Sensitivity analysis of the IMAGE Greenhouse model

被引:33
|
作者
Campolongo, F [1 ]
Braddock, R [1 ]
机构
[1] Griffith Univ, Nathan, Qld 4111, Australia
关键词
climate change; Greenhouse Effect; sensitivity analysis; one-factor-at a-time; two-factor interaction effects;
D O I
10.1016/S1364-8152(98)00079-6
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Sensitivity analysis is an important component of model building as it provides information about the parameters which have major influences on the model and its outputs. IMAGE (Integrated Model to Assess the Greenhouse Effect) has gained acceptance as a mid-range model for working with and predicting climate change. It is an ideal model for the application of new methods of sensitivity analysis. The sensitivity of IMAGE has been carried out by employing a new screening method which estimates first-order and second-order effects. This includes a first estimate of the non-linear interactions between the parameters of IMAGE. The new method is a development of the screening method proposed by Morris. The efficient sampling strategy in the parameter space is based on graph theory and on the solution of the "handcuffed prisoner problem". The results of the analysis are presented and some of the important first- and second-order interactions are identified. The strengths of these interactions indicate where the modelling of processes incorporated in IMAGE has to be revised in order to properly represent reality. (C) 1999 Published by Elsevier Science Ltd. All rights reserved.
引用
下载
收藏
页码:275 / 282
页数:8
相关论文
共 50 条
  • [21] Sensitivity analysis of an optimal control problem in greenhouse climate management
    Van Henten, EJ
    BIOSYSTEMS ENGINEERING, 2003, 85 (03) : 355 - 364
  • [22] A Sensitivity Analysis of Timing and Costs of Greenhouse Gas Emission Reductions
    Reyer Gerlagh
    Bob van der Zwaan
    Climatic Change, 2004, 65 : 39 - 71
  • [23] A sensitivity analysis of timing and costs of greenhouse gas emission reductions
    Gerlagh, R
    Van der Zwaan, B
    CLIMATIC CHANGE, 2004, 65 (1-2) : 39 - 71
  • [24] Quantifying sensitivity and uncertainty analysis of a new mathematical model for the evaluation of greenhouse gas emissions from membrane bioreactors
    Mannina, Giorgio
    Cosenza, Alida
    JOURNAL OF MEMBRANE SCIENCE, 2015, 475 : 80 - 90
  • [25] Application of neural image analysis in evaluating the quality of greenhouse tomatoes
    Zaborowicz, Maciej
    Boniecki, Piotr
    Koszela, Krzysztof
    Przybylak, Andrzej
    Przybyl, Jacek
    SCIENTIA HORTICULTURAE, 2017, 218 : 222 - 229
  • [26] An image model for quantitative image analysis
    Choi, H
    Chung, C
    INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, PROCEEDINGS - VOL III, 1996, : 983 - 986
  • [27] IMAGE - AN INTEGRATED MODEL TO ASSESS THE GREENHOUSE-EFFECT - ROTMANS,J
    WHITE, RK
    RISK ANALYSIS, 1992, 12 (02) : 325 - 326
  • [28] Botrytis cinerea Spectral Characteristics and Light Source Sensitivity Analysis in the Greenhouse
    Choi, E. G.
    Kim, C. H.
    Beak, G. Y.
    Kim, M. H.
    Kim, H. T.
    Kim, D. E.
    Yoon, Y. C.
    INTERNATIONAL SYMPOSIUM ON NEW TECHNOLOGIES FOR ENVIRONMENT CONTROL, ENERGY-SAVING AND CROP PRODUCTION IN GREENHOUSE AND PLANT FACTORY - GREENSYS 2013, 2014, 1037 : 819 - 826
  • [29] Polarization sensitivity error analysis and measurement of a greenhouse gas monitoring instrument
    Luo, Hai-Yan
    Li, Zhi-Wei
    Qiu, Zhen-Wei
    Shi, Hai-Liang
    Chen, Di-Hu
    Xiong, Wei
    APPLIED OPTICS, 2018, 57 (34) : 10009 - 10016
  • [30] Sensitivity analysis of greenhouse gas emissions from a pork production chain
    Groen, E. A.
    van Zanten, H. H. E.
    Heijungs, R.
    Bokkers, E. A. M.
    de Boer, I. J. M.
    JOURNAL OF CLEANER PRODUCTION, 2016, 129 : 202 - 211