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#1 Wien, 26/02/09 Klimamodelle - was können sie und was können sie nicht? Institute of Coastal Research, GKSS Research Centre Geesthacht, und Klimacampus,

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Präsentation zum Thema: "#1 Wien, 26/02/09 Klimamodelle - was können sie und was können sie nicht? Institute of Coastal Research, GKSS Research Centre Geesthacht, und Klimacampus,"—  Präsentation transkript:

1 #1 Wien, 26/02/09 Klimamodelle - was können sie und was können sie nicht? Institute of Coastal Research, GKSS Research Centre Geesthacht, und Klimacampus, Universität Hamburg, Hans von Storch Österreichische Akademie der Wissenschaften, Kommission für Reinhaltung der Luft. Klima: Modelle, Prognosen, Strategien - Was nützen sie ? Donnerstag, 26. Februar 2009, 16:00 bis 19:00Theatersaal, Sonnenfelsfasse 19, 1010 Wien

2 #2 Wien, 26/02/09 Hesses concept of models Reality and a model have attributes, some of which are consistent and others are contradicting. Other attributes are unknown whether reality and model share them. The consistent attributes are positive analogs. The contradicting attributes are negative analogs. The unknown attributes are neutral analogs. Hesse, M.B., 1970: Models and analogies in science. University of Notre Dame Press, Notre Dame 184 pp. Conceptual aspects of modelling

3 #3 Wien, 26/02/09 Validating the model means to determine the positive and negative analogs. Applying the model means to assume that specific neutral analogs are actually positive ones. The constructive part of a model is in its neutral analogs.

4 #4 Wien, 26/02/09 Models are smaller than reality (finite number of processes, reduced size of phase space) simpler than reality (description of processes is idealized) closed, whereas reality is open (infinite number of external, unpredictable forcing factors is reduced to a few specified factors)

5 #5 Wien, 26/02/09

6 #6 Wien, 26/02/09

7 #7 Wien, 26/02/09

8 #8 Wien, 26/02/09 Only part of contributing spatial and temporal scales are selected. Parameter range limited Models represent only part of reality; Subjective choice of the researcher; Certain processes are disregarded.

9 #9 Wien, 26/02/09 Models can not be verified because reality is open. Coincidence of modelled and observed state may happen because of model´s skill or because of fortuitous (unknown) external influences, not accounted for by the model. Trivially: all models are false (= have negative analogs)

10 #10 Wien, 26/02/09 Purpose of models # reduction of complex systems understanding # surrogate reality realism

11 #11 Wien, 26/02/09 Models for reduction of complex systems good for: constitution of understanding, i.e. theory construction of hypotheses

12 #12 Wien, 26/02/09 Models as surrogate reality dynamical, process-based models, characteristics: complexity quasi-realistic mathematical/mechanistic engineering approach

13 #13 Wien, 26/02/09 Bremen, 17.Oktober 2007 atmosphere

14 #14 Wien, 26/02/09 Dynamical processes in the atmosphere Dynamical processes in a global atmospheric general circulation model

15 #15 Wien, 26/02/09 The model can be validated only for that part of the phase space, which is sufficiently covered by observations.

16 #16 Wien, 26/02/09 Modell Beobachtet Klimazonen Klassifikation nach Koeppen Erich Roeckner, pers. Mitteilung

17 #17 Wien, 26/02/09 Observed Simulated Winter (DJF) Erich Roeckner, pers. Mitteilung Zyklogenese Sturmbahn- dichten

18 #18 Wien, 26/02/09 Precipitation in IPCC AR4 models Erich Roeckner, pers. Mitteilung

19 #19 Wien, 26/02/09 Applying the model outside the admissible domain means to exploit a neutral analog.

20 #20 Wien, 26/02/09 process sensitivity analysis – neutral analog: embedding of process in dynamics experimentation tool (test of hypotheses) – neutral analog: all processes significant to the hypothesis are operating in the model. forecast of detailed development (e.g. weather forecast) – neutral analog: future development dynamically consistent interpretation and extrapolation of observations in space and time (data assimilation) - neutral analog: space-time correlations reconstruction of global past states and construction of scenarios - neutral analog: sensitivity to external forcings Purposes

21 #21 Wien, 26/02/09 Roeckner & Lohmann, 1993 No cirrus Effect of black cirrus detailed parameterization Latitude-height distribution of temperature (deg C) Difference black cirrus - detailed parameterization Difference no cirrus - detailed parameterization

22 #22 Wien, 26/02/09 Testing the MBH hockeystick method Simulating the process of reconstructing historical climate variations using the data from the 1000 year historical ECHO-G simulation. Done by constructing pseudo-proxies. Short-term ( 100 years) severely underestimated. MBH method methodically flawed.

23 #23 Wien, 26/02/09 Erklärung für die jüngste Klimageschichte Modellrechungen ohne anthropogene Einflüsse Beobachtungen; relativ zu Mittel °C°C

24 #24 Wien, 26/02/09 Modellrechnungen mit anthropogenen Einflüssen Beobachtungen °C°C Erklärung für die jüngste Klimageschichte

25 #25 Wien, 26/02/09 PAGE 25 SRES Scenarios SRES = IPCC Special Report on Emissions Scenarios Globale Szenarien => Abschätzung der Wirkung von Emissionsminderungen

26 #26 Wien, 26/02/09 Zwei Szenarien (A1B und B1) der Änderung der jährlichen Niederschlagssummen in relativ zu CLM modell Beate Geyer, GKSS Regionale Spezifikation => Anpassung

27 #27 Wien, 26/02/09 Gill et al.,2007 Lokale Modellierung: Potentiale für Mikroskaliges Klimamanagement

28 #28 Wien, 26/02/09 Zusammenfassung Quasirealistische Modelle sind validiert für das gegenwärtige Klima, d.h. sie beschreiben die wesentlichen, großskaligen Statistiken des derzeitigen Klimageschehens. Für Klimawandeluntersuchungen dienen quasirealistische Modelle - der Detektion und Attribution von gegenwärtigem Klimawandel, - der Abschätzung der Sensitivität des globalen Klimasystems gegenüber der Intensität von Emissionen, - der Spezifikation von möglichen zukünftigen Anpassungsbedarfen - der Erforschung des Potentials lokalen Klimamanagements

29 #29 Wien, 26/02/09 Zu diesem Thema kann man lesen: von Storch, H., S. Güss und M. Heimann, 1999: Das Klimasystem und seine Modellierung. Eine Einführung. Springer Verlag ISBN , 255 pp von Storch, H., and G. Flöser (Eds.), 2001: Models in Environmental Research. Proceedings of the Second GKSS School on Environmental Research, Springer Verlag ISBN , 254 pp. Müller, P., and H. von Storch, 2004: Computer Modelling in Atmospheric and Oceanic Sciences - Building Knowledge. Springer Verlag Berlin - Heidelberg - New York, 304pp, ISN X


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