Abstract
Abstract. It has been shown that lag-covariance based statistical measures, suggested by the Fluctuation Dissipation Theorem (FDT), may allow estimation of climate sensitivity in a climate model. Recently Schwartz (2007) has used measures of the decay of autocorrelation in a global surface temperature time series to estimate the real world climate sensitivity. Here we use a simple climate model, and analysis of archived coupled climate model output from the IPCC AR4 runs, for which the climate sensitivity is known, to test the utility of this approach. Our analysis of these archived model output data show that estimates of climate sensitivity derived from century-long time scales typically grossly underestimate the models' true climate sensitivity. We analyze the behavior of the simple model with adjustable heat capacity in two surface layers, subject to various stochastic forcings and for various climate sensitivities, modulated by albedo and water vapor feedbacks. We use our simple climate model to demonstrate: 1. that a much longer time series would be required to accurately diagnose the earth's climate sensitivity than is presently available 2. that for shorter time series there is a systematic bias towards underpredicting climate sensitivity, 3. that the addition of a second heat reservoir weakly coupled to the first greatly reduces the decorrelation timescale of short temperature time series produced by the model, aggravating the tendency to underestimate climate sensitivity, and 4. that because of this it is possible to have a selection of models in which the climate sensitivity is inversely related to the decorrelation time scale, as is true for the IPCC models.
Highlights
An accurate determination of the earth’s climate sensitivity, the expected mean surface temperature response to a doubling of carbon dioxide concentration, has been the outstanding problem in climate dynamics for the last several decades. Leith (1975) and Bell (1980) introduced the idea that the climate sensitivity of the earth or of a general circulation model (GCM) could be predicted using the Fluctuation Dissipation Theorem (FDT) (Callen and Green, 1952)
Bell (1980) and Cionni et al (2004) were able to show that global climate sensitivity could be predicted to useful accuracy for a simplified climate model and for a highly complex chemical GCM, respectively, using measures based on the FDT
We investigate the practical usefulness of the FDT for the purpose of diagnosing climate sensitivity
Summary
An accurate determination of the earth’s climate sensitivity, the expected mean surface temperature response to a doubling of carbon dioxide concentration, has been the outstanding problem in climate dynamics for the last several decades. Leith (1975) and Bell (1980) introduced the idea that the climate sensitivity of the earth or of a general circulation model (GCM) could be predicted using the Fluctuation Dissipation Theorem (FDT) (Callen and Green, 1952). Knutti et al (2008) compares predicted and realized climate sensitivity in the AR4 GCM runs, while Scafetta (2008) and Foster et al (2008) use simplified a climate model to simulate the ability of the FDT to estimate climate sensitivity. They concluded that the method of Schwartz (2007) would systematically underestimate climate sensitivity. These errors are due both to the inadequate length of the time series involved, and to the assumption of a single heat capacity for the climate system
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