Global Carbon Budget 2016

Quéré, Corinne Le; Andrew, Robbie M.; Canadell, Josep G.; Sitch, Stephen; Korsbakken, Jan Ivar; Peters, Glen P.; Manning, Andrew C.; Boden, Thomas A.; Tans, Pieter P.; Houghton, Richard A.; Alin, Simone R.; Andrews, Oliver; Anthoni, Peter; Barbero, Leticia; Bopp, Laurent; Chevallier, F.; Chini, L. P.; Ciais, Philippe; Currie, Kim; Delire, Christine; Doney, Scott C.; Friedlingstein, Pierre; Gkritzalis, Thanos; Harris, Ian; Hauck, Judith; Haverd, Vanessa; Hoppema, Mario; Goldewijk, Kees Klein; Kato, Etsushi; Körtzinger, Arne; Landschützer, Peter; Lefèvre, Nathalie; Lenton, Andrew; Lienert, Sebastian; Lombardozzi, Danica; Melton, Joe R.; Metzl, Nicolas; Millero, Frank J.; Monteiro, Pedro M. S.; Munro, David R.; Nabel, Julia E. M. S.; Nakaoka, Shin‐Ichiro; O’Brien, Kevin D.; Olsen, Are; Omar, Abdirahman M; Ono, Tsuneo; Pierrot, Denis; Poulter, Benjamin; Rödenbeck, Christian; Salisbury, Joe; Schuster, Ute; Schwinger, Jörg; Séférian, Roland; Skjelvan, Ingunn; Stocker, Benjamin D.; Sutton, Adrienne J.; Takahashi, Toshiyuki; Tian, Hanqin; Tilbrook, Bronte; Laan-Luijkx, Ingrid T. van der; Werf, Guido R. van der; Viovy, Nicolas; Walker, Anthony P.; Wiltshire, Andrew J.; Zaehle, Sönke

doi:10.5194/essd-2016-51

Cited by 169 publications

(261 citation statements)

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“…As an additional check of the model, we also calculated the summer MLD trend from a hindcast simulation with the same model setup using the same methodology as for the observational data. We analyzed output from a century‐scale simulation where the model is forced by historic atmospheric CO 2 concentrations (Le Quéré et al, ) and interannual‐varying atmospheric forcing fields from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR‐R1; Kalnay et al, ). The model is spun‐up from 1900 to 1947, and we ran the model for 69 years, from 1948 to 2016.…”

Section: Resultsmentioning

confidence: 99%

“…The model is spun‐up from 1900 to 1947, and we ran the model for 69 years, from 1948 to 2016. This model simulation was submitted to the Global Carbon Budget 2017 and is the same physical set‐up as in the Global Carbon Budget 2016 (Le Quéré et al, ). The comparison of the modeled MLD trend (Figure f) to the observed one (Figure e) in the period 2002–2011 shows that the model is able to reproduce the pattern and amplitude of the observed trend in MLD.…”

Section: Resultsmentioning

confidence: 99%

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Drivers of Interannual Variability of Summer Mixed Layer Depth in the Southern Ocean Between 2002 and 2011

et al. 2018

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Climate change projections indicate that there will be warming and an intensification of westerly winds in the Southern Ocean (SO) in the future. These two forcings potentially have opposing effects on the depth of the surface mixed layer. Here we investigate how interannual to decadal variability of atmospheric surface air temperature (SAT) and zonal wind speed (uwind) impact mixed layer depth (MLD) in the SO (south of 30°S) during summer, the season of main biological activity. We use gridded MLD data from observations and atmospheric reanalysis data of uwind and SAT in the SO to assess summer MLD variability and its potential drivers. With a model‐based sensitivity experiment, we quantify the relative contributions of uwind versus SAT forcing on the summer MLD in the decade 2002–2011. Wind‐induced changes dominate over temperature‐induced changes of the MLD between 2002 and 2011. We find a positive trend of summer MLD in the Antarctic Zone of the Atlantic and Indian Ocean sectors. Our model‐based sensitivity study suggests that the summer MLD shows a zonally asymmetric response to recent atmospheric forcing. In the Pacific and Australian sectors, cooling and intensification of uwind jointly result in a deepening of the mixed layer. In the Atlantic and Indian sectors, the MLD responds differently north and south of the Antarctic Polar Front (APF). A deepening south of the APF is caused by the increase in uwind, whereas the decrease in uwind and warming act in concert to result in a shoaling of the MLD north of the APF.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Drivers of Interannual Variability of Summer Mixed Layer Depth in the Southern Ocean Between 2002 and 2011

et al. 2018

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“…The oceans take up more than 25% of anthropogenic carbon dioxide (CO 2 ) emissions (Le Quéré et al, ), thereby mitigating climate change. The Southern Ocean is responsible for 40% of this anthropogenic CO 2 uptake by the oceans (Khatiwala et al, ; Sabine et al, ), a trend which has reinvigorated lately after receding between 2002 and 2012 (Landschützer et al, ).…”

Section: Introductionmentioning

confidence: 99%

Sea Ice Meltwater and Circumpolar Deep Water Drive Contrasting Productivity in Three Antarctic Polynyas

et al. 2019

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In the Southern Ocean, polynyas exhibit enhanced rates of primary productivity and represent large seasonal sinks for atmospheric CO2. Three contrasting east Antarctic polynyas were visited in late December to early January 2017: the Dalton, Mertz, and Ninnis polynyas. In the Mertz and Ninnis polynyas, phytoplankton biomass (average of 322 and 354 mg chlorophyll a (Chl a)/m2, respectively) and net community production (5.3 and 4.6 mol C/m2, respectively) were approximately 3 times those measured in the Dalton polynya (average of 122 mg Chl a/m2 and 1.8 mol C/m2). Phytoplankton communities also differed between the polynyas. Diatoms were thriving in the Mertz and Ninnis polynyas but not in the Dalton polynya, where Phaeocystis antarctica dominated. These strong regional differences were explored using physiological, biological, and physical parameters. The most likely drivers of the observed higher productivity in the Mertz and Ninnis were the relatively shallow inflow of iron‐rich modified Circumpolar Deep Water onto the shelf as well as a very large sea ice meltwater contribution. The productivity contrast between the three polynyas could not be explained by (1) the input of glacial meltwater, (2) the presence of Ice Shelf Water, or (3) stratification of the mixed layer. Our results show that physical drivers regulate the productivity of polynyas, suggesting that the response of biological productivity and carbon export to future change will vary among polynyas.

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“…This estimation includes the 2016 global carbon budget [37]. As a result of this estimation, a set of 107 values of the remaining global quota after 2016 were obtained, all of them equally probable.…”

Section: Methodsmentioning

confidence: 99%

A human-scale perspective on global warming: Zero emission year and personal quotas

2017

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This article builds on the premise that human consumption of goods, food and transport are the ultimate drivers of climate change. However, the nature of the climate change problem (well described as a tragedy of the commons) makes it difficult for individuals to recognise their personal duty to implement behavioural changes to reduce greenhouse gas emissions. Consequently, this article aims to analyse the climate change issue from a human-scale perspective, in which each of us has a clearly defined personal quota of CO2 emissions that limits our activity and there is a finite time during which CO2 emissions must be eliminated to achieve the “well below 2°C” warming limit set by the Paris Agreement of 2015 (COP21). Thus, this work’s primary contribution is to connect an equal per capita fairness approach to a global carbon budget, linking personal levels with planetary levels. Here, we show that a personal quota of 5.0 tons of CO2 yr-1 p-1 is a representative value for both past and future emissions; for this level of a constant per-capita emissions and without considering any mitigation, the global accumulated emissions compatible with the “well below 2°C” and 2°C targets will be exhausted by 2030 and 2050, respectively. These are references years that provide an order of magnitude of the time that is left to reverse the global warming trend. More realistic scenarios that consider a smooth transition toward a zero-emission world show that the global accumulated emissions compatible with the “well below 2°C” and 2°C targets will be exhausted by 2040 and 2080, respectively. Implications of this paper include a return to personal responsibility following equity principles among individuals, and a definition of boundaries to the personal emissions of CO2.

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Global Carbon Budget 2016

Cited by 169 publications

References 0 publications

Drivers of Interannual Variability of Summer Mixed Layer Depth in the Southern Ocean Between 2002 and 2011

Drivers of Interannual Variability of Summer Mixed Layer Depth in the Southern Ocean Between 2002 and 2011

Sea Ice Meltwater and Circumpolar Deep Water Drive Contrasting Productivity in Three Antarctic Polynyas

A human-scale perspective on global warming: Zero emission year and personal quotas

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