Science Advances

Supplementary Materials

This PDF file includes:

  • section S1. Key forcings used expressed in absolute units
  • section S2. Separating the two AMO time series and ENSO from the IPO
  • section S3. The REML linear temperature change method
  • section S4. CMIP5 model experiments used
  • section S5. Structure of the regression equations and cross-correlation of predictors
  • section S6. Comparison of annual reconstruction and CMIP5 root mean square errors with estimated WMO GST annual uncertainties
  • section S7. Reconstruction and CMIP5 correlation statistics for 1941–1975
  • section S8. Substituting ERA Interim GST for WMO GST for 1997–2015
  • section S9. Response times of GST to TSI forcing
  • section S10. Further details of the WMO data sets
  • section S11. Structure of multiple regression residuals and cross-correlation of predictors
  • fig. S1. Volcanic, solar, and GA forcings in original units without smoothing, expressed as anomalies from their 1961–1990 averages.
  • fig. S2. Additional details of monthly time series of the predictors.
  • fig. S3. Maximum likelihood plot of the serial correlation of the residuals and their variance for the reconstructed linear component of WMO temperature change over 2001–2013.
  • fig. S4. Identifying the boundaries between consecutive slowdown and warming periods using trend analysis.
  • fig. S5. Reconstructed and CMIP5 root mean square errors for annual data compared to one-sigma uncertainties in annual WMO GST values including additional uncertainties due to the spread of the three component data sets.
  • fig. S6. Comparing the reconstructions using ERA Interim and WMO GST during slowdown period 3.
  • fig. S7. As in the Fig. 6C panels for 1998–2013, 2001–2010, and 2001–2013 in the main text but for ERA Interim.
  • fig. S8. Original (unfiltered) and e-folded monthly TSI time series January 1981 to December 2015 reflecting the three sets of delayed e-folding response times used in the paper.
  • table S1. CMIP5 models and historical experiments used in this paper.
  • table S2. Combinations of predictors used in the 18 main regression equations.
  • table S3. Correlation skill of average reconstruction GST and CMIP5 average GST with WMO GST in slowdown period 2, 1941–1975.
  • table S4. Cross-correlation of monthly predictors 1891–2015.
  • table S5. Cross-correlation of monthly predictors 1951–2015.
  • References (57–59)

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