Keywords

uncertainty, pedigree, nusap, quality, integrated assessment modelling

Start Date

1-7-2002 12:00 AM

Description

A novel approach to uncertainty assessment, known as the NUSAP method (Numeral Unit Spread Assessment Pedigree) was applied to assess qualitative and quantitative uncertainties in the TIMER energy model, part of RIVMs IMAGE Model. The TIMER model is a system dynamics energy model that has been used, for instance, in the development of the new IPCC baseline scenarios (SRES). For our analysis we have used the IMAGE B1 scenario as case study. We used two complementary tools to assess uncertainty: (1) The Morris algorithm for global sensitivity analysis and (2) a NUSAP expert elicitation workshop, which assessed different aspects of the strength of the knowledgebase of the parameters. Results of (1) and (2) were combined into a diagnostic diagram putting spread and strength together to provide guidance in prioritisation of key uncertainties. The project has shown that the NUSAP method can be applied to complex models in a meaningful way. The method provides a means to focus research efforts on the potentially most problematic parameters, identifying at the same time specific weaknesses in these parameters.

Share

COinS
 
Jul 1st, 12:00 AM

Uncertainty management in complex models: the NUSAP method

A novel approach to uncertainty assessment, known as the NUSAP method (Numeral Unit Spread Assessment Pedigree) was applied to assess qualitative and quantitative uncertainties in the TIMER energy model, part of RIVMs IMAGE Model. The TIMER model is a system dynamics energy model that has been used, for instance, in the development of the new IPCC baseline scenarios (SRES). For our analysis we have used the IMAGE B1 scenario as case study. We used two complementary tools to assess uncertainty: (1) The Morris algorithm for global sensitivity analysis and (2) a NUSAP expert elicitation workshop, which assessed different aspects of the strength of the knowledgebase of the parameters. Results of (1) and (2) were combined into a diagnostic diagram putting spread and strength together to provide guidance in prioritisation of key uncertainties. The project has shown that the NUSAP method can be applied to complex models in a meaningful way. The method provides a means to focus research efforts on the potentially most problematic parameters, identifying at the same time specific weaknesses in these parameters.