centre for Climate Research34, Goddard Space Flight Center35, Leibniz Institute for Baltic Sea Research36, Princeton University37, Leibniz Institute of Marine Sciences38, National Oceanic and Atmospheric Administration39, Auburn University40, Food and Agriculture Organization41, VU University Amsterdam42
TL;DR: In this article, the authors describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
Abstract: . Accurate assessment of anthropogenic carbon dioxide ( CO2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions ( EFF ) are based on energy statistics and cement production data, while emissions from land use and land-use change ( ELUC ), 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 ( GATM ) is computed from the annual changes in concentration. The ocean CO2 sink ( SOCEAN ) and terrestrial CO2 sink ( SLAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( BIM ), 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 understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ . For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr −1 , ELUC 1.5±0.7 GtC yr −1 , GATM 4.7±0.02 GtC yr −1 , SOCEAN 2.4±0.5 GtC yr −1 , and SLAND 3.2±0.8 GtC yr −1 , with a budget imbalance BIM of 0.5 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr −1 . Also for 2017, ELUC was 1.4±0.7 GtC yr −1 , GATM was 4.6±0.2 GtC yr −1 , SOCEAN was 2.5±0.5 GtC yr −1 , and SLAND was 3.8±0.8 GtC yr −1 , with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of + 2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018 .

1,458 citations

Journal ArticleDOI
Pierre Friedlingstein1, Pierre Friedlingstein2, Matthew W. Jones3, Michael O'Sullivan1, Robbie M. Andrew, Judith Hauck4, Glen P. Peters, Wouter Peters5, Wouter Peters6, Julia Pongratz7, Julia Pongratz8, Stephen Sitch1, Corinne Le Quéré3, Dorothee C. E. Bakker3, Josep G. Canadell9, Philippe Ciais10, Robert B. Jackson11, Peter Anthoni12, Leticia Barbero13, Leticia Barbero14, Ana Bastos8, Vladislav Bastrikov10, Meike Becker15, Meike Becker16, Laurent Bopp2, Erik T. Buitenhuis3, Naveen Chandra17, Frédéric Chevallier10, Louise Chini18, Kim I. Currie19, Richard A. Feely20, Marion Gehlen10, Dennis Gilfillan21, Thanos Gkritzalis22, Daniel S. Goll23, Nicolas Gruber24, Sören B. Gutekunst25, Ian Harris26, Vanessa Haverd9, Richard A. Houghton27, George C. Hurtt18, Tatiana Ilyina7, Atul K. Jain28, Emilie Joetzjer10, Jed O. Kaplan29, Etsushi Kato, Kees Klein Goldewijk30, Kees Klein Goldewijk31, Jan Ivar Korsbakken, Peter Landschützer7, Siv K. Lauvset15, Nathalie Lefèvre32, Andrew Lenton33, Andrew Lenton34, Sebastian Lienert35, Danica Lombardozzi36, Gregg Marland21, Patrick C. McGuire37, Joe R. Melton, Nicolas Metzl32, David R. Munro38, Julia E. M. S. Nabel7, Shin-Ichiro Nakaoka39, Craig Neill34, Abdirahman M Omar15, Abdirahman M Omar34, Tsuneo Ono, Anna Peregon10, Anna Peregon40, Denis Pierrot14, Denis Pierrot13, Benjamin Poulter41, Gregor Rehder42, Laure Resplandy43, Eddy Robertson44, Christian Rödenbeck7, Roland Séférian10, Jörg Schwinger31, Jörg Schwinger15, Naomi E. Smith5, Naomi E. Smith45, Pieter P. Tans20, Hanqin Tian46, Bronte Tilbrook33, Bronte Tilbrook34, Francesco N. Tubiello47, Guido R. van der Werf48, Andy Wiltshire44, Sönke Zaehle7 
University of Exeter1, École Normale Supérieure2, Norwich Research Park3, Alfred Wegener Institute for Polar and Marine Research4, Wageningen University and Research Centre5, University of Groningen6, Max Planck Society7, Ludwig Maximilian University of Munich8, Commonwealth Scientific and Industrial Research Organisation9, Centre national de la recherche scientifique10, Stanford University11, Karlsruhe Institute of Technology12, Atlantic Oceanographic and Meteorological Laboratory13, Cooperative Institute for Marine and Atmospheric Studies14, Bjerknes Centre for Climate Research15, Geophysical Institute, University of Bergen16, Japan Agency for Marine-Earth Science and Technology17, University of Maryland, College Park18, National Institute of Water and Atmospheric Research19, National Oceanic and Atmospheric Administration20, Appalachian State University21, Flanders Marine Institute22, Augsburg College23, ETH Zurich24, Leibniz Institute of Marine Sciences25, University of East Anglia26, Woods Hole Research Center27, University of Illinois at Urbana–Champaign28, University of Hong Kong29, Utrecht University30, Netherlands Environmental Assessment Agency31, University of Paris32, University of Tasmania33, Hobart Corporation34, University of Bern35, National Center for Atmospheric Research36, University of Reading37, Cooperative Institute for Research in Environmental Sciences38, National Institute for Environmental Studies39, Russian Academy of Sciences40, Goddard Space Flight Center41, Leibniz Institute for Baltic Sea Research42, Princeton University43, Met Office44, Lund University45, Auburn University46, Food and Agriculture Organization47, VU University Amsterdam48
TL;DR: In this article, the authors describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land use change, and show that 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 understanding of the contemporary carbon cycle.
Abstract: . Accurate assessment of anthropogenic carbon dioxide ( CO2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions ( EFF ) are based on energy statistics and cement production data, while emissions from land use change ( ELUC ), 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 ( GATM ) is computed from the annual changes in concentration. The ocean CO2 sink ( SOCEAN ) and terrestrial CO2 sink ( SLAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( BIM ), 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 understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ . For the last decade available (2009–2018), EFF was 9.5±0.5 GtC yr −1 , ELUC 1.5±0.7 GtC yr −1 , GATM 4.9±0.02 GtC yr −1 ( 2.3±0.01 ppm yr −1 ), SOCEAN 2.5±0.6 GtC yr −1 , and SLAND 3.2±0.6 GtC yr −1 , with a budget imbalance BIM of 0.4 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr −1 , reaching 10 GtC yr −1 for the first time in history, ELUC was 1.5±0.7 GtC yr −1 , for total anthropogenic CO2 emissions of 11.5±0.9 GtC yr −1 ( 42.5±3.3 GtCO2 ). Also for 2018, GATM was 5.1±0.2 GtC yr −1 ( 2.4±0.1 ppm yr −1 ), SOCEAN was 2.6±0.6 GtC yr −1 , and SLAND was 3.5±0.7 GtC yr −1 , with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).

981 citations

Journal ArticleDOI
15 Aug 2018-Nature
TL;DR: Satellite observations and Earth system model simulations reveal that marine heatwaves have increased in recent decades and will increase further in terms of frequency, intensity, duration and spatial extent, suggesting that MHWs will become very frequent and extreme under global warming.
Abstract: Marine heatwaves (MHWs) are periods of extreme warm sea surface temperature that persist for days to months1 and can extend up to thousands of kilometres2. Some of the recently observed marine heatwaves revealed the high vulnerability of marine ecosystems3–11 and fisheries12–14 to such extreme climate events. Yet our knowledge about past occurrences15 and the future progression of MHWs is very limited. Here we use satellite observations and a suite of Earth system model simulations to show that MHWs have already become longer-lasting and more frequent, extensive and intense in the past few decades, and that this trend will accelerate under further global warming. Between 1982 and 2016, we detect a doubling in the number of MHW days, and this number is projected to further increase on average by a factor of 16 for global warming of 1.5 degrees Celsius relative to preindustrial levels and by a factor of 23 for global warming of 2.0 degrees Celsius. However, current national policies for the reduction of global carbon emissions are predicted to result in global warming of about 3.5 degrees Celsius by the end of the twenty-first century16, for which models project an average increase in the probability of MHWs by a factor of 41. At this level of warming, MHWs have an average spatial extent that is 21 times bigger than in preindustrial times, last on average 112 days and reach maximum sea surface temperature anomaly intensities of 2.5 degrees Celsius. The largest changes are projected to occur in the western tropical Pacific and Arctic oceans. Today, 87 per cent of MHWs are attributable to human-induced warming, with this ratio increasing to nearly 100 per cent under any global warming scenario exceeding 2 degrees Celsius. Our results suggest that MHWs will become very frequent and extreme under global warming, probably pushing marine organisms and ecosystems to the limits of their resilience and even beyond, which could cause irreversible changes. Satellite observations and Earth system model simulations reveal that marine heatwaves have increased in recent decades and will increase further in terms of frequency, intensity, duration and spatial extent.

673 citations