A novel method to improve temperature simulations of general circulation models based on ensemble empirical mode decomposition and its application to multi-model ensembles

References

• Annan J. D. , Hargreaves J. C . Reliability of the CMIP3 ensemble. Geophys. Res. Lett. 2010; 37: L2703.
   Web of Science ®Google Scholar
• Berliner L. M. , Kim Y . Bayesian design and analysis for superensemble-based climate forecasting. J. Clim. 2008; 21: 1891–1910.
   Web of Science ®Google Scholar
• Breaker L. C. , Ruzmaikin A . The 154-year record of sea level at San Francisco: extracting the long-term trend, recent changes, and other tidbits. Clim. Dynam. 2011; 36: 545–559.
   Web of Science ®Google Scholar
• Chen D. , Achberger C. , Räisänen J. , Hellström C . Using statistical downscaling to quantify the GCM-related uncertainty in regional climate change scenarios: a case study of Swedish precipitation. Adv. Atmos. Sci. 2006; 23: 54–60.
   Web of Science ®Google Scholar
• Collins M. , Booth B. B. , Bhaskaran B. , Harris G. R. , Murphy J. M. , co-authors . Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles. Clim. Dynam. 2011; 36: 1737–1766.
   Web of Science ®Google Scholar
• Daubechies I . Orthonormal bases of compactly supported wavelets. Commun. Pure Appl. Math. 1988; 41: 909–996.
   Web of Science ®Google Scholar
• Daubechies I . Symmetry for Compactly Supported Wavelet Bases. Ten lectures on wavelets. 1992; Philadelphia: Society for Industrial and Applied Mathematics. 251–287.
   Google Scholar
• Doblas Reyes F. J. , Hagedorn R. , Palmer T. N . The rationale behind the success of multi-model ensembles in seasonal forecasting–II. Calibration and combination. Tellus A. 2005; 57: 234–252.
   Google Scholar
• Duan Q. , Ajami N. K. , Gao X. , Sorooshian S . Multi-model ensemble hydrologic prediction using Bayesian model averaging. Adv Water Resour. 2007; 30: 1371–1386.
   Web of Science ®Google Scholar
• Feddersen H. , Navarra A. , Ward M. N . Reduction of model systematic error by statistical correction for dynamical seasonal predictions. J Clim. 1999; 12: 1974–1989.
   Web of Science ®Google Scholar
• Franzke C . Long-range dependence and climate noise characteristics of Antarctic temperature data. J. Clim. 2010; 23: 6074–6081.
   Web of Science ®Google Scholar
• Gates W. L. , Boyle J. S. , Covey C. , Dease C. G. , Doutriaux C. M. , co-authors . An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I). Bull. Am. Meteorol. Soc. 1999; 80: 29–55.
   Web of Science ®Google Scholar
• Giorgi F. , Mearns L. O . Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “reliability ensemble averaging” (REA) method. J. Clim. 2002; 15: 1141–1158.
   Web of Science ®Google Scholar
• Giorgi F. , Mearns L. O . Probability of regional climate change based on the reliability ensemble averaging (REA) method. Geophys. Res. Lett. 2003; 30: 1629.
   Web of Science ®Google Scholar
• Graps A . An introduction to wavelets. Comput. Sci. Eng. 1995; 2: 50–61.
   Web of Science ®Google Scholar
• Hagedorn R. , Doblas Reyes F. J. , Palmer T. N . The rationale behind the success of multi-model ensembles in seasonal forecasting–I. Basic concept. Tellus A. 2005; 57: 219–233.
   Google Scholar
• Huang N. E. , Shen Z. , Long S. R . A new view of nonlinear water waves: the Hilbert spectrum 1. Annu. Rev. Fluid. Mech. 1999; 31: 417–457.
   Web of Science ®Google Scholar
• Huang N. E. , Shen Z. , Long S. R. , Wu M. C. , Shih H. H. , co-authors . The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. Roy. Soc. Lond. 1998; 454: 903–995.
   Web of Science ®Google Scholar
• Huang N. E. , Wu Z . A review on Hilbert-Huang transform: method and its applications to geophysical studies. Rev. Geophys. 2008; 46: G2006.
   Web of Science ®Google Scholar
• IPCC (Intergovernmental Panel on Climate Change). Climate Change 2007: Synthesis Report. 2007; Cambridge: Cambridge University Press.
   Google Scholar
• Kharin V. V. , Zwiers F. W . Climate predictions with multimodel ensembles. J. Clim. 2002; 15: 793–799.
   Web of Science ®Google Scholar
• Krishnamurti T. N. , Kishtawal C. M. , LaRow T. E. , Bachiochi D. R. , Zhang Z. , co-authors . Improved weather and seasonal climate forecasts from multimodel superensemble. Science. 1999; 285: 1548–1550.
   PubMed Web of Science ®Google Scholar
• Krishnamurti T. N. , Kishtawal C. M. , Shin D. W. , Williford C. E . Improving tropical precipitation forecasts from a multianalysis superensemble. J. Clim. 2000; 13: 4217–4227.
   Web of Science ®Google Scholar
• Min S. K. , Hense A . A Bayesian approach to climate model evaluation and multi-model averaging with an application to global mean surface temperatures from IPCC AR4 coupled climate models. Geophys. Res. Lett. 2006a; 33: L8708.
   Web of Science ®Google Scholar
• Min S. K. , Hense A . A Bayesian assessment of climate change using multimodel ensembles. Part I: global mean surface temperature. J. Clim. 2006b; 19: 3237–3256.
   Web of Science ®Google Scholar
• Pagowski M. , Grell G. A. , McKeen S. A. , Dévényi D. , Wilczak J. M. , co-authors . A simple method to improve ensemble-based ozone forecasts. Geophys. Res. Lett. 2005; 32: L7814.
   Web of Science ®Google Scholar
• Peng P. , Kumar A. , van den Dool H. , Barnston A. G . An analysis of multi-model ensemble predictions for seasonal climate anomalies. J. Geophy. Res. 2002; 107: ACL–18.
   Web of Science ®Google Scholar
• Qian C. , Fu C. , Wu Z. , Yan Z . On the secular change of spring onset at Stockholm. Geophys. Res. Lett. 2009; 36: L12706.
   Web of Science ®Google Scholar
• Raftery A. E. , Gneiting T. , Balabdaoui F. , Polakowski M . Using Bayesian model averaging to calibrate forecast ensembles. Mon. Weather Rev. 2005; 133: 1155–1174.
   Web of Science ®Google Scholar
• Reifen C. , Toumi R . Climate projections: past performance no guarantee of future skill. Geophys. Res. Lett. 2009; 36: L13704.
   Web of Science ®Google Scholar
• Semenov M. A. , Stratonovitch P . Use of multi-model ensembles from global climate models for assessment of climate change impacts. Clim. Res. 2010; 41: 1–14.
   Web of Science ®Google Scholar
• Shin D. W. , Krishnamurti T. N . Short-to medium-range superensemble precipitation forecasts using satellite products: 2. Probabilistic forecasting. J. Geophys. Res. 2003; 108: 8384.
   Web of Science ®Google Scholar
• Tebaldi C. , Knutti R . The use of the multi-model ensemble in probabilistic climate projections. Phil Trans Roy. Soc A. 2007; 365: 2053–2075.
   PubMed Web of Science ®Google Scholar
• Weigel A. P. , Liniger M. A. , Appenzeller C . Can multi-model combination really enhance the prediction skill of probabilistic ensemble forecasts?. Q. J. Roy. Meteorol. Soc. 2008; 134: 241–260.
   Web of Science ®Google Scholar
• Weisheimer A. , Doblas-Reyes F. J. , Palmer T. N. , Alessandri A. , Arribas A. , co-authors . ENSEMBLES: a new multi-model ensemble for seasonal-to-annual predictions: Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs. Geophys. Res. Lett. 2009; 36: L21711.
   Web of Science ®Google Scholar
• Weisheimer A. , Smith L. A. , Judd K . A new view of seasonal forecast skill: bounding boxes from the DEMETER ensemble forecasts. Tellus A. 2005; 57: 265–279.
   Google Scholar
• Wu Z. , Huang N. E . Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv. Adapt. Data Anal. 2009; 1: 1–41.
   Google Scholar
• Wu Z. , Huang N. E. , Long S. R. , Peng C . On the trend, detrending, and variability of nonlinear and nonstationary time series. Proc Natl Acad Sci. 2007; 104: 14889–14894.
   PubMed Web of Science ®Google Scholar
• Wu Z. , Schneider E. K. , Kirtman B. P. , Sarachik E. S. , Huang N. E. , co-authors . The modulated annual cycle: an alternative reference frame for climate anomalies. Clim. Dynam. 2008; 31: 823–841.
   Web of Science ®Google Scholar
• Yun W. T. , Stefanova L. , Krishnamurti T. N . Improvement of the multimodel superensemble technique for seasonal forecasts. J. Clim. 2003; 16: 3834–3840.
   Web of Science ®Google Scholar