TY - JOUR
T1 - Diagnostic indicators for integrated assessment models of climate policies
AU - Kriegler, Elmar
AU - Petermann, Nils
AU - Krey, Volker
AU - Schwanitz, Valeria Jana
AU - Luderer, Gunnar
AU - Ashina, Shuichi
AU - Bosetti, Valentina
AU - Eom, Jiyong
AU - Kitous, Alban
AU - Méjean, Aurélie
AU - Paroussos, Leonidas
AU - Sano, Fuminori
AU - Turton, Hal
AU - Wilson, Charlie
AU - van Vuuren, Detlef P.
PY - 2015/1
Y1 - 2015/1
N2 - Integrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results.
AB - Integrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results.
U2 - 10.1016/j.techfore.2013.09.020
DO - 10.1016/j.techfore.2013.09.020
M3 - Article
VL - 90
SP - 45
EP - 61
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
SN - 0040-1625
IS - Part A
ER -