Multiple Rotations of Gaussian Quadratures: An Efficient Method for Uncertainty Analyses in Large-Scale Simulation Models

Stepanyan D, Grethe H, Zimmermann G, Siddig K, Deppermann A, Feuerbacher A, Luckmann J, Valin H, et al. (2020). Multiple Rotations of Gaussian Quadratures: An Efficient Method for Uncertainty Analyses in Large-Scale Simulation Models. Environmental Modelling & Software: e104929. DOI:10.1016/j.envsoft.2020.104929. (In Press)

[img]
Preview
Text
ENVSOFT_R3_LE_DS_clean.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview

Abstract

Concerns regarding the impact of climate change, food price volatility, and weather uncertainty have motivated users of simulation models to consider uncertainty in their simulations. One way to do this is to integrate uncertainty components in the model equations, thus turning the model into a problem of numerical integration. Most of these problems do not have analytical solutions, and researchers, therefore, apply numerical approximation methods. This article presents a novel approach to conducting an uncertainty analysis as an alternative to the computationally burdensome Monte Carlo-based (MC) methods. The developed method is based on the degree three Gaussian quadrature (GQ) formulae and is tested using three large-scale simulation models. While a standard single GQ method often produces low-quality approximations, the results of this study demonstrate that the proposed approach reduces the approximation errors by a factor of nine using only 3.4% of the computational effort required by the MC-based methods in the most computationally demanding model.

Item Type: Article
Uncontrolled Keywords: Uncertainty analysis; systematic sensitivity analysis; stochastic modeling; multiple rotations of Gaussian quadratures; Monte Carlo sampling; computable general equilibrium model; spartial equilibrium models
Research Programs: Ecosystems Services and Management (ESM)
Depositing User: Luke Kirwan
Date Deposited: 16 Nov 2020 12:38
Last Modified: 20 Nov 2020 05:17
URI: http://pure.iiasa.ac.at/16845

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313