1. The Art and Role of Climate Modeling
Institute of Coastal Research, GKSS Research Centre Geesthacht, Hans von Storch
Turku, 5-9 June 2001, CLIC Symposium
45 minutes incl.discussion
"Climate Modelling„
Abstract
Climate models are an indispensable tool for modern climate research; based on detailed descriptions of all first order climate processes, these models simulate climate variables in a quasi-realistic manner on time scales of a few hours to centuries of years and spatial scales of a few hundred kilometres. These models generate a virtual reality or laboratory which allow the reconstructing of past (historical and paleoclimatic) states and of plausible scenarios of future changes.
In this talk, the art of quasi realistic climate modelling is reviewed. Its limitation - such as the failure to immediately constitute knowledge (insight into climate dynamics) or to provide regional detail, or the impossibility for positive verification - is discussed. The different modes of applications are sketched: simulation runs in the paradigm of initial/boundary value problems, and data analysis in the spirit of a state space formulation.
The talk is concluded with a short discourse about the contemporary public role of climate models.
based on:
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
The Art and Role of Climate Modeling

2. Overview: Conceptual aspects of modelling
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Overview:
Conceptual aspects of modelling
Quasi-realistic climate models („surrogate reality“)
Free and forced simulations for reconstruction of historical climate
Laboratory to test conceptual models
Climate change simulations

3. Institut für Küstenforschung Hesse’s concept of models
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Hesse’s 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.
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.
Hesse, M.B., 1970: Models and analogies in science. University of Notre Dame Press, Notre Dame 184 pp.

4. Positive analog
Neutral analog
Application

5. Quasi-realistic Modelling
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Quasi-realistic Modelling

6. Models are Institut für Küstenforschung
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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)

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10. Models represent only part of reality;
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Models represent only part of reality;
Subjective choice of the researcher; Certain processes are disregarded.
Only part of contributing spatial and temporal scales are selected.
Parameter range limited

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Models can be shown to be consistent with observations, e.g. the known part of the phase space may reliably be reproduced.

12. Models can not be verified because reality is open.
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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 unknown external influences not accounted for by the model.

13. Models as surrogate reality
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Models as surrogate reality
dynamical, process-based models
• experimentation tool (test of hypotheses)
• design of scenario
• sensitivity analysis
• dynamically consistent interpretation and extrapolation of observations in space and time (“data analysis”)
• forecast of detailed development (e.g. weather forecast)

14. quasi-realistic climate models
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quasi-realistic climate models

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Dynamical processes in the atmosphere

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Dynamical processes in a global atmospheric general circulation model

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Dynamical processes in the ocean

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Dynamical processes in a global ocean model

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1880–2049
ECHAM3/LSG
1973–1993
ERA ECMWF

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How well are these processes represented in climate models?
atmosphere
ocean
Bray and von Storch, 1999
Results of a survey among climate modellers

23. Laboratory to test conceptual models
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Laboratory to test conceptual models

24. Example: Stommel model of the North Atlantic overturning
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Example: Stommel model of the North Atlantic overturning
Ft, Ht freshwater and heat flux Fp, Hp
Subtropical Atlantic Tt,St
Subpolar Atlantic Tp, Sp
Trans-port

25. Institut für Küstenforschung Rahmstorf‘s model Stommel‘s theory
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Rahmstorf‘s model
Stommel‘s theory
Rahmstorf, 1995

26. Testing the of multimodality of large scale atmospheric dynamics
Berner and Branstator, pers. comm

27. Free and forced simulations for reconstruction of historical climate
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Free and forced simulations for reconstruction of historical climate

28. Free Simulation: 1000 years
no solar variability, no changes in greenhouse gas concentrations, no orbital forcing
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Temperature (at 2m) deviations from 1000 year average [K]
Zorita, 2001

29. Forced Simulation 1550-2000 simulation Changing solar forcing and
time variable volcanic aerosol load;
greenhouse gases

30. Climate model used Institut für Küstenforschung Atmosphere: ECHAM4
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Climate model used
Atmosphere: ECHAM4
horizontal resolution T30 ~ 300 km at mid latitudes
Ocean: HOPE-G
horizontal resolution T42 ~ 200 km at mid latitudes
increased resolution in the tropics
Model provided as community climate by
Model & Data Group at MPI for Meteorology and run at German Climate Computing Centre (DKRZ) and computing facilities at FZ Jülich

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Temperature conditions in Switzerland according to Pfister‘s classification.
From Luterbacher, 2001

33. Late Maunder Minimum 1675-1710 vs. 1550-1800 validation
Reconstruction from historical evidence, from Luterbacher et al.
Late Maunder Minimum
Model-based reconstuction vs

34. Global 1675-1710 temperature anomaly
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Model as a constructive tool
Global temperature anomaly

35. Institut für Küstenforschung Model as a constructive tool
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Model as a constructive tool
Simulated differences of ice coverage, in percent, during the LMM event and the long term mean

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control
forced

37. Climate change simulations
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Climate change simulations

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Scenario A2
Annual temperature changes [°C]
(2071–2100) –(1961–1990)
Scenario B2
Danmarks Meteorologiske Institut

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Consistency of regional change in precipitation in different climate model scenarios.
(consistency: 7 out of 9 scenarios agree)

41. Quasi-realistic climate models
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Quasi-realistic climate models
are useful tools to describe our knowledge about the climate processes and their interactions in a comprehensive manner.
are a reduction of the real complexity of the climate system. They may be used to construct knowledge, but do not by themselves represent more knowledge than was inserted into.
are the only tool to conduct experiments with the environmental system.
are a valuable tool to reconstruct past climate variations and to envisage possible future climate developments.
cannot be “verified”, i.e., shown to respond “correctly” to anomalous forcing if this has not been observed before.

42. Quasi-realistic climate models
are useful tools to describe our knowledge about the climate processes and their interactions in a comprehensive manner.
are a reduction of the real complexity of the climate system. They may be used to construct knowledge, but do not by themselves represent more knowledge than was inserted into.
are the only tool to conduct experiments with the environmental system.
are a valuable tool to reconstruct past climate variations and to envisage possible future climate developments.
cannot be “verified”, i.e., shown to respond “correctly” to anomalous forcing if this has not been observed before.