Format

Send to

Choose Destination
Risk Anal. 2014 Feb;34(2):271-93. doi: 10.1111/risa.12117. Epub 2013 Sep 23.

Uncertainty in climate change modeling: can global sensitivity analysis be of help?

Author information

1
IEFE Università Bocconi, Milan, Italy.

Abstract

Integrated assessment models offer a crucial support to decisionmakers in climate policy making. For a full understanding and corroboration of model results, analysts ought to identify the exogenous variables that influence the model results the most (key drivers), appraise the relevance of interactions, and the direction of change associated with the simultaneous variation of uncertain variables. We show that such information can be directly extracted from the data set produced by Monte Carlo simulations. Our discussion is guided by the application to the well-known DICE model of William Nordhaus. The proposed methodology allows analysts to draw robust insights into the dependence of future atmospheric temperature, global emissions, and carbon costs and taxes on the model's exogenous variables.

KEYWORDS:

Climate change; global sensitivity analysis; integrated assessment modeling; risk analysis

PMID:
24111855
DOI:
10.1111/risa.12117
[Indexed for MEDLINE]
Free full text

Supplemental Content

Full text links

Icon for Wiley Icon for Archivio Istituzionale della Ricerca Unimi
Loading ...
Support Center