How well do integrated assessment models simulate climate change?

Vuuren, Detlef van; Lowe, Jason; Stehfest, Elke; Gohar, Laila; Hof, Andries F.; Hope, Chris; Warren, Rachel; Meinshausen, Malte; Plattner, Gian‐Kasper

doi:10.1007/s10584-009-9764-2

Cited by 133 publications

(107 citation statements)

References 48 publications

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“…For comparison the dashed line denotes the path for the median case of f = 0.6 which represents an equilibrium climate sensitivity of around 3 C. We begin by considering the difference between the temperature response functions along this path representing a single model run (dashed line). This portion of the experiment, that is with an implied equilibrium climate sensitivity around 3 C, is very similar to the one carried out by van Vuuren et al (2011) and despite differences in the model vintages we find very similar results. 7 Initially, that is over the first 10-20 6 If model specific uncertain parameters are allowed to vary the primary results due not differ, and any differences in the plots presented are negligible.…”

Section: Temperature Dynamics For a Sustained Forcingsupporting

confidence: 80%

“…The important work of van Vuuren et al (2011) and Warren et al (2010) are the exception and provide a careful examination of the climate modules within this class of IAMs through inter-model comparisons with more complex models, including three-dimensional Atmosphere-Ocean General Circulation Models (AOGCMs). These studies provided a comprehensive look into the climate models contained within IAMs, examining in detail the links between emissions and atmospheric concentrations, concentrations and radiative forcing, and radiative forcing and temperature among other aspects of the models.…”

Section: Introductionmentioning

confidence: 99%

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Transient Temperature Response Modeling in IAMs: The Effects of Over Simplification on the SCC

Marten

2011

Economics

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Integrated Assessment Models (IAMs) couple representations of the natural climate system with models of the global economy to evaluate climate and energy policies. Such models are currently used to derive the benefits of carbon mitigation policies through estimates of the social cost of carbon (SCC). To remain tractable these models often utilize highly simplified representations of complex natural, social, and economic systems. The authors consider three prominent IAMs, DICE, FUND, and PAGE, and compare their highly simplified temperature response models to two upwelling diffusion energy balance models that better reflect the progressive heat uptake of the deep ocean. They find that all three IAMs fail to fully capture important characteristics in the dynamics of temperature response, especially for high equilibrium climate sensitivities. This has serious implications given these models are often run with distributions for the equilibrium climate sensitivity which have a positive probability for such states of the world. The authors find that, all else equal, the temperature response model in FUND can lead to estimates of the expected SCC that are 10-75% lower than those derived using more realistic climate models, while the models in DICE and PAGE lead to expected SCC estimates that are 10-110% and 40-260% higher, respectively. Special IssueThe Social Cost of Carbon JEL Q54, Q58

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Section: Temperature Dynamics For a Sustained Forcingsupporting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Transient Temperature Response Modeling in IAMs: The Effects of Over Simplification on the SCC

Marten

2011

Economics

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“…van Vuuren et al (2011), Marten (2011 and others have evaluated the predictive performance of the simple climate modules in IAMs. In order to study the economic consequences of uncertainty about extreme warming in IAMs, it is helpful to first get a conceptual handle on the underlying physical uncertainties that drive the economic analysis.…”

Section: The Science Of Extreme Warmingmentioning

confidence: 99%

Tall tales and fat tails: the science and economics of extreme warming

2013

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It has recently been highlighted that the economic value of climate change mitigation depends sensitively on the slim possibility of extreme warming. This insight has been obtained through a focus on the fat upper tail of the climate sensitivity probability distribution. However, while climate sensitivity is undoubtedly important, what ultimately matters is transient temperature change. A focus on transient temperature change stresses the interplay of climate sensitivity with other physical uncertainties, notably effective heat capacity. In this paper we present a conceptual analysis of the physical uncertainties in economic models of climate mitigation, leading to an empirical application of the DICE model, which investigates the interaction of uncertainty in climate sensitivity and the effective heat capacity. We expand on previous results exploring the sensitivity of economic evaluations to the tail of the climate sensitivity distribution alone, and demonstrate that uncertainty about the system's effective heat capacity also plays a very important role. We go on to discuss complementary avenues of economic and scientific research that may help provide a better combined understanding of the physical and economic processes associated with a rapidly warming world.

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“…Van Vuuren et al (2011b) presented a detailed comparison of the representation of the carbon cycle and climate system in different IAMs. It was concluded that the representations of the carbon cycle in IAMs mostly lie within the range of earth system models (referred to as Bexpert models^).…”

Section: Introductionmentioning

confidence: 99%

How well do integrated assessment models represent non-CO2 radiative forcing?

et al. 2015

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This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-CO 2 gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/m 2 in 2100) in non-CO 2 forcing projections for a 2.6 W/ Climatic Change (2015) How well do integrated assessment models represent non-CO 2 radiative forcing? m 2 mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required CO 2 forcing targets and policy costs.

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How well do integrated assessment models simulate climate change?

Cited by 133 publications

References 48 publications

Transient Temperature Response Modeling in IAMs: The Effects of Over Simplification on the SCC

Transient Temperature Response Modeling in IAMs: The Effects of Over Simplification on the SCC

Tall tales and fat tails: the science and economics of extreme warming

How well do integrated assessment models represent non-CO2 radiative forcing?

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