Publications

Export 5 results:
Sort by: Author Title Type [ Year  (Desc)]
2018
Le Quere, C, Andrew RM, Friedlingstein P, Sitch S, Hauck J, Pongratz J, Pickers PA, Korsbakken JI, Peters GP, Canadell JG, Arneth A, Arora VK, Barbero L, Bastos A, Bopp L, Chevallier F, Chini LP, Ciais P, Doney SC, Gkritzalis T, Goll DS, Harris I, Haverd V, Hoffman FM, Hoppema M, Houghton RA, Hurtt G, Ilyina T, Jain AK, Johannessen T, Jones CD, Kato E, Keeling RF, Goldewijk KK, Landschutzer P, Lefevre N, Lienert S, Liu Z, Lombardozzi D, Metzl N, Munro DR, Nabel J, Nakaoka S, Neill C, Olsen A, Ono T, Patra P, Peregon A, Peters W, Peylin P, Pfeil B, Pierrot D, Poulter B, Rehder G, Resplandy L, Robertson E, Rocher M, Rodenbeck C, Schuster U, Schwinger J, Seferian R, Skjelvan I, Steinhoff T, Sutton A, Tans PP, Tian HQ, Tilbrook B, Tubiello FN, van der Laan-Luijkx IT, van der Werf GR, Viovy N, Walker AP, Wiltshire AJ, Wright R, Zaehle S, Zheng B.  2018.  Global Carbon Budget 2018. Earth System Science Data. 10:2141-2194.   10.5194/essd-10-2141-2018   AbstractWebsite

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 (E-FF) are based on energy statistics and cement production data, while emissions from land use and 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) and terrestrial CO2 sink (S-LAND) are estimated with global process models constrained by observations. 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 understanding of the contemporary carbon cycle. All uncertainties are reported as +/- 1 sigma. For the last decade available (2008-2017), E-FF was 9.4 +/- 0.5 GtC yr(-1), E-LUC 1.5 +/- 0.7 GtC yr(-1), G(ATM) 4.7 +/- 0.02 GtC yr(-1), S-OCEAN 2.4 +/- 0.5 GtC yr(-1), and S-LAND 3.2 +/- 0.8 GtC yr(-1), with a budget imbalance B-IM of 0.5 GtC yr(-1) indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in E-FF was about 1.6 % and emissions increased to 9.9 +/- 0.5 GtC yr(-1). Also for 2017, E-LUC was 1.4 +/- 0.7 GtC yr(-1), G(ATM) was 4.6 +/- 0.2 GtC yr(-1), S-OCEAN was 2.5 +/- 0.5 GtC yr(-1), and S-LAND was 3.8 +/- 0.8 GtC yr(-1), with a B-IM 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 E-FF 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.

Nevison, C, Munro D, Lovenduski N, Cassar N, Keeling R, Krummel P, Tjiputra J.  2018.  Net community production in the Southern Ocean: Insights from comparing atmospheric potential oxygen to satellite ocean color algorithms and ocean models. Geophysical Research Letters. 45:10549-10559.   10.1029/2018gl079575   AbstractWebsite

The contribution of oceanic net community production (NCP) to the observed seasonal cycle in atmospheric potential oxygen (APO) is estimated at Cape Grim, Tasmania. The resulting APO(NCP) signal is compared to satellite and ocean model-based estimates of POC export and NCP across the Southern Ocean. The satellite products underestimate the amplitude of the observed APONCP seasonal cycle by more than a factor of 2. Ocean models suggest two reasons for this underestimate: (1) Current satellite products substantially underestimate the magnitude of NCP in early spring. (2) Seasonal O-2 outgassing is supported in large part by storage of carbon in DOC and living biomass. More DOC observations are needed to help evaluate this latter model prediction. Satellite products could be improved by developing seasonally dependent relationships between remote sensing chlorophyll data and in situ NCP, recognizing that the former is a measure of mass, the latter of flux. Plain Language Summary Phytoplankton in the surface ocean transform carbon dioxide into organic carbon while also producing oxygen. A fraction of the carbon is exported into the deep ocean, while the oxygen is emitted to the atmosphere. The carbon export rate influences how much carbon dioxide the ocean can absorb. The rate is commonly estimated using satellite-based phytoplankton color measured in the surface ocean, but such estimates involve many uncertain steps and assumptions. Small but detectible seasonal cycles in atmospheric oxygen have been used as an independent method for evaluating satellite-based estimates of organic carbon export. In this study, we evaluate eight satellite-derived carbon export estimates based on their ability to reproduce the observed seasonal cycle of atmospheric oxygen measured at a southeastern Australia site. All underpredict the seasonal oxygen cycle by at least a factor of 2, in part because they fail to capture the carbon and oxygen produced in early springtime and also because they focus on large particles of carbon that are heavy enough to sink while neglecting the dissolved fraction of organic carbon. Our study suggests that satellite estimates could be improved by a better understanding of seasonal variations in the relationship between phytoplankton productivity and carbon export.

Resplandy, L, Keeling RF, Rodenbeck C, Stephens BB, Khatiwala S, Rodgers KB, Long MC, Bopp L, Tans PP.  2018.  Revision of global carbon fluxes based on a reassessment of oceanic and riverine carbon transport. Nature Geoscience. 11:504-+.   10.1038/s41561-018-0151-3   AbstractWebsite

Measurements of atmospheric CO2 concentration provide a tight constraint on the sum of the land and ocean sinks. This constraint has been combined with estimates of ocean carbon flux and riverine transport of carbon from land to oceans to isolate the land sink. Uncertainties in the ocean and river fluxes therefore translate into uncertainties in the land sink. Here, we introduce a heat-based constraint on the latitudinal distribution of ocean and river carbon fluxes, and reassess the partition between ocean, river and land in the tropics, and in the southern and northern extra-tropics. We show that the ocean overturning circulation and biological pump tightly link the ocean transports of heat and carbon between hemispheres. Using this coupling between heat and carbon, we derive ocean and river carbon fluxes compatible with observational constraints on heat transport. This heat-based constraint requires a 20-100% stronger ocean and river carbon transport from the Northern Hemisphere to the Southern Hemisphere than existing estimates, and supports an upward revision of the global riverine carbon flux from 0.45 to 0.78 PgC yr(-1). These systematic biases in existing ocean/river carbon fluxes redistribute up to 40% of the carbon sink between northern, tropical and southern land ecosystems. As a consequence, the magnitude of both the southern land source and the northern land sink may have to be substantially reduced.

Rodenbeck, C, Zaehle S, Keeling R, Heimann M.  2018.  How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data Biogeosciences. 15:2481-2498.   10.5194/bg-15-2481-2018   AbstractWebsite

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as "inter-annual climate sensitivity". We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical interannual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.

Le Quere, C, Andrew RM, Friedlingstein P, Sitch S, Pongratz J, Manning AC, Korsbakken JI, Peters GP, Canadell JG, Jackson RB, Boden TA, Tans PP, Andrews OD, Arora VK, Bakker DCE, Barbero L, Becker M, Betts RA, Bopp L, Chevallier F, Chini LP, Ciais P, Cosca CE, Cross J, Currie K, Gasser T, Harris I, Hauck J, Haverd V, Houghton RA, Hunt CW, Hurtt G, Ilyina T, Jain AK, Kato E, Kautz M, Keeling RF, Goldewijk KK, Kortzinger A, Landschutzer P, Lefevre N, Lenton A, Lienert S, Lima I, Lombardozzi D, Metzl N, Millero F, Monteiro PMS, Munro DR, Nabel J, Nakaoka S, Nojiri Y, Padin XA, Peregon A, Pfeil B, Pierrot D, Poulter B, Rehder G, Reimer J, Rodenbeck C, Schwinger J, Seferian R, Skjelvan I, Stocker BD, Tian HQ, Tilbrook B, Tubiello FN, van der Laan-Luijkx IT, van der Werf GR, van Heuven S, Viovy N, Vuichard N, Walker AP, Watson AJ, Wiltshire AJ, Zaehle S, Zhu D.  2018.  Global Carbon Budget 2017. Earth System Science Data. 10:405-448.   10.5194/essd-10-405-2018   AbstractWebsite

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. CO2 emissions from fossil fuels and industry (E-FF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E-LUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G(ATM)) is computed from the annual changes in concentration. The ocean CO2 sink (S-OCEAN) and terrestrial CO2 sink (S-LAND) are estimated with global process models constrained by observations. 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 understanding of the contemporary carbon cycle. All uncertainties are reported as +/- 1 sigma. For the last decade available (2007-2016), E-FF was 9.4 +/- 0.5 GtC yr(-1), E-LUC 1.3 +/- 0.7 GtC yr(-1), G(ATM) 4.7 +/- 0.1 GtC yr(-1), S-OCEAN 2.4 +/- 0.5 GtC yr(-1), and S-LAND 3.0 +/- 0.8 GtC yr(-1), with a budget imbalance B-IM of 0.6 GtC yr(-1) indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in E-FF was approximately zero and emissions remained at 9.9 +/- 0.5 GtC yr(-1). Also for 2016, E-LUC was 1.3 +/- 0.7 GtC yr(-1), G(ATM) was 6.1 +/- 0.2 GtC yr(-1), S-OCEAN was 2.6 +/- 0.5 GtC yr(-1), and S-LAND was 2.7 +/- 1.0 GtC yr(-1), with a small B-IM of 0.3 GtC. G(ATM) continued to be higher in 2016 compared to the past decade (2007-2016), reflecting in part the high fossil emissions and the small S-LAND consistent with El Nino conditions. The global atmospheric CO2 concentration reached 402.8 +/- 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6-9 months indicate a renewed growth in E-FF of +2.0% (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quere et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).