Uncertainty in temperature projections reduced using carbon cycle and climate observations

The response of the carbon cycle to climate change, including carbon fluxes, is now shown to be the second largest source of uncertainty in projections of temperature. A simplified climate model using temperature records and historical estimates of CO2 concentrations demonstrates that considering these two factors together reduces uncertainty further than treating them as individual parameters.

[1]  M. Sambridge,et al.  Monte Carlo analysis of inverse problems , 2002 .

[2]  Andrei P. Sokolov,et al.  Constraining climate model parameters from observed 20th century changes , 2008 .

[3]  R. Betts,et al.  High sensitivity of future global warming to land carbon cycle processes , 2012 .

[4]  Peter J. Gleckler,et al.  Improved estimates of upper-ocean warming and multi-decadal sea-level rise , 2008, Nature.

[5]  Myles R. Allen,et al.  Constraining climate forecasts: The role of prior assumptions , 2005 .

[6]  I. Enting,et al.  Observational constraints on parameter estimates for a simple climate model , 2013 .

[7]  J. Hansen,et al.  A slippery slope: How much global warming constitutes “dangerous anthropogenic interference”? , 2005 .

[8]  N. Meinshausen,et al.  Greenhouse-gas emission targets for limiting global warming to 2 °C , 2009, Nature.

[9]  M. Scholze,et al.  Constraining predictions of the carbon cycle using data , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[10]  T. Raddatz,et al.  Correlation between climate sensitivity and aerosol forcing and its implication for the “climate trap” , 2011 .

[11]  John F. B. Mitchell,et al.  THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research , 2007 .

[12]  Pierre Friedlingstein,et al.  A Review of Uncertainties in Global Temperature Projections over the Twenty-First Century , 2008 .

[13]  Vincent R. Gray Climate Change 2007: The Physical Science Basis Summary for Policymakers , 2007 .

[14]  Alexei G. Sankovski,et al.  Special report on emissions scenarios , 2000 .

[15]  R. Schnur,et al.  Climate-carbon cycle feedback analysis: Results from the C , 2006 .

[16]  T. Wigley,et al.  Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration , 2011 .

[17]  Joeri Rogelj,et al.  Global warming under old and new scenarios using IPCC climate sensitivity range estimates , 2012 .

[18]  M. Webb,et al.  Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles , 2011 .

[19]  P. Jones,et al.  Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850 , 2006 .

[20]  Nebojsa Nakicenovic,et al.  Avoiding dangerous climate change , 2006 .

[21]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[22]  K. Calvin,et al.  The RCP greenhouse gas concentrations and their extensions from 1765 to 2300 , 2011 .

[23]  W. Knorr,et al.  Inversion of terrestrial ecosystem model parameter values against eddy covariance measurements by Monte Carlo sampling , 2005 .

[24]  R. Bodman Estimating uncertainties in future global warming using a simple climate model , 2011 .

[25]  Albert Tarantola,et al.  Inverse problem theory - and methods for model parameter estimation , 2004 .

[26]  K. Davis,et al.  A Bayesian calibration of a simple carbon cycle model: The role of observations in estimating and reducing uncertainty , 2008 .

[27]  Pieter P. Tans,et al.  Extension and integration of atmospheric carbon dioxide data into a globally consistent measurement record , 1995 .