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Predictability and Nonlinear Modelling in Natural Sciences and Economics

  • Book
  • © 1994

Overview

Editors:
  1. J. Grasman

    1. Department of Mathematics, Agricultural University, Wageningen, The Netherlands

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  2. G. Straten

    1. Department of Agricultural Engineering and Physics, Agricultural University, Wageningen, The Netherlands

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    You can also search for this editor in PubMed   Google Scholar

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Table of contents (55 chapters)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Introduction

    1. Introduction

      • J. Grasman, G. Van Straten
      Pages 1-5

  3. Geophysics

    1. Karl Popper and the Accountability of Scientific Models

      • H. Tennekes
      Pages 6-10

    2. Evaluation of Forecasts

      • Allan H. Murphy, Martin Ehrendorfer
      Pages 11-28

    3. The Liouville Equation and Prediction of Forecast Skill

      • Martin Ehrendorfer
      Pages 29-44

    4. An Improved Formula to Describe Error Growth in Meteorological Models

      • Jean-François Royer, Rodica Stroe, Michel Déqué, Stéphane Vannitsem
      Pages 45-56

    5. Searching for Periodic Motions in Long-Time Series

      • Rubén A. Pasmanter
      Pages 57-64

    6. Comparison Study of the Response of the Climate System to Major Volcanic Eruptions and El Niño Events

      • W. Böhme
      Pages 65-85

    7. Detection of a Perturbed Equator-Pole Temperature Gradient in a Spectral Model of the Atmospheric Circulation

      • Sipko L. J. Mous
      Pages 86-94

    8. A Simple Two-Dimensional Climate Model with Ocean and Atmosphere Coupling

      • E. J. M. Veling, M. E. Wit
      Pages 95-112

    9. Climate Modelling at Different Scales of Space

      • G. Maracchi
      Pages 113-126

  4. Agriculture

    1. Simulation of Effects of Climatic Change on Cauliflower Production

      • Jørgen E. Olesen, Kai Grevsen
      Pages 127-137

    2. Validation of Large Scale Process-Oriented Models for Managing Natural Resource Populations: A Case Study

      • R. A. Fleming, C. A. Shoemaker
      Pages 138-148

    3. Uncertainty of Predictions in Supervised Pest Control in Winter Wheat: Its Price and Causes

      • Walter A. H. Rossing, Richard A. Daamen, Eligius M. T. Hendrix, Michiel J. W. Jansen
      Pages 149-156

    4. The Implications and Importance of Non-Linear Responses in Modelling the Growth and Development of Wheat

      • Mikhail A. Semenov, John R. Porter
      Pages 157-171

    5. Growth Curve Analysis of Sedentary Plant Parasitic Nematodes in Relation to Plant Resitance and Tolerance

      • R. J. F. Van Haren, E. M. L. Hendrikx, H. J. Atkinson
      Pages 172-183

  5. Population Biology

    1. Using Chaos to Understand Biological Dynamics

      • Bruce E. Kendall, William M. Schaffer, Lars F. Olsen, Charles W. Tidd, Bodil L. Jorgensen
      Pages 184-203

    2. Qualitative Analysis of Unpredictability: A Case Study from Childhood Epidemics

      • Ralf Engbert, Friedhelm R. Drepper
      Pages 204-215

    3. Control and Prediction in Seasonally Driven Population Models

      • Ira B. Schwartz, Ioana Triandaf
      Pages 216-227

    4. Simple Theoretical Models and Population Predictions

      • Alan A. Berryman, Mikael Munster-Swendsen
      Pages 228-231
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Keywords

About this book

Researchers in the natural sciences are faced with problems that require a novel approach to improve the quality of forecasts of processes that are sensitive to environmental conditions. Nonlinearity of a system may significantly complicate the predictability of future states: a small variation of parameters can dramatically change the dynamics, while sensitive dependence of the initial state may severely limit the predictability horizon. Uncertainties also play a role.
This volume addresses such problems by using tools from chaos theory and systems theory, adapted for the analysis of problems in the environmental sciences. Sensitive dependence on the initial state (chaos) and the parameters are analyzed using methods such as Lyapunov exponents and Monte Carlo simulation. Uncertainty in the structure and the values of parameters of a model is studied in relation to processes that depend on the environmental conditions. These methods also apply to biology and economics.
For research workers at universities and (semi)governmental institutes for the environment, agriculture, ecology, meteorology and water management, and theoretical economists.

Editors and Affiliations

  • Department of Mathematics, Agricultural University, Wageningen, The Netherlands

    J. Grasman

  • Department of Agricultural Engineering and Physics, Agricultural University, Wageningen, The Netherlands

    G. Straten

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