Abstract
Among the most interesting and fascinating phenomena (that are predictable) are the complex ocean/atmosphere/land dynamical system called weather and its long time average climate. This complex dynamical system can be described in a simplified manner by the following features: (a) it evolves in time according to a set of rules; (b) the present conditions determine its future; (c) the rules governing them are usually non-linear; and (d) there may be many interacting variables describing it as a whole. It is widely accepted that the climate and the chemical composition on the Earth have been and are maintained at the steady state by the presence of life itself. Therefore, the climate can be considered through modelling processes on the environmental interface that is defined as an interface between two either abiotic or biotic environments which are in relative motion, exchanging energy through biophysical and chemical processes and fluctuating temporally and spatially regardless of its space and time scale. This interface as a complex system is a suitable area for occurrence of the chaotic irregularities in temporal variation of some physical or biological quantities describing their interaction. In this paper we consider some issues which are important from the point of view of the current climate modelling attempts. We deal with the following points: (i) overview of the results achieved until the present time, (ii) discussion of the term predictability beyond the complexity and (iii) numerical investigation of the system of two coupled logistic representing energy exchange of two interacting environmental interfaces relevant for providing insight into the properties of the Earth’s climate.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arshinov V, Fuchs C (2003) Preface. In: Arshinov V and Fuchs C, (eds) Causality, Emergence, Self-Organisation, NIA-Priroda, Moscow, pp. 1–18.
Bhumralkar CM (1975) Numerical experiments on the computation of ground surface temperature in an atmospheric general circulation model. J Appl Meteor 14:1246–1258.
Collier JD (2003) Fundamental properties of self-organisation. In: Arshinov V and Fuchs C, (eds) Causality, Emergence, Self-Organisation, NIA-Priroda, Moscow, pp. 150–166.
Collins M (2002) Climate predictability on interannual to decadal time scales: The initial value problem. Climate Dyn 19:671–692.
Edmonds B (1996) Pragmatic Holism. CPM Report 96-08, MMU.
Edmonds B (1999) What is complexity? The philosophy of complexity per se with application to some examples in evolution. In: Heylighen F and Aerts D (eds) In the Evolution of Complexity, Kluwer, Dordrecht.
Flood RL, Carson ER (1993) Dealing with Complexity: An Introduction to the Theory and Application of Systems Science, Plenum Press, New York.
Gödel K (1931) Über Formal Unentscheidbare Sätze der Principia Mathematica und Verwandter Systeme. I Monatshefte für Math u Physik 38:173–198.
Hartmann DL, Buizza R, Palmer TN (1995) Singular vectors: The effect of spatial scale on linear growth of disturbances. J Atmos Sci 52:3885–3894.
Heylighen F (1996) What is complexity?. In: Heylighen F, Aerts D (eds) In the Evolution of Complexity, Kluwer, Dordrecht.
Heylighen F (1997) The growth of structural and functional complexity. In: Heylighen F, (eds) In the Evolution of Complexity, Kluwer, Dordrecht.
Holtslag AA, van Ulden AP (1975) A simple scheme for daytime estimates of the surface fluxes from routine weather data. J Appl Meteor 22:517–529.
Hunt J (1999) Environmental forecasting and turbulence modeling. Physica D 133:270–295.
Keller DF (1999) Climate, modeling and predictability. Physica D 133:296–308.
James IN (2002) Models of the predictability of a simple nonlinear dynamical system. Atmos Sci Lett 3:42–51.
Jin F-F, Neelin JD, Ghil M (1994) El Niño on the devil’s staircase: Annual subharmonic steps to chaos. Science 264:70–72.
Kauffman S (1993) The Origins of Order, Oxford University Press, Oxford.
Krishnamurthy V (1993) A predictability study of Lorenz’s 28-variable model as a dynamical system. J Atmos Sci 50:2215–2229.
Kirtman BP, Schopf P (1998) Decadal variability in ENSO predictability and prediction. J Climate 11:2804–2822.
Lorenz EN (1962) The statistical prediction of solutions of dynamic equations. In Proceedings of the Internat. Symp. Numerical Weather Prediction, Tokyo, Japan, November 1960, pp. 629–635.
Lorenz EN (1963a) The predictability of hydrodynamic flows. Trans New York Acad Sci Ser II 25:409–423.
Lorenz EN (1963b) Deterministic nonperiodic flow. J Atmos Sci 20:130–141.
Lorenz EN (1964) The problem of deducing the climate from the governing equations. Tellus 16:1–11.
Lorenz EN (1969) The predictability of a flow which contains many scales of motion. Tellus 21:289–307.
Lorenz EN (1982) Atmospheric predictability experiments with a large numerical model. Tellus 34:505–513.
Lorenz EN (1984) Some aspects of atmospheric predictability. In: Burridge DM, Killn E, eds. In Problems and Prospects in Long and Medium Range Weather Forecasting, Springer-Verlag, Berlin, pp. 1–20.
Lorenz EN, Kerry EA (1998) Optimal sites for supplementary weather observations: Simulation with a small model. J Atmos Sci 55:399–414.
Mihailovic DT, Balaž I (2007) An essay about modelling problems of complex systems in environmental fluid mechanics. Idojaras 111(2–3):209–220.
Mihailovic DT, Kapor DV, Lalic B, Arsenic I (2001) The chaotic time fluctuations of ground surface temperature resulting from energy balance equation for the soil-surface system. In: Abstracts of the 26th General Assembly of European Geophysical Society, Nice, France, 20-25 March 2001.
Monteith JL, Unsworth M (1990) Principles of Environmental Physics, Edward Arnold, London.
Orell D (2003) Model error and predictability over different time scales in the Lorenz’96 systems. J Atmos Sci 60:2219–2228.
Rosen R (1977) Complexity as a system property. Int J Gen Systems 3:227–232.
Rosen R (1985) Anticipatory Systems: Philosophical, Mathematical and Methodological Foundations, Pergamon Press, New York.
Rosen R (1991) Life Itself: A Comprehensive Inquiry into the Nature, Origin and Fabrication of Life, Columbia University Press, New York.
Simmons AJ, Hollingsworth A (2002) Some aspects of the improvement in skill of numerical weather prediction. Quart J Royal Metor Soc 128:647–678.
Shukla J (1981) Dynamical predictability of monthly means. J Atmos Sci 38:2547–2572.
Shukla J (1985) Predictability. Adv Geophys 28B:87–122.
Shukla J, Paolino DA, Straus DM, DeWitt D, Fennessy M, Kinter JL, Marx L, Mo R (2000) Dynamical seasonal predictions with the COLA atmospheric model. Quart J Royal Metor Soc 126B:2265–2291.
van der Vaart HR (1973) A comparative investigation of certain difference equations and related differaential equations: Implications for model building. Bull of Math Biol 35:195–211.
Zeng X, Pielke RA, Eykholt R (1990) Chaos in daisyworld. Tellus 42B:309–318.
Zwiers FW, Kharin VV (1998) Intercomparison of interannual variability and potential predictability: An AMIP diagnostic subproject. Climate Dyn 14:517–528.
Acknowledgement
The research work described in this paper has been funded by the Serbian Ministry of Science and Technology under the project “Modelling and Numerical Simulations of Complex Physical Systems”, No. ON141035 for 2006-2010.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media B.V.
About this paper
Cite this paper
Mihailovic, D.T. (2010). Climate Modelling Beyond the Complexity: Challenges in Model-Building. In: Alexandrov, V., Gajdusek, M., Knight, C., Yotova, A. (eds) Global Environmental Change: Challenges to Science and Society in Southeastern Europe. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8695-2_5
Download citation
DOI: https://doi.org/10.1007/978-90-481-8695-2_5
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-8694-5
Online ISBN: 978-90-481-8695-2
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)