#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 Wien, 26/02/09

Hesse’s concept of modelsReality 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 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 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 Wien, 26/02/09

#6 Wien, 26/02/09

#7 Wien, 26/02/09

#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 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 Wien, 26/02/09

Purpose of models

# reduction of complex systems “understanding”

# surrogate reality realism

#11 Wien, 26/02/09

Models for reduction of complex systems

good for:

• constitution of “understanding”, i.e. theory

• construction of hypotheses

#12 Wien, 26/02/09

Models as surrogate reality• dynamical, process-based models,

characteristics:

complexity quasi-realistic mathematical/mechanisticengineering approach

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

atmosphere

#14 Wien, 26/02/09

Dynamical processes in the atmosphereDynamical processes in a global atmospheric general circulation model

#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 Wien, 26/02/09

Modell

Beobachtet

Klimazonen

Klassifikation nach Koeppen

Erich Roeckner, pers. Mitteilung

#17 Wien, 26/02/09

Observed Simulated Winter(DJF)

Erich Roeckner, pers. Mitteilung

Zyklogenese

Sturmbahn-dichten

#18 Wien, 26/02/09

Precipitation in IPCC AR4 models

Erich Roeckner, pers. Mitteilung

#19 Wien, 26/02/09

Applying the model outside the admissible domain means to exploit a neutral analog.

#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 Wien, 26/02/09

Roeck

ner

& L

ohm

ann,

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 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 (<20 yrs) variations about ok, but long-term variations (>100 years) severely underestimated.

• MBH method methodically flawed.

#23 Wien, 26/02/09

Erklärung für die jüngste Klimageschichte

Modellrechungen ohne anthropogene EinflüsseBeobachtungen; relativ zu 1961-1990 Mittel

°C

#24 Wien, 26/02/09

Modellrechnungen mit anthropogenen EinflüssenBeobachtungen

°C

Erklärung für die jüngste Klimageschichte

#25 Wien, 26/02/09PAGE 25

“SRES” ScenariosSRES = IPCC Special Report on Emissions

Scenarios

Globale Szenarien => Abschätzung der Wirkung von Emissionsminderungen

#26 Wien, 26/02/09

Zwei Szenarien (A1B und B1) der Änderung der jährlichen Niederschlagssummen in 2061-2090 relativ zu 1961-1990.

CLM modellBeate Geyer, GKSS

Regionale Spezifikation => Anpassung

#27 Wien, 26/02/09

Gill et al.,2007

Lokale Modellierung: Potentiale für Mikroskaliges Klimamanagement

#28 Wien, 26/02/09

ZusammenfassungQuasirealistische 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 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 3-540-65830-0, 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 3-540-67862, 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 1437-028X