Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison

被引：76

作者：

Gillingham, Kenneth ^{[1
]}

Nordhaus, William ^{[2
]}

Anthoff, David ^{[3
]}

Blanford, Geoffrey ^{[4
]}

Bosetti, Valentina

Christensen, Peter ^{[5
]}

McJeon, Haewon ^{[6
]}

Reilly, John ^{[7
]}

机构：

[1] Yale Univ, 195 Prospect St, New Haven, CT 06511 USA

[2] Yale Univ, 28 Hillhouse Ave, New Haven, CT 06511 USA

[3] Univ Calif Berkeley, Berkeley, CA 94720 USA

[4] Elect Power Res Inst, Palo Alto, CA USA

[5] Univ Illinois, Champaign, IL USA

[6] Joint Global Change Res Inst, College Pk, MD USA

[7] MIT, Cambridge, MA 02139 USA

来源：

JOURNAL OF THE ASSOCIATION OF ENVIRONMENTAL AND RESOURCE ECONOMISTS | 2018年 / 5卷 / 04期

基金：

欧洲研究理事会; 美国国家科学基金会;

关键词：

Climate policy; Integrated assessment models; Uncertainty; SOCIAL COST; POLICY; CARBON; TEMPERATURE; SENSITIVITY; MITIGATION; EMISSIONS;

D O I：

10.1086/698910

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The economics of climate change involves a vast array of uncertainties, complicating our understanding of climate change. This study explores uncertainty in baseline trajectories using multiple integrated assessment models commonly used in climate policy development. The study examines model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the probability distributions of key output variables, including CO2 concentrations, temperature, damages, and social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting distributions provide a useful input into climate policy discussions.

引用

页码：791 / 826

页数：36

共 52 条

[1] Uncertainty in Climate Change Modeling: Can Global Sensitivity Analysis Be of Help? [J].