Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Urban, Nathan M.; Keller, Klaus (2010)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
How has the Atlantic Meridional Overturning Circulation (AMOC) varied over the past centuries and what is the risk of an anthropogenic AMOC collapse? We report probabilistic projections of the future climate which improve on previous AMOC projection studies by (i) greatly expanding the considered observational constraints and (ii) carefully sampling the tail areas of the parameter probability distribution function (pdf). We use a Bayesian inversion to constrain a simple model of the coupled climate, carbon cycle and AMOC systems using observations to derive multicentury hindcasts and projections. Our hindcasts show considerable skill in representing the observational constraints. We show that robust AMOC risk estimates can require carefully sampling the parameter pdfs. We find a low probability of experiencing an AMOC collapse within the 21st century for a business-as-usual emissions scenario. The probability of experiencing an AMOC collapse within two centuries is 1/10. The probability of crossing a forcing threshold and triggering a future AMOC collapse (by 2300) is approximately 1/30 in the 21st century and over 1/3 in the 22nd. Given the simplicity of the model structure and uncertainty in the forcing assumptions, our analysis should be considered a proof of concept and the quantitative conclusions subject to severe caveats.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Adger, N., Aggarwal, P., Agrawala, S., Alcamo, J., Allali, A. and coauthors. 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability, Summary for Policymakers. IPCC Secretariat, c/o WMO, 7bis, Avenue de la Paix, C.P. N ◦ 2300, 1211 Geneva 2, Switzerland.
    • Alley, R., Berntsen, T., Bindoff, N. L., Chen, Z., Chidthaisong, A. and co-authors. 2007. Climate Change 2007: The Physical Science Basis, Summary for Policymakers. IPCC Secretariat, c/o WMO, 7bis, Avenue de la Paix, C.P. N ◦ 2300, 1211 Geneva 2, Switzerland.
    • Annan, J. D. and Hargreaves, J. C. 2009. On the generation and interpretation of probabilistic estimates of climate sensitivity. Clim. Change. doi:10.1007/s10584-009-9715-y.
    • Annan, J. D., Hargreaves, J. C., Ohgaito, R., Abe-Ouchi, A. and Emori, S. 2005. Efficiently constraining climate sensitivity with paleoclimate simulations. Scient. Online Lett. Atmos. 1, 181-184.
    • Baumgartner, A. and Reichel, E. 1975. The World Water Balance. Elsevier, Amsterdam, the Netherlands, and New York.
    • Bence, J. R. 1995. Analysis of short time series: correcting for autocorrelation. Ecology 76, 628-639.
    • Boden, T. A., Marland, G. and Andres, R. J. 2009. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, TN, U.S.A. doi:10.3334/CDIAC/00001. Available electronically from: http://cdiac.ornl.gov/trends/emis/overview_2006.html.
    • Broecker, W. S. 1991. The great ocean conveyor. Oceanography 4, 79-89.
    • Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B. and Jones, P. D. 2006. Uncertainty estimates in regional and global observed temperature changes: a new data set from 1850. J. Geophys. Res.-Atmos. 111, D12106, doi:10.1029/2005JD006548.
    • Bryden, H. L., Longworth, H. R. and Cunningham, S. A. 2005. Slowing of the Atlantic meridional overturning circulation at 25◦ N. Nature 438(7068), 655-657.
    • Cessi, P., Young, W. R. and Polton, J. A. 2006. Control of large-scale heat transport by small-scale mixing. J. Phys. Oceanogr. 36(10), 1877-1894.
    • Challenor, P. G., Hankin, R. K. S. and March, R. 2006. Towards the probability of rapid climage change. In: Avoiding Dangerous Climate Change (eds H. J. Schellnhuber, W. Cramer, N. Nakicenovic, T. Wigley and G. Yohe), Cambridge University Press, Cambridge, pp. 55-63.
    • Crowley, T. J. 2000. Causes of climate change over the past 1000 years. Science 289(5477), 270-277.
    • Cunningham, S. A., Kanzow, T., Rayner, D., Baringer, M. O., Johns, W. E. and co-authors. 2007. Temporal variability of the Atlantic meridional overturning circulation at 26.5◦N. Science 317(5840), 935- 938.
    • Curry, R. and Mauritzen, C. 2005. Dilution of the northern North Atlantic Ocean in recent decades. Science 308(5729), 1772-1774.
    • Draper, D. 1995. Assessment and propagation of model uncertainty. J. R. Statist. Soc. Ser. B-Methodol. 57(1), 45-97.
    • Ellsberg, D. 1961. Risk, ambiguity, and the Savage axioms. Quart. J. Econ. 75, 643-669.
    • Etheridge, D. M., Steele, L. P., Langenfelds, R. L., Francey, R. J., Barnola, J. M., and co-authors. 1996. Natural and anthropogenic changes in atmospheric CO2 over the last 1000 years from air in Antarctic ice and firn. J. Geophys. Res.-Atmos. 101(D2), 4115-4128.
    • Forest, C. E., Stone, P. H., Sokolov, A. P., Allen, M. R. and Webster, M. D. 2002. Quantifying uncertainties in climate system properties with the use of recent climate observations. Science 295, 113-117.
    • Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W. and coauthors. 2006. Climate-carbon cycle feedback analysis: results from the C4MIP model intercomparison. J. Climate 19, 3337-3353.
    • Fro¨lich, C. and Lean, J. 1998. The Sun's total irradiance: cycles and trends in the past two decades and associated climate change uncertainties. Geophys. Res. Lett. 25, 4377-4380. Updated data are available online: C. Fro¨lich, PMOD/WRC, http://www. pmodwrc.ch/pmod.php?topic=tsi/composite/SolarConstant.
    • Gouretski, V. and Koltermann, K. P. 2007. How much is the ocean really warming? Geophys. Res. Lett. 34, L01610.
    • Hastings, W. K. 1970. Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57(1), 97-109.
    • Hegerl, G. C., Crowley, T. J., Hyde, W. T. and Frame, D. J. 2006. Climate sensitivity constrained by temperature reconstructions over the past seven centuries. Nature 440(7087), 1029-1032.
    • Hoeting, J. A., Madigan, D., Raftery, A. E. and Volinsky, C. T. 1999. Bayesian model averaging: a tutorial. Stat. Sci. 14(4), 382-401.
    • Hofmann, M. and Rahmstorf, S. 2009. On the stability of the Atlantic meridional overturning circulation. Proc. Natl. Acad. Sci. U. S. A. 106, 20584-20589.
    • Hooss, G., Voss, R., Hasselmann, K., Maier-Reimer, E. and Joos, F. 2001. A nonlinear impulse response model of the coupled carbon cycle-climate system (NICCS). Clim. Dyn. 18(3-4), 189-202.
    • Houghton, R. A., Davidson, E. A. and Woodwell, G. M. 1998. Missing sinks, feedbacks, and understanding the role of terrestrial ecosystems in the global carbon balance. Global Biogeochem. Cycles 12(1), 25-34.
    • Jain, A. K. and Yang, X. J. 2005. Modeling the effects of two different land cover change data sets on the carbon stocks of plants and soils in concert with CO2 and climate change. Global Biogeochem. Cycles 19(2), GB2015.
    • Kanzow, T., Cunningham, S. A., Rayner, D., Hirschi, J. J. M., Johns, W. E. and co-authors. 2007. Observed flow compensation associated with the MOC at 26.5◦N in the Atlantic. Science 317(5840), 938-941.
    • Keeling, C. D. and Whorf, T. P. 2005. Atmospheric CO2 records from sites in the SIO air sampling network, Technical report, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory. Updated data available online: P. Tans, NOAA/ESRL, ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_annmean_mlo.txt.
    • Keller, K. and McInerney, D. 2008. The dynamics of learning about a climate threshold. Clim. Dyn. 30, 321-332.
    • Keller, K., Tan, K., Morel, F. M. M. and Bradford, D. F. 2000. Preserving the ocean circulation: implications for climate policy. Clim. Change 47(1-2), 17-43.
    • Keller, K., Bolker, B. M. and Bradford, D. F. 2004. Uncertain climate thresholds and optimal economic growth. J. Environ. Econ. Manage. 48, 723-741.
    • Keller, K., Miltich, L. I., Robinson, A. and Tol, R. S. J. 2007a. How overconfident are current projections of carbon dioxide emissions? Working Paper Series, Research Unit Sustainability and Global Change, Hamburg University. FNU-124, http://ideas.repec.org/ s/sgc/wpaper.html.
    • Keller, K., Schlesinger, M. and Yohe, G. 2007b. Managing the risks of climate thresholds: uncertainties and information needs. Clim. Change 91, 5-10. doi:10.1007/s10584-006-9114-6.
    • Knutti, R., Stocker, T. F., Joos, F. and Plattner, G. K. 2003. Probabilistic climate change projections using neural networks. Clim. Dyn. 21(3-4), 257-272.
    • Krebs, U. and Timmermann, A. 2007. Tropical air-sea interactions accelerate the recovery of the Atlantic meridional overturning circulation after a major shutdown. J. Clim. 20, 4940-4956.
    • Kriegler, E. 2005. Imprecise probability analysis for integrated assessment of climate change. PhD Thesis, University of Potsdam, Potsdam, Germany.
    • Kuhlbrodt, T., Rahmstorf, S., Zickfeld, K., Vikebo, F. B., Sundby, S. and co-authors. 2009. An integrated assessment of changes in the thermohaline circulation. Clim. Change 96, 489-537.
    • Latif, M., Roeckner, E., Mikolajewski, U. and Voss, R. 2000. Tropical stabilization of the thermohaline circulation in a greenhouse warming simulation. J. Clim. 13, 1809-1813.
    • Lempert, R. J. 2002. A new decision sciences for complex systems. Proc. Natl. Acad. Sci. U. S. A. 99, 7309-7313.
    • Link, P. M. and Tol, R. S. J. 2004. Possible economic impacts of a shutdown of the thermohaline circulation: an application of FUND. Portuguese Econ. J. 3, 99-114.
    • Lohmann, U. and Feichter, J. 2005. Global indirect aerosol effects: a review. Atmos. Chem. Phys. 5, 715-737.
    • Lumpkin, R. and Speer, K. 2007. Global ocean meridional overturning. J. Phys. Oceanogr. 37(10), 2550-2562.
    • McNeil, B. I., Matear, R. J., Key, R. M., Bullister, J. L. and Sarmiento, J. L. 2003. Anthropogenic CO2 uptake by the ocean based on the global chlorofluorocarbon data set. Science 299(5604), 235-239.
    • Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. and co-authors. 2007, Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
    • Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H. and Teller, E., 1953. Equation of state calculations by fast computing machines. J. Chem. Phys. 21, 1087-1092.
    • Nordhaus, W. D. 2007. The challenge of global warming: economic models and environmental policy, Technical report, http://nordhuas.econ.yale.edu/DICE2007.htm, accessed May 2, 2007, model version: DICE-2007.delta.v7.
    • Obata, A.. 2007. Climate-carbon cycle model response to freshwater discharge into the North Atlantic. J. Clim. 20, 5962-5976.
    • Rahmstorf, S. and Zickfeld, K. 2005. Thermohaline circulation changes: a question of risk assessment-an editorial review essay. Clim. Change 68(1-2), 241-247.
    • Ramankutty, N. and Foley, J. A. 1999. Estimating historical changes in global land cover: Croplands from 1700 to 1992. Global Biogeochem. Cycles 13(4), 997-1027.
    • Ricciuto, D., Davis, K. and Keller, K. 2008. A Bayesian calibration of a simple carbon cycle model: the role of observations in estimating and reducing uncertainty. Global Biogeochem. Cycles 22, GB2030.
    • Sarmiento, J. L. and Le Que´re´, C. 1996. Oceanic carbon dioxide uptake in a model of century-scale global warming. Science 274, 1346- 1350.
    • Schmittner, A., Urban, N. M., Keller, K. and Matthews, D. 2009. Using tracer observations to reduce the uncertainty of ocean diapycnal mixing and climate-carbon cycle projections. Global Biogeochem. Cycles 23, GB4009.
    • Schneider, S. H., Semenov, S., Patwardhan, A., Burton, I., Magadza, C. H. D. and co-authors. 2007a. Assessing key vulnerabilities and the risk from climate change. In: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden and C. E. Hanson), Cambridge University Press, Cambridge, UK, 779-810.
    • Schneider, B., Latif, M. and Schmittner, A. 2007b. Evaluation of different methods to assess model projections of the future evolution of the Atlantic meridional overturning circulation. J. Clim. 20(10), 2121-2132.
    • Schneider von Deimling, T., Held, H., Ganopolski, A. and Rahmstorf, S. 2006. Climate sensitivity estimated from ensemble simulations of glacial climate. Clim. Dyn. 27, 149-163.
    • Siegenthaler, U. and Joos, F. 1992. Use of a simple model for studying oceanic tracer distributions and the global carbon cycle. Tellus B 44, 186-207.
    • Stommel, H. 1961. Thermohaline convection with two stable regimes of flow. Tellus 13(2), 224-230.
    • Stouffer, R. J., Yin, J., Gregory, J. M., Dixon, K. W., Spelman, M. J. and co-authors. 2006. Investigating the causes of the response of the thermohaline circulation to past and future climate changes. J. Clim. 19(8), 1365-1387.
    • Tanaka, K., Kriegler, E., Bruckner, T., Hooss, G., Knorr, W. and coauthors. 2007. Aggregated carbon cycle, atmospheric chemistry, and climate model (ACC2). description of the forward and inverse modes (Reports on Earth System Science No. 40), Technical report, Hamburg, Germany.
    • Tomassini, L., Reichert, P., Knutti, R., Stocker, T. F. and Borsuk, M. E. 2007. Robust Bayesian uncertainty analysis of climate system properties using Markov chain Monte Carlo methods. J. Clim. 20, 1239-1254.
    • Urban, N. M. and Keller, K. 2009. Complementary constraints on climate sensitivity. Geophys. Res. Lett. 36, L04708.
    • Vellinga, M. and Wood, R. A. 2002. Global climatic impacts of a collapse of the Atlantic thermohaline circulation. Clim. Change 54(3), 251-267.
    • Vizcaino, M., Mikolajewicz, U., Groger, M., Maier-Reimer, E., Schurgers, G. and co-authors. 2008. Long-term ice sheet-climate interactions under anthropogenic greenhouse forcing simulated with a complex Earth System Model. Clim. Dyn. 31, 665-690.
    • Webster, M. D., Babiker, M., Mayer, M., Reilly, J. M., Harnisch, J. and co-authors. 2002. Uncertainty in emissions projections for climate models. Atmos. Environ. 36(22), 3659-3670.
    • Wood, R. A., Vellinga, M. and Thorpe, R. 2003. Global warming and thermohaline circulation stability. Phil. Trans. R. Soc. Lond. Ser. AMath. Phys. Eng. Sci. 361(1810), 1961-1974.
    • Yohe, G., Schlesinger, M. E. and Andronova, N. G. 2006. Reducing the risk of a collapse of the Atlantic thermohaline circulation. Integr. Assess. J. 6(1), 57-73.
    • Zickfeld, K., Slawig, T. and Rahmstorf, S. 2004. A low-order model for the response of the Atlantic thermohaline circulation to climate change. Ocean Dyn. 54(1), 8-26.
    • Zickfeld, K., Levermann, A., Morgan, M. G., Kuhlbrodt, T., Rahmstorf, S. and co-authors. 2007. Expert judgements on the response of the Atlantic meridional overturning circulation to climate change. Clim. Change 82, 235-265.
    • Zickfeld, K., Eby, M. and Weaver, A. J. 2008. Carbon-cycle feedbacks of changes in the Atlantic meridional overturning circulation under future atmospheric CO2. Global Biogeochem. Cycles 22, GB3024.
    • Zwally, H. J., Abdalati, W., Herring, T., Larson, K., Saba, J. and Steffen, K. 2002. Surface melt-induced acceleration of Greenland ice-sheet flow. Science 297(5579), 218-222.
  • Inferred research data

    The results below are discovered through our pilot algorithms. Let us know how we are doing!

    Title Trust
  • Discovered through pilot similarity algorithms. Send us your feedback.

Share - Bookmark

Cite this article

Collected from