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Februar 2003 Workshop Kopenhagen1 Assessing the uncertainties in regional climate predictions of the 20 th and 21 th century Andreas Hense Meteorologisches Institut Universität Bonn

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Februar 2003 Workshop Kopenhagen2 Overview The problem –Climate system and climate models as random systems The consequences of randomness –Estimation of randomness at various levels –Predictability of forced climate variations –Comparison of simulations with observations The conclusions

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Februar 2003 Workshop Kopenhagen3 The problem: the climate system as a random system

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Februar 2003 Workshop Kopenhagen4 The problem: the climate system as a random system Due to the high dimensionality ~ 10 32 degrees of freedom: statistical physics Due to the nonlinearities in the atmosphere, ocean and the interactions: dynamical systems theory

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Februar 2003 Workshop Kopenhagen5 The problem continued: climate models as random systems Due to high dimensionality ~ 10 8 degrees of freedom Due to nonlinearities in the model atmospheres, oceans and interactions Due to parametrized subgrid scale processes („clouds, rain, convection etc..“) Due to model errors

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Februar 2003 Workshop Kopenhagen6 The consequences: Estimation of randomness From the real climate system –one observation / realisation available randomness has to be modelled –e.g. assuming ergodicity, probabilities by „counting“, frequentist‘s approach –bayesian approach, modelling by probability densities... more at the end

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Februar 2003 Workshop Kopenhagen7 The consequences: Estimation of randomness In models by Monte Carlo simulations, sampling the uncertainties in initial conditions, parameters, models Initial conditions

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Februar 2003 Workshop Kopenhagen8 The consequences: estimation of randomness Sampling models

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Februar 2003 Workshop Kopenhagen9 The consequences: predictability of forced climate variations Forced variations: Greenhouse gases, solar forcing, volcanoes overlaid by random variations –in models –in reality Forced variations > random variations ? –Predictability of the 2nd kind –In models Analysis-of-Variance –on specified space and time scales

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Februar 2003 Workshop Kopenhagen10 ECHAM3/LSG & HadCM2

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Februar 2003 Workshop Kopenhagen11 ECHAM3/LSG & HadCM2

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Februar 2003 Workshop Kopenhagen13 The Bayes Theorem

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Februar 2003 Workshop Kopenhagen14 The consequences: comparison of simulations with observations, Bayesian Classification (Attribution)

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Februar 2003 Workshop Kopenhagen15 A Bayesian attribution experiment ECHAM3/LSG 1880-1979 Control ECHAM3/LSG in 2000 Scenario NCEP Reanalysis Data 1958-1999 Observations Northern hemisphere area averages –near surface (2m) Temperature –70 hPa Temperature joint work with Seung-Ki Min, Heiko Paeth and Won-Tae Kwon

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Februar 2003 Workshop Kopenhagen17 Conclusions Inherent uncertainty in the climate system –due to the chaotic nature –strong dependance on space and time scales and type of variable –annual temperature on a regional scale ~ 70% predictable –annual sum of precipitation on a regional scale ~ 20% –decadal sum of precipiation ~ 70%

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Februar 2003 Workshop Kopenhagen18 Conclusion Uncertainty introduced by model errors are large on the regional scale Uncertainty introduced by randomized parametrizations not yet explored Despite of all uncertainties climate change signals on the global / hemispheric scale can be detected Uncertainty has to be quantified as additional input for impact studies, „meta-information“ scales in space, time and variable have to be selected from the discipline

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