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PRECLIM (part 1) DeClips / model weighting NCCR WP2 Meeting, 5 October 2010

PRECLIM (part 1) DeClips / model weighting NCCR WP2 Meeting, 5 October 2010. Andreas Weigel, Reidun Gangsto, Andreas Fischer, Reto Knutti, Mark Lingier, Christof Appenzeller. decadal. NCCR 1+2. Predictions at different time-scales. monthly. seasonal. weather. multi-decadal. Declips

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PRECLIM (part 1) DeClips / model weighting NCCR WP2 Meeting, 5 October 2010

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  1. PRECLIM (part 1)DeClips / model weightingNCCR WP2 Meeting, 5 October 2010 Andreas Weigel, Reidun Gangsto, Andreas Fischer, Reto Knutti, Mark Lingier, Christof Appenzeller

  2. decadal NCCR 1+2 Predictions at different time-scales monthly seasonal weather multi-decadal Declips (with SwissRe) Preclim Traditional MCH NCCR 3

  3. Sources of uncertainty in decadal mean temperature projections Hawkins and Sutton, 2009

  4. Decadal predictions • Decadal time scale represents planning horizon for • infrastructure • energy • insurance • agriculture • fishery • … • Pioneering studies indicate potential decadal predictabi- lity in North Atlantic region (Smith et al. 2008, Keenlyside et al. 2008) • Currently field of intensive research. Will be considered in IPCC AR5. • Experimental data-set available from EU FP6 ENSEMBLES Keenlyside et al (2008)

  5. ENSEMBLES decadal predictions Ensemble size Hindcast-Periods Model 3 1960-1970 3 1965-1975 IFS / HOPE (ECMWF) 3 … 3 2005-2015 3 1960-1970 3 1965-1975 Different initial con-ditions HadGEM2 (Met Office) … 3 2005-2015 3 3 1960-1970 3 1965-1975 ARPEGE4 (CERFACS) … 3 2005-2015 3 3 1960-1970 3 1965-1975 ECHAM5 (IfM Kiel) 3 … 3 2005-2015 9 1960-1970 Per-turbed physics 9 1961-1971 DePreSys (Met Office) 9 1962-1972 9 … 9 2005-2015

  6. Research tasks • Establish verification framework for decadal forecasts • Small sample size • Lack of observations for 3D ocean in earlier decades • Two-step assessment: Trend & remaining fluctuations • Skill assessment for Europe (T and other variables) • Comparison to other strategies (stat. models, persistence, …) • Added value • Investigate potential applications for the reinsurance business (SwissRe application model and/or toymodel) • Apply to newer model runs according to availability (e.g. CMIP5)

  7. Hindcasts of T2 (°C) Global annual average T2 (IFS vs observations) Anomalies (°C) Global annual average T2 (ARPEGE vs observations) Need to correct for drift and systematic errors

  8. decadal NCCR 1+2 Predictions at different time-scales monthly seasonal weather multi-decadal Declips (with SwissRe) Preclim Traditional MCH NCCR 3

  9. PDF Probabilistic climate projections Modelled Climate Change Signals Weighting? Statistical model (e.g. Buser et al. 2009) (presentation A. Fischer)

  10. First PRECLIM-Paper… Weigel et al., J. Clim. 2010

  11. Effects of weighting Increase of error (MSE) Benchmark Equal weights Decrease of error (MSE) Both models have same skill Model 2 inifintely better than Model 1 Weigel et al, 2010, J. Clim.

  12. Effects of weighting Increase of error (MSE) Benchmark Equal weights Optimal weights Decrease of error (MSE) Both models have same skill Model 2 inifintely better than Model 1 Weigel et al, 2010, J. Clim.

  13. Effects of weighting Increase of error (MSE) Worst possible weights Benchmark Equal weights Optimal weights Decrease of error (MSE) Both models have same skill Model 2 inifintely better than Model 1 Weigel et al, 2010, J. Clim.

  14. Effects of weighting Increase of error (MSE) Random weights Benchmark Equal weights Optimal weights Decrease of error (MSE) Both models have same skill Model 2 inifintely better than Model 1 Weigel et al, 2010, J. Clim.

  15. PDF Probabilistic climate projections Modelled Climate Change Signals Weighting? Statistical model (e.g. Buser et al. 2009) (presentation A. Fischer)

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