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ChuanLi Jiang, Sarah T. Gille, Janet Sprintall, and Colm Sweeney

south. The observed DIC effect on p CO 2 peaks during austral winter from July to August, about 6 months after the observed austral summer peak, due to changes in the SST effect on p CO 2 . This out-of-phase relation between the SST- and DIC-forced effects explains the small amplitudes of the seasonal cycle of p CO 2 variations (2.5 μ atm to the south and 7.5 μ atm to the north; Fig. 12a ), since the effects compensate for each other. The amplitudes of the eight ESMs show meridional

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Charles D. Koven, William J. Riley, and Alex Stern

is dominated by soil hydrology, latent heat, and thermal properties. An exception to this is for some models that place snow insulation effects within the soil column. Similarly, while the mean temperature and the amplitude of the seasonal cycle will be linked at a given position along these vertical gradients, varying process representation in different models may lead to different levels of thermal rectification associated with the multiple processes operating across each gradient. The soil

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V. Brovkin, L. Boysen, V. K. Arora, J. P. Boisier, P. Cadule, L. Chini, M. Claussen, P. Friedlingstein, V. Gayler, B. J. J. M. van den Hurk, G. C. Hurtt, C. D. Jones, E. Kato, N. de Noblet-Ducoudré, F. Pacifico, J. Pongratz, and M. Weiss

signal coincides spatially with regions of strongest forcing and because the signal is in line with our knowledge of LULCC effects on local energy and water balance. For tropical and subtropical regions, the seasonality of the response of near surface air temperature for regions where LULCC exceeds 10% is small ( Fig. B1 ). Fig . 5. Maps of difference in mean annual near-surface air temperature (K) between ensemble averages of the (top)–(bottom) RCP and LUCID simulations for (left) RCP2.6 and (right

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A. Anav, P. Friedlingstein, M. Kidston, L. Bopp, P. Ciais, P. Cox, C. Jones, M. Jung, R. Myneni, and Z. Zhu

, 316 , 1732 – 1735 . Takahashi , T. , and Coauthors , 2002 : Global sea–air CO 2 flux based on climatological surface ocean p CO 2 , and seasonal biological and temperature effects . Deep-Sea Res. , 49B , 1601 – 1622 . Takahashi , T. , and Coauthors , 2009 : Climatological mean and decadal change in surface ocean p CO 2 , and net sea–air CO 2 flux over the global oceans . Deep-Sea Res. , 56B , 554 – 577 . Taylor , K. E. , R. J. Stouffer , and G. Meehl , 2012 : An

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Alan J. Hewitt, Ben B. B. Booth, Chris D. Jones, Eddy S. Robertson, Andy J. Wiltshire, Philip G. Sansom, David B. Stephenson, and Stan Yip

concentration pathway ( Jones et al. 2006 ; Plattner et al. 2008 ). This method has become widespread and was recommended by Hibbard et al. (2007) as the experimental design for CMIP5 and has subsequently been used to present compatible emissions from the CMIP5 multimodel ensemble ( Jones et al. 2013 ). The natural uptake of carbon by land and ocean biospheres is sensitive to both changes in climate and the concentration of atmospheric CO 2 and the balance between these large but offsetting effects on

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Pierre Friedlingstein, Malte Meinshausen, Vivek K. Arora, Chris D. Jones, Alessandro Anav, Spencer K. Liddicoat, and Reto Knutti

( Dunne et al. 2013 ; Anav et al. 2013 ). As noted in Dunne et al. (2013) , the GFDL ESM tends to underestimate the atmospheric CO 2 seasonal cycle, potentially also leading to a relatively weak land uptake. We also note that GFDL-ESM2G has a more comprehensive treatment of land cover change than other ESMs ( Shevliakova et al. 2009 ), accounting for transitions between primary forests, crops, pastures, and secondary forests as well as wood harvesting, which increases the simulated LUC emissions

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Eleanor J. Burke, Chris D. Jones, and Charles D. Koven

permafrost) to climate change (γ L ; PgC K −1 ) was found using esmFdbck1 where the atmospheric CO 2 increases by 1% yr −1 in the following manner: where (PgC) is the change in the mean total land carbon and is the change in the mean global mean temperature (K). The change is defined for the mean of the first and last 5 years of the 140-yr simulation, which starts at preindustrial CO 2 and ends at 4 times preindustrial CO 2 . These simulations do not include the confounding effects of changes in

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Lifen Jiang, Yaner Yan, Oleksandra Hararuk, Nathaniel Mikle, Jianyang Xia, Zheng Shi, Jerry Tjiputra, Tongwen Wu, and Yiqi Luo

across ESMs. This means that the vegetation carbon storage depends mostly on how long the carbon will remain in the vegetation. These findings indicate that parameterization of residence time and its spatial distributions in ESMs may be a key factor in controlling the vegetation carbon simulations. Improvement of other drivers and processes that have effects on the residence times, including harvesting and natural disturbances, are also important for ESMs to get more accurate predictions of biomass

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Vivek K. Arora, George J. Boer, Pierre Friedlingstein, Michael Eby, Chris D. Jones, James R. Christian, Gordon Bonan, Laurent Bopp, Victor Brovkin, Patricia Cadule, Tomohiro Hajima, Tatiana Ilyina, Keith Lindsay, Jerry F. Tjiputra, and Tongwen Wu

the biogeochemically coupled simulation the biogeochemistry responds to the increasing atmospheric CO 2 while the radiative forcing remains at preindustrial values. The simulations do not include the confounding effects of changes in land use, non-CO 2 greenhouse gases, aerosols, etc., and so provide a controlled experiment with which to compare carbon–climate interactions across models. Results from eight of the comprehensive Earth system models participating in the CMIP5 intercomparison

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