Probabilistic Estimates of Transient Climate Sensitivity Subject to Uncertainty in Forcing and Natural Variability
In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estim...
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| Vydáno v: | Journal of climate Ročník 24; číslo 21; s. 5521 - 5537 |
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Boston, MA
American Meteorological Society
01.11.2011
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| ISSN: | 0894-8755, 1520-0442 |
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| Abstract | In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estimates of the TCS that combine these two sources of uncertainty for various underlying assumptions about the nature of the uncertainty. The authors also provide estimates of how quickly the uncertainty in the TCS may be expected to diminish in the future as additional observations become available. These estimates are made using a nonlinear Kalman filter coupled to a stochastic, global energy balance model, using the filter and observations to constrain the model parameters. This study verifies that model and filter are able to emulate the evolution of a comprehensive, state-of-the-art atmosphere–ocean general circulation model and to accurately predict the TCS of the model, and then apply the methodology to observed temperature and forcing records of the twentieth century.
For uncertainty assumptions best supported by global surface temperature data up to the present time, this paper finds a most likely present-day estimate of the transient climate sensitivity to be 1.6 K, with 90% confidence the response will fall between 1.3 and 2.6 K, and it is estimated that this intervalmay be 45% smaller by the year 2030. The authors calculate that emissions levels equivalent to forcing of less than 475 ppmv CO₂ concentration are needed to ensure that the transient temperature response will not exceed 2 K with 95% confidence. This is an assessment for the short-to-medium term and not a recommendation for long-term stabilization forcing; the equilibrium temperature response to this level of CO₂ may be much greater. The flat temperature trend of the last decade has a detectable but small influence on TCS. This study describes how the results vary if different uncertainty assumptions are made and shows they are robust to variations in the initial prior probability assumptions. |
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| AbstractList | In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estimates of the TCS that combine these two sources of uncertainty for various underlying assumptions about the nature of the uncertainty. The authors also provide estimates of how quickly the uncertainty in the TCS may be expected to diminish in the future as additional observations become available. These estimates are made using a nonlinear Kalman filter coupled to a stochastic, global energy balance model, using the filter and observations to constrain the model parameters. This study verifies that model and filter are able to emulate the evolution of a comprehensive, state-of-the-art atmosphere–ocean general circulation model and to accurately predict the TCS of the model, and then apply the methodology to observed temperature and forcing records of the twentieth century.For uncertainty assumptions best supported by global surface temperature data up to the present time, this paper finds a most likely present-day estimate of the transient climate sensitivity to be 1.6 K, with 90% confidence the response will fall between 1.3 and 2.6 K, and it is estimated that this interval may be 45% smaller by the year 2030. The authors calculate that emissions levels equivalent to forcing of less than 475 ppmv CO2 concentration are needed to ensure that the transient temperature response will not exceed 2 K with 95% confidence. This is an assessment for the short-to-medium term and not a recommendation for long-term stabilization forcing; the equilibrium temperature response to this level of CO2 may be much greater. The flat temperature trend of the last decade has a detectable but small influence on TCS. This study describes how the results vary if different uncertainty assumptions are made and shows they are robust to variations in the initial prior probability assumptions. In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estimates of the TCS that combine these two sources of uncertainty for various underlying assumptions about the nature of the uncertainty. The authors also provide estimates of how quickly the uncertainty in the TCS may be expected to diminish in the future as additional observations become available. These estimates are made using a nonlinear Kalman filter coupled to a stochastic, global energy balance model, using the filter and observations to constrain the model parameters. This study verifies that model and filter are able to emulate the evolution of a comprehensive, state-of-the-art atmosphere–ocean general circulation model and to accurately predict the TCS of the model, and then apply the methodology to observed temperature and forcing records of the twentieth century. For uncertainty assumptions best supported by global surface temperature data up to the present time, this paper finds a most likely present-day estimate of the transient climate sensitivity to be 1.6 K, with 90% confidence the response will fall between 1.3 and 2.6 K, and it is estimated that this interval may be 45% smaller by the year 2030. The authors calculate that emissions levels equivalent to forcing of less than 475 ppmv CO2 concentration are needed to ensure that the transient temperature response will not exceed 2 K with 95% confidence. This is an assessment for the short-to-medium term and not a recommendation for long-term stabilization forcing; the equilibrium temperature response to this level of CO2 may be much greater. The flat temperature trend of the last decade has a detectable but small influence on TCS. This study describes how the results vary if different uncertainty assumptions are made and shows they are robust to variations in the initial prior probability assumptions. In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estimates of the TCS that combine these two sources of uncertainty for various underlying assumptions about the nature of the uncertainty. The authors also provide estimates of how quickly the uncertainty in the TCS may be expected to diminish in the future as additional observations become available. These estimates are made using a nonlinear Kalman filter coupled to a stochastic, global energy balance model, using the filter and observations to constrain the model parameters. This study verifies that model and filter are able to emulate the evolution of a comprehensive, state-of-the-art atmosphere–ocean general circulation model and to accurately predict the TCS of the model, and then apply the methodology to observed temperature and forcing records of the twentieth century. For uncertainty assumptions best supported by global surface temperature data up to the present time, this paper finds a most likely present-day estimate of the transient climate sensitivity to be 1.6 K, with 90% confidence the response will fall between 1.3 and 2.6 K, and it is estimated that this intervalmay be 45% smaller by the year 2030. The authors calculate that emissions levels equivalent to forcing of less than 475 ppmv CO₂ concentration are needed to ensure that the transient temperature response will not exceed 2 K with 95% confidence. This is an assessment for the short-to-medium term and not a recommendation for long-term stabilization forcing; the equilibrium temperature response to this level of CO₂ may be much greater. The flat temperature trend of the last decade has a detectable but small influence on TCS. This study describes how the results vary if different uncertainty assumptions are made and shows they are robust to variations in the initial prior probability assumptions. In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estimates of the TCS that combine these two sources of uncertainty for various underlying assumptions about the nature of the uncertainty. The authors also provide estimates of how quickly the uncertainty in the TCS may be expected to diminish in the future as additional observations become available. These estimates are made using a nonlinear Kalman filter coupled to a stochastic, global energy balance model, using the filter and observations to constrain the model parameters. This study verifies that model and filter are able to emulate the evolution of a comprehensive, state-of-the-art atmosphere-ocean general circulation model and to accurately predict the TCS of the model, and then apply the methodology to observed temperature and forcing records of the twentieth century. For uncertainty assumptions best supported by global surface temperature data up to the present time, this paper finds a most likely present-day estimate of the transient climate sensitivity to be 1.6 K, with 90% confidence the response will fall between 1.3 and 2.6 K, and it is estimated that this interval may be 45% smaller by the year 2030. The authors calculate that emissions levels equivalent to forcing of less than 475 ppmv CO2 concentration are needed to ensure that the transient temperature response will not exceed 2 K with 95% confidence. This is an assessment for the short-to-medium term and not a recommendation for long-term stabilization forcing; the equilibrium temperature response to this level of CO2 may be much greater. The flat temperature trend of the last decade has a detectable but small influence on TCS. This study describes how the results vary if different uncertainty assumptions are made and shows they are robust to variations in the initial prior probability assumptions. [PUBLICATION ABSTRACT] |
| Author | Padilla, Lauren E. Rowley, Clarence W. Vallis, Geoffrey K. |
| Author_xml | – sequence: 1 givenname: Lauren E. surname: Padilla fullname: Padilla, Lauren E. organization: Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey – sequence: 2 givenname: Geoffrey K. surname: Vallis fullname: Vallis, Geoffrey K. organization: GFDL, Princeton University, Princeton, New Jersey – sequence: 3 givenname: Clarence W. surname: Rowley fullname: Rowley, Clarence W. organization: Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey |
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| Cites_doi | 10.1029/2008GL034932 10.1175/2010JCLI3380.1 10.1175/1520-0442(2002)015<0124:TROCSA>2.0.CO;2 10.1175/1520-0469(2004)061<0264:AMASDM>2.0.CO;2 10.1126/science.1064419 10.1038/416723a 10.1175/JCLI3363.1 10.5194/npg-12-363-2005 10.1029/2007GL032904 10.1109/ACC.2002.1025369 10.1029/2007GL031383 10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2 10.1029/2005JD006548 10.1029/98GL01908 10.1007/s003820050185 10.1029/2004GL022241 10.1175/1520-0442(2002)015<2837:SCCSAA>2.0.CO;2 10.1175/JCLI3802.1 10.1175/2009JCLI3089.1 10.1175/JCLI3629.1 10.5194/acp-7-2287-2007 10.1029/2005GL023977 10.1002/cpa.1014 10.1029/2008JD010405 10.1126/science.1144735 10.1175/JCLI3864.1 10.1038/35036559 10.2151/sola.2005-047 10.1029/94JC00572 10.1175/2009JCLI2647.1 10.1175/2007JCLI2119.1 10.1029/2010GL042911 10.1175/2009JCLI3466.1 |
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| Keywords | Short term Transient response trend-surface analysis General circulation models stabilization sensitivity analysis Carbon dioxide Non linear filter Surface temperature energy balance digital simulation ocean-atmosphere interaction Long term greenhouse gas Ocean-atmosphere model Century 20th Forcing Medium term transient phenomena Kalman filters uncertainties |
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| SubjectTerms | 20th century Aerosols Atmospheric circulation Carbon dioxide Carbon dioxide concentration Climate Climate change Climate models Climate sensitivity Conditional probability Confidence interval Confidence intervals Earth, ocean, space Emissions Energy balance Equilibrium Estimates Exact sciences and technology External geophysics General circulation models Global climate models Global temperatures Global warming Heat Kalman filters Modelling Natural variability Ocean temperature Oceanic general circulation model Oceans Parametric models Probability theory Sensitivity Standard deviation Statistical analysis Surface temperature Temperature Temperature data Uncertainty Variability |
| Title | Probabilistic Estimates of Transient Climate Sensitivity Subject to Uncertainty in Forcing and Natural Variability |
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