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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 ResearchGKSS Research CenterGeesthacht, Germany
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Baltic Sea Science Conference, 20 March 2007
Overview
1. Experimental set-up2. 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
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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
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Baltic Sea Science Conference, 20 March 2007
1675-1710vs. 1550-1800
Reconstruction from historical evidence, from Luterbacher et al.
Late Maunder Minimum
Model-based reconstuction
Skill of simulation
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Baltic Sea Science Conference, 20 March 2007
Skill of simulation
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Baltic Sea Science Conference, 20 March 2007
Skill of simulation
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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.
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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
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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.
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Baltic Sea Science Conference, 20 March 2007
Testing the MBH method
pseudo-proxies: grid point SAT plus white noisered: 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
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Baltic Sea Science Conference, 20 March 2007
Testing validity of proxy-derived indicators
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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.
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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
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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.
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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.
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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 Hollandde Kraker, 1999
Very little evidence available
Number of yearly events with air pressure < 980 hPaLund and StockholmBärring and von Storch, 2004
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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
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Baltic Sea Science Conference, 20 March 2007
Storminess
Pre-industrial: 1550-1850 change from pre-industrial to industrial period 1850-2000
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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
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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.
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Baltic Sea Science Conference, 20 March 2007
The Baltic Sea
Results for the Baltic Sea Region
- Overall development
- Maunder Minimum (downscaling)
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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
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Late Maunder Minimum
Cold winters and springs, 1675-1710
Late Maunder Minimum
Cold winters and springs, 1675-1710
Analysis of Columbus run, only.
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Baltic Sea Science Conference, 20 March 2007
Temperature conditions in Switzerland according to Pfister‘s classification (1999).
Late Maunder Minimum
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Simulated global 1675-1710 temperature anomaly
deMenocal et al.
(2000)
Ice conditions off Iceland (Koch, 1945)
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Baltic Sea Science Conference, 20 March 2007
The Baltic Sea
REMO model area; 0.5°x0.5° grid
ECHO-G grid
Dynamical Downscaling
„normal“: 1625-1656LMM : 1675-1705
Müller, B., 2004: Eine regionale Klimasimulation für Europa zur Zeit des späten Maunder Minimums 1675-1710, GKSS Report 2004/2
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Baltic Sea Science Conference, 20 March 2007
0
10
20
30
40
50
60
70
80
90
100
650 750 850 950 1050 1150 1250 1350 1450 1550 1650 1750 1850 1950
forest farmland greenland infrastructure water
Lower boundary conditions
are
a [
%]
Land-use
Sea ice coverageafter Koslowski (1999)
3.3.1692
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Baltic Sea Science Conference, 20 March 2007
REMO
Temperature differences LMM – non-LMM
Luterbacher
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Baltic Sea Science Conference, 20 March 2007
Mean difference of European air temperature during LMM and (pre-industrial) non-LMM.
LMM in Europe
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Baltic Sea Science Conference, 20 March 2007
Winter
-4
-3
-2
-1
0
1
2
5 10 15 20 25 30
Ano
mal
ie [K
]
REMO Luterbacher
Frühling
-4
-3
-2
-1
0
1
2
5 10 15 20 25 30
Anom
alie
[K]
Sommer
-4
-3
-2
-1
0
1
2
5 10 15 20 25 30
Anom
alie
[K]
Herbst
-4
-3
-2
-1
0
1
2
5 10 15 20 25 30
Anom
alie
[K]
REMO and Luterbacher
WinterWinter
FallFall
SpringSpring
SummerSummer
Seasonal Seasonal temperature temperature anomalies in anomalies in areas with areas with skill of skill of reconstruction reconstruction > 0.5> 0.5
Differences of Differences of ranked ranked seasonal seasonal means (i.e., means (i.e., 1= difference 1= difference of coldest of coldest season in LMM season in LMM and control and control season)season)
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Baltic Sea Science Conference, 20 March 2007
Precip anomalies LMM – non-LMM
Luterbacher[mm/season]
REMO
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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.
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Baltic Sea Science Conference, 20 March 2007
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Baltic Sea Science Conference, 20 March 2007
Storminess
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Baltic Sea ice winter index after Koslowski (1998)
grey: raw index, red: 5 year mean, blue:20 year mean