1. Baltic Sea Science Conference, 20 March 2007 Climate simulations for the last millennium. Implications for the Baltic Sea Hans von Storch and Eduardo Zorita Institute for Coastal Research GKSS Research Center Geesthacht, Germany

2. Baltic Sea Science Conference, 20 March 2007 Overview 1.Experimental set-up 2.Utility I: Testing validity of proxy derived indicators. Testing MBH and Luterbacher temp’s 3.Utility II: Estimating the unobservable. Examples (1) extra-tropical storminess (2) Baltic Sea region conditions

3. Baltic Sea Science Conference, 20 March 2007 ECHO-G simulations „Erik den Røde” (1000- 1990) and “Christoph Columbus” (1550-1990) with estimated volcanic, GHG and solar forcing Experimental set-up

4. Baltic Sea Science Conference, 20 March 2007 1675-1710 vs. 1550-1800 Reconstruction from historical evidence, from Luterbacher et al. Late Maunder Minimum Model-based reconstuction Skill of simulation

5. Baltic Sea Science Conference, 20 March 2007 Skill of simulation

6. Baltic Sea Science Conference, 20 March 2007 Skill of simulation

7. Baltic Sea Science Conference, 20 March 2007 Skill of simulation Old statement: Both, Erik den Røde and Christoph Columbus generate temperature variations considerably larger than standard reconstructions (Mann, Jones …). The simulated temperature variations are of a similar range as derived from NH summer dendro-data and from terrestrial boreholes.

8. Baltic Sea Science Conference, 20 March 2007 Conclusion, 1 1.Millennial simulations - efforts to simulate the response to estimated volcanic, GHG and solar forcing, 1000-2000. 2.Low-frequency variability in millennial simulations: > Mann, Jones, “hockeystick”, but ~ Esper, boreholes, (some) instrumental data

9. Baltic Sea Science Conference, 20 March 2007 Testing validity of proxy-derived indicators For the purpose of testing reconstruction methods, it does not really matter how „good“ the historical climate is reproduced by Erik den Røde. The model data provide a laboratory to test MBH and Luterbacher’s methodologies.

10. Baltic Sea Science Conference, 20 March 2007 Testing the MBH method pseudo-proxies: grid point SAT plus white noise red: mimicking largest sample used in MBH von Storch, H., E. Zorita, J. Jones, Y. Dimitriev, F. González-Rouco, and S. Tett, 2004: Reconstructing past climate from noisy data, Science 306, 679-682 and later comments and responses

11. Baltic Sea Science Conference, 20 March 2007 Testing validity of proxy-derived indicators

12. Baltic Sea Science Conference, 20 March 2007 Storminess New statement: Hockey-stick curve is likely an under- estimate of low- frequency variability. The bulk of recent reconstructions show significantly larger variability than the hockey- stick.

13. Baltic Sea Science Conference, 20 March 2007 Testing validity of proxy-derived indicators Testing the Luterbacher et al. (2004) reconstruction of European temperatures since 1500 Küttel, M., J. Luterbacher, E. Zorita, E. Xoplaki, N. Riedwyl and H. Wanner, 2007: Testing a European winter surface reconstruction in a surrogate climate. Geophys. Res. Lett., in press

14. Baltic Sea Science Conference, 20 March 2007 Applying the Luterbacher methodology to ECHO-G (top) and HadCM3 (bottom) simulation data, using the same decreasing network of proxy and instrumental data as available for Luterbacher. Proxy data are degraded by white noise, instrumental data not. Dashed lines represent 90% confidence bands.

15. Baltic Sea Science Conference, 20 March 2007 Conclusion Millennial simulation-data used to test methods for reconstructing historical temperature variations. Randomized grid-point SAT (i.e. red noise added) is used as pseudo proxy. MBH method, based on regression and inflation, suffers from significant under-estimation of low- frequency NH mean SAT. Luterbacher’s approach works fine with sufficiently dense data networks; it shows loss of low-frequency variability, when the network becomes too thin.

16. Baltic Sea Science Conference, 20 March 2007 Extratropical storminess Developing hypotheses about the variability of climate variables Baltic Sea Science Conference, 20 March 2007 Estimates based upon repair costs for dikes in Holland de Kraker, 1999 Very little evidence available Number of yearly events with air pressure < 980 hPa Lund and Stockholm Bärring and von Storch, 2004

17. Baltic Sea Science Conference, 20 March 2007 Storminess Fischer-Bruns, I., H. von Storch, F. González-Rouco and E. Zorita, 2005: Modelling the variability of midlatitude storm activity on decadal to century time scales. Clim. Dyn. 25: 461-476 Studying the variability of extratropical storminess during hundredth of years

18. Baltic Sea Science Conference, 20 March 2007 Storminess Pre-industrial: 1550-1850 change from pre-industrial to industrial period 1850-2000

19. Baltic Sea Science Conference, 20 March 2007 Storminess Storm shift index defined as PCs of storm frequency EOFs North Atlantic Mean near- surface temperature (red/orange) storm frequency index (blue), storm shift index (green) 2  band of preindustrial conditions

20. Baltic Sea Science Conference, 20 March 2007 Storminess - Conclusions 1.During historical times extra-tropical storminess is remarkably stationary with little variability. 2.During historical times, storminess and large-scale temperature variations are mostly decoupled. 3.There are indications for a poleward shift of the regions with high storm frequency on both hemispheres with future warming.

21. Baltic Sea Science Conference, 20 March 2007 The Baltic Sea Results for the Baltic Sea Region - Overall development - Maunder Minimum (downscaling)

22. Baltic Sea Science Conference, 20 March 2007 The Baltic Sea Gouirand, I., A. Moberg, and E. Zorita, 2007: Climate variability in Scandinavia for the past millennium simulated by an atmosphere-ocean egenral circulation model. Tellus 59A, 30-49 Low pass filtered Scandinavian temperatures - Simulated by ECHO-G (black) - Reconstructed from proxies (grey) - Uppsala temperature readings (dashed) Proxies: tree rings Proxies: ice break up AMJJA DJFM

23. Late Maunder Minimum Cold winters and springs, 1675-1710 Late Maunder Minimum Cold winters and springs, 1675-1710 Analysis of Columbus run, only.

24. Baltic Sea Science Conference, 20 March 2007 Temperature conditions in Switzerland according to Pfister‘s classification (1999). Late Maunder Minimum

25. Simulated global 1675-1710 temperature anomaly deMenocal et al. (2000) Ice conditions off Iceland (Koch, 1945)

26. Baltic Sea Science Conference, 20 March 2007 The Baltic Sea REMO model area; 0.5°x0.5° grid ECHO-G grid Dynamical Downscaling „normal“: 1625-1656 LMM : 1675-1705 Müller, B., 2004: Eine regionale Klimasimulation für Europa zur Zeit des späten Maunder Minimums 1675- 1710, GKSS Report 2004/2

27. Baltic Sea Science Conference, 20 March 2007 Lower boundary conditions area [%] Land-use Sea ice coverage after Koslowski (1999) 3.3.1692

28. Baltic Sea Science Conference, 20 March 2007 REMO Temperature differences LMM – non-LMM Luterbacher

29. Baltic Sea Science Conference, 20 March 2007 Mean difference of European air temperature during LMM and (pre-industrial) non-LMM. LMM in Europe

30. Baltic Sea Science Conference, 20 March 2007 REMO and Luterbacher Winter Fall Spring Summer Seasonal temperature anomalies in areas with skill of reconstruction > 0.5 Differences of ranked seasonal means (i.e., 1= difference of coldest season in LMM and control season)

31. Baltic Sea Science Conference, 20 March 2007 Precip anomalies LMM – non-LMM Luterbacher [mm/season] REMO

32. Baltic Sea Science Conference, 20 March 2007 Overall conclusions Multi-century simulations with state- of-the art GCMs are useful for … examining diagnostic (statistical) methods, incl. proxy assessments. … deriving hypotheses about the free and forced variability in historical times.

33. Baltic Sea Science Conference, 20 March 2007

34. Storminess

35. Baltic Sea ice winter index after Koslowski (1998) grey: raw index, red: 5 year mean, blue:20 year mean