AD-DICE: an implementation of adaptation in the DICE model

Integrated Assessment Models (IAMS) have helped us over the past decade to understand the interactions between the environment and the economy in the context of climate change. Although it has also long been recognized that adaptation is a powerful and necessary tool to combat the adverse effects of climate change, most IAMS have not explicitly included the option of adaptation in combating climate change. This paper adds to the IAM and climate change literature by explicitly including adaptation in an IAM, thereby making the trade-offs between adaptation and mitigation visible. Specifically, a theoretical framework is created and used to implement adaptation as a decision variable into the DICE model. We use our new AD-DICE model to derive the adaptation cost functions implicit in the DICE model. In our set-up, adaptation and mitigation decisions are separable and AD-DICE can mimic DICE when adaptation is optimal. We find that our specification of the adaptation costs is robust with respect to the mitigation policy scenarios and parameter values. Our numerical results show that adaptation is a powerful option to combat climate change, as it reduces most of the potential costs of climate change in earlier periods, while mitigation does so in later period

Global economic impacts of climate variability and change during the 20th century

Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970's, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed

Climate Policy Under Fat-Tailed Risk: An Application of Dice

Uncertainty plays a significant role in evaluating climate policy, and fat-tailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question, we propose a new way of investigating the impact of (fat-tailed) uncertainty on optimal climate policy: the curvature of the optimal carbon tax against the uncertainty. We find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases, but it does not accelerate as implied by Weitzman's Dismal Theorem. We find the same result in a wide variety of sensitivity analyses. These results emphasize the importance of balancing the costs of climate change against its benefits, also under deep uncertainty. © 2013 Springer Science+Business Media Dordrecht

Adaptation in integrated assessment modeling: where do we stand?

Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We analyze how modelers have chosen to describe adaptation within an integrated framework, and suggest many ways they could improve the treatment of adaptation by considering more of its bottom-up characteristics. Until this happens, we suggest, models may be too optimistic about the net benefits adaptation can provide, and therefore may underestimate the amount of mitigation they judge to be socially optimal. Under some conditions, better modeling of adaptation costs and benefits could have important implications for defining mitigation targets. © Springer Science+Business Media B.V. 2009

Population-based emergence of unfamiliar climates

Time of emergence, which characterizes when significant signals of climate change will emerge from existing variability, is a useful and increasingly common metric. However, a more useful metric for understanding future climate change in the context of past experience may be the ratio of climate signal to noise (S/N)—a measure of the amplitude of change expressed in terms of units of existing variability. Here, we present S/N projections in the context of emergent climates (termed ‘unusual’, ‘unfamiliar’ and ‘unknown’ by reference to an individual’s lifetime), highlighting sensitivity to future emissions scenarios and geographical and human groupings. We show how for large sections of the world’s population, and for several geopolitical international groupings, mitigation can delay the onset of ‘unknown’ or ‘unfamiliar’ climates by decades, and perhaps even beyond 2100. Our results demonstrate that the benefits of mitigation accumulate over several decades, a key metric of which is reducing S/N, or keeping climate as familiar as possible. A relationship is also identified between cumulative emissions and patterns of emergent climate signals. Timely mitigation will therefore provide the greatest benefits to those facing the earliest impacts, many of whom are alive now

Beyond Copenhagen: A Realistic Climate Policy in a Fragmented World

In this paper we argue that the financial provisions of the Copenhagen Accord, if used primarily to mitigate greenhouse gas (GHGs) emissions, could compensate the lack of more energetic action on the domestic mitigation side. In order to maximize the mitigation potential, the Copenhagen Green Climate Fund (CGCF) should be transformed into the International Bank for Emissions Allowance Acquisition (IBEAA) envisaged by Bradford ( 2008 ). We estimate that 50 percent of the CGCF in 2020 (50 US billions) could finance from 2.1 to 3.3 Gt CO2-eq emission reductions, depending on the domestic mitigation effort of Annex I and Non-Annex I countries. We construct a matrix that shows the level of GHGs emissions in 2020 under all possible combinations of abatement pledges and international mitigation financing, thus highlighting a rich set of options to reach the same level of GHGs emissions in 2020