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We applied a low-pass, 21-point binomial filter (half power at periods near 10 years), as used in the Intergovernmental Panel on Climate Change (IPCC) assessment (1).
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note
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A brief description of the five climate models is provided in the Supporting Online Material, together with references to publications providing more details.
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12
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0242645672
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note
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For each of the models, we used data from long control simulations that have been performed with no changes to the external forcing parameters. The control simulations include 990 years of data from HadCM2, 1830 years from HadCM3, 500 years from GFDL R30, 240 years from ECHAM4, and 530 years from NCAR PCM. The 530-year period from PCM came from years 390 to 919 of the control run, after most of the initial climate drift had stabilized. Data for DTR were not available from the HadCH3 model and could not be determined from the GFDL model, which does not include a diurnal cycle of solar irradiance,
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13
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0242645673
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note
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2 according to IPCC scenario 1592a for the period 1880-2000, along with estimated observed changes in anthropogenic sulfate aerosols represented through regional changes to surface albedo. For the HadCM3 (21), ECHAM4, and PCM (22) models, observed increases in individual major anthropogenic greenhouse gases are included, together with changes in tropospheric and stratospheric ozone and an explicit treatment of the direct radiative effect of sulfate aerosols. HadCM3 and ECHAM4 also include parameterizations for indirect sulfate forcing effects via cloud albedo changes. From HadCM2 and HadCM3, we have four independent members of an ensemble of simulations with different initial conditions, three GS ensemble members from GFDL R30, two from ECHAM4, and seven from PCM.
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14
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0242645674
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note
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The natural externally forced model simulations include fixed greenhouse gas concentrations and estimated changes in total solar irradiance and stratospheric volcanic aerosol optical depth for the period 1880-1999. Somewhat different solar and volcanic forcing data sets are used for the different models. For the HadCM2 (three ensemble members) and HadCM3 (four ensemble members) simulations, the solar forcing is based on Lean et al. (23) and the volcanic forcing is based on updated data from Sato (24). For the GFDL model (20), the solar forcing is based on Lean (25) and the volcanic forcing is based on Andronova et al. (26). For the NCAR PCM simulations (27) (four ensemble members), the solar forcing is based on Hoyt and Schatten (28) and the volcanic forcing is based on Ammann et al. (29). For the GFDL model, simulations with natural external forcing alone were not available, so the NAT response was estimated from the difference between model. simulations with all forcings (both anthropogenic forcing and natural external forcing, three ensemble members each) and simulations with anthropogenic forcing alone (three ensemble members); that is, NAT response ∼ (GS + NAT) response-GS response. For the HadCM2 model, only simulations with separate solar (SOL) and volcanic (VOL) forcing were available, so the NAT response was estimated as the sum of these model responses; that is, NAT response ∼ SOL response + VOL response.
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The uncertainty of the ensemble mean 50-year and 100-year trends due to natural internal variability was estimated by resampling trends from the long control simulations from the respective models and allowing for the number of members in each ensemble. Further details of the approach used for estimating natural internal variability are given in the Supporting Online Material.
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17
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0242477245
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note
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Consistency here means that the observed trend lies within the 90% confidence interval for the ensemble-mean forced trend (shown as the error bar about the forced model trend) combined with the 90% confidence interval for a single realization due to natural internal climate variability (shown as the error bar about zero trend).
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in preparation
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note
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We acknowledge the assistance of the many scientists who developed the observational data sets and the climate models used in this study. Constructive comments from a number of reviewers helped to improve this manuscript. Supported by a Discovery grant from the Australian Research Council (K.B.); the UK Department for Environment, Food and Rural Affairs under contract PECD 7/12/37 (P.A.S.); and NSF and the Office of Biological and Environmental Research, U.S. Department of Energy (J.M.A., G.A.M.).
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