by E Kopits · 2013 · Cited by 7 — Intergovernmental Panel on Climate Change (2007b). A Report of Working Group I: Summary for. Policymakers. ipcc.ch/pdf/assessment-report/ar4/wg1
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Working Paper Series U.S. Environmental Protection Agency National Center for Environmental Economics 1200 Pennsylvania Avenue, NW (MC 1809) Washington, DC 20460 http://www.epa.gov/economics Moving Forward with Incorporating ﬁCatastrophic ﬂ Climate Change into Policy Analysis Elizabeth Kopits, Alex L. Marten, Ann Wolverton Working Paper # 13-01 January , 20 13
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NCEE Working Paper Series Working Paper # 13 -01 January, 2013 DISCLAIMER The views expressed in this paper are those of the author(s) and do not necessarily represent those of the U.S. Environmental Protection Agency. In addition, although the research described in this paper may have been funded entirely or in part by the U.S. Environmental Protection Agency, it has not been subjected to the Agen cy’s required peer and policy review. No official Agency endorsement should be inferred. Moving Forward with Incorporating ﬁCatastrophic ﬂ Climate Change into Policy Analysis Elizabeth Kopits, Alex L. Marten, Ann Wolverton
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1 Moving Forward with Incorporating ﬁCatastrophicﬂ Climate Change into Policy Analysis Elizabeth Kopits, Alex L. Marten, Ann Wolverton 1 Abstract It has often been stated that current studies aimed at understanding the magnitude of optimal climate policy fail to adequately capture the potential for ﬁcatastrophicﬂ impacts of climate change. While economic modeling exercises to date do provide evidence that potential climate catastrophes might significantly influence the optimal path of abatement, there is a need to move beyond experiments which are abstracted from important details of the climate problem in order to substantively inform the policy debate . This paper provides a foundation for improving the economic modeling of potential large scale impacts of climate change in order to understand their influence on estimates of socially efficient climate policy. We begin by considering how the term ﬁcatastrophic impactsﬂ has been used in the scientific literature to describe changes in the climate system and carefully review the characteristics of the events that have been discussed in this context. We contrast those findings with a review of the way in which the economic literature has modeled the potential economic and human welfare impacts of events of this nature . We find that the uniform way in which the economic literature has typically modeled such impacts along with the failure to understand differences in the end points and timescales examined by the natural science literature ha s resulted in the model ing of events that do not resemble those of concern. Based on this finding and our review of the scientific literature we provide a path forward for better incorporating these events into integrated assessment modeling, identifying areas where modeling cou ld be improved even within current modeling frameworks and others where additional work is needed. Keywords: Climate Change, Catastrophes, Integrated Assessment Model JEL Codes: Q54, Q58 1 National Center for Environmental Economics, U.S. Environmental Protection Agency, Washington, DC 20460. Corresponding Email: Kopits.email@example.com . The views expressed in this paper are those of the authors and do not necessarily reflect the view or p olicies of the U.S. Environmental Protection Agency. The authors appreciate the helpful comments of Tim Lenton of the University of Exeter and Steve Newbold of the U.S. EPA National Center for Environmental Economics.
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2 1. Introduction It is common within the academic and public discours e on climate change for the term catastrophe to be invoked when describing the possible outcomes of a changing climate and in justifying particular responses to the problem . In fact it has been suggested that the potential for ﬁcatastrophic impactsﬂ as a result of climate change is the most important aspect of the problem for determining the optimal level of response (Pindyck and Wang 2012, Weitzman 2009). Pindyck (2012) goes so far as to argue that ﬁthe economic case for a stringent GHG abatement policy, i f it is to be made at all, must be based on the possibility of a catastrophic outcome.ﬂ Thus, it is perhaps not surprising that analyses of greenhouse gas mitigation benefits are often criticized for failing to adequately capture possible catastrophic impa cts (e.g., Tol 2009, NAS 2010) . Even the U.S. government in its primary work to value the benefits of greenhouse gas abatement notes a lack of accounting for catastrophic impacts as a major caveat that requires their analysis only be considered ﬁprovisiona lﬂ (U .S. Interagency Working Group on Social Cost of Carbon , 2010) . However, despite the seeming importance of such potential climate change related events there has been little progress in defensibly integrating catastrophic impacts into analyses consider ing the benefits of climate policy . One obstacle that has impeded forward progress on this front is the inconsistent and sometimes nebulous way in which the expression ﬁcatastrophic impactsﬂ has been used (Hulme, 2003) . The term has been adopted as a catc h-all phrase that refers to any climate induced impact that exhibits one or more of a number of characteristics: relatively sudden occurrence, irreversible transition to a new state after crossing a threshold, relatively large physical or economic impact s, or relatively low probability but extensive impact s. For this reason the types of impacts covered under the catastrophic moniker are numerous and heterogeneous . For example, the term climate catastrophe has been used to describe everything from dieback of Amazon rainforests over the coming decades to the potential massive release of methane emissions from the sea floor over the next thousand years (Lenton et al. 2008) . Some even have argued for establishing an overall global threshold for climate change , b elow which we are deemed safe from violating “non -negotiable planetary preconditions – [and] avoid the risk of deleterious or even catastrophic environmental change at continental to global scalesﬂ (Rockstrom et al. 2009). The authors acknowledge that determining what is safe is a normative judgment, but link it to the notion that deleterious or catastrophic effects from climate change would occur when Earth systems are pushed out of the Holocene state (a period of relatively stability over the past 10, 000 years) (Rockstrom et al. 2009). The ambition of an overall global warming threshold was formally endorsed in the 2009
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3 Copenhagen Accord, in which mor e than two dozen key countries — representing more than 80 percent of the world’s global warming pollu tion Œ agreed to register non -binding national commitments to combat climate change : ﬁTo achieve the ultimate objective of the Convention to stabilize greenhouse gas concentration in the atmosphere at a level that would prevent dangerous anthropogenic int erference with the climate system, we shall, recognizing the scientific view that the increase in global temperature should be below 2 degrees Celsius, on the basis of equity and in the context of sustainable development, enhance our long -term cooperative action to combat climate change ﬂ (UNFCCC 2009). In public discourse catastrophic impacts are often invoked as a seemingly monolithic occurrence 2, a tendency that is also often present in the economic analyses of optimal climate policy conditional on the po tential for such events . By assuming uniformity across the multitude of characteristics over which these potential climate ﬁcatastrophesﬂ may vary, the economic research on the subject has severely limited its ability to substantively inform policy discuss ions. In addition, many economic modeling efforts fall substantially short when it comes to incorporating scientific evidence regarding the causes, likelihood, and potential physical impacts of such climate change induced events . The former may arise from an absence of literature that summarizes the significant differences between potential large scale events resulting from climate change and what that means for incorporating them into economic analysis, while the latter appears to be the result of fundamen tal differences between disciplines as to what constitutes relatively rapid or large changes and the appropriate end points to measure in policy analysis . Both of these concerns have been observed by natural scientists (e.g., Hulme 2003), and calls are inc reasing across the scientific community for more research on welfare impacts, with better links to the scient ific evidence on how physical processes are likely to unfold (e.g., Lenton 2011, Lenton and Ciscar 2012 ). In this paper we seek to provide a foundation to help improve the economic modeling of potential large scale impacts of climate change within Earth systems in order to understand their influence on estimates of socially efficient climate policy . We begin b y considering how the term ﬁcatastrophic impactsﬂ has been used in the scientific literature to describe changes in the climate system and 2 Examples of such statements includ e: ﬁ We have a window of only 10 -15 years to take the steps we need to avoid crossing catastrophic tipping pointsﬂ (Jan Peter Balkenende & Tony Blair, October 20, 2006 ), ﬁ Until now, leaders have focused on slowing warming to 2 degrees Celsius to prevent cat astrophic changes associated with climate change ﬂ (MIT News, June 14, 2012), ﬁ Even if the ultimate result were an Earth that is still hospitable to mankind, the transition could be catastrophic ﬂ (The Economist, June 18, 2012).
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4 carefully review the characteristics of the events that have been discussed in this context . We explore the potential economic and human welfare impacts of such events and contrast those findings with a review of the way in which the economic literature has modeled these events classified as possible climate catastrophes .3 We find that the relatively uniform way in which the economic literature has typically modeled such impacts along with the failure to understand differences in the end points and timescales examined by the natural science literature have resulted in the modeling of events that do not resemble those of c oncern in reality. Based on this finding and our review of the scientific literature we suggest a path forward for better incorporating these events into integrated assessment modeling, identifying areas where modeling could be improved even within current IAM frameworks and others where additional work is needed. 2. Catastrophic Impacts from th e Scientific Perspective An often cited technical definition for the term catastrophe is ﬁwhen the climate system is forced to cross some threshold, triggering a tra nsition to a new state at a rate determined by the climate system itself and faster than the causeﬂ (NRC 2002) . This characterization captures two of three salient aspects of the typical use of the term catastrophe in the scientific literature. First , the event occurs relatively quickly. Second , it causes a natural system to move to a new steady state . Catastrophes related to climate change have also been termed ﬁsurprisesﬂ in the scientific literature, which the IPCC (1996) defines as the rapid, non -linea r response of a natural system to anthropogenic forcing. 4 This definition highlights a t hird important aspect of the term catastrophe: it could potentially result in a relatively large impact . In particular, t he potential for relatively abrupt shifts in the states of natural systems are a cause for concern due to the ﬁlarge and widespread consequencesﬂ that may result (IPCC 2007) and the possibility that they occur so rapidly that ﬁhuman and other natural systems have difficulty adaptingﬂ (NRC 2002; Posne r 2004) . 3 In this paper we focus on t he economic study on specific large climate induced Earth system, outside of direct temperature response to anthropogenic emissions. Alternatively, there exists an economic literature that has focused on the policy implications of potentially large welfare impacts associated with a significantly stronger than expected climate response to anthropogenic emissions (e.g., Weitzman, 2011). 4 The IPCC has also previously used the potentially confusing terminology of ﬁlarge scale discontinuitiesﬂ to describe such events. However, we note that the notion of a discontinuity in this case would arise from observing the time path of the system over a long time horizon, and does not refer to a mathematical discontinuity in the state transition dynamics of the system.
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6 increases in the atmospheric concentration of greenhouse gases from the burning of fossil fuels, deforestation, and other land -use change could trigger changes within an Earth system . Feedback effects within the se system s could amplify these changes (e.g., surface melting of an ice sheet can affect the speed of ice flow) leading to even large r impacts, such as the complete collapse of ice sheets, substantial dieback of the Amazon fore st, or the thaw ing of permafrost, to name a few . Finally, the new state may exhibit persistence: the Earth system is described as eventually settling into a new but fundamentally different stable state that is irreversible (e.g. NRC 2002; IPCC 2007) or reversible only over very long time scales (Perrings 2003; Schneider 2003). Our analogy with other natural sy stems ends here, however . While a lake ecosystem or canoe has a defined and limited set of boundaries that constrains the problem, climate change affects the entire Earth through the coupled system containing the atmosphere, oceans, ice, and biological sys tems, which increases the analytical challenge associated with understanding the overall impacts of crossing of a given threshold within a particular system . While much of the focus with regard to climate change has been on events that result from the cro ssing of a potential threshold in a natural system that leads to a new equilibrium (referred to as bifurcation) , Lenton et al. (2008) argue that it is important to consider a broader set of tipping elements in the climate system. They define the term ‚‚tip ping element™™ to describe “subsystems of the Earth system that are at least sub -continental in scale and can be switched Šunder certain circumstances Šinto a qualitatively different state by small perturbations. The tipping point is the corresponding critic al point Šin forcing and a feature of the system Šat which the future state of the system is qualitatively altered.” This characterization would include the typical bifurcation point discussed above along with cases where the system may potentially bounce be tween states after the threshold is crossed . Therefore, the transition could be irreversible or a phase after which the system returns to its prior state . Lenton et al. (2008) stress that even though some transitions are reversible in principle, they are unlikely to be reversed in practice for many centuries because of the inertia in rising temperatures. Time scales, geographic breadth, and climate end points Scientific definitions of what can be considered a catastrophe also encompass a wide range of tim e scales, geographic breadth, and climate end points. Events within the scientific literature described as resulting in ﬁrapid,ﬂ ﬁsudden,ﬂ or ﬁabruptﬂ state change include qualitative Earth system changes that can range in time scale from decades (e.g., NR C 2002; Clark et. al 2002; Alley et al. 2003; USCCSP 2008), to a few centuries (e.g., Shindell 2007), and sometimes even up to millennia (e.g., Lenton et al. 2008).
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7 This variation exists because shifts in biological systems are often considered rapid in r elation to the timescale of the previous stable state . For example, the transition in the Earth™s biosphere from the last glacial into the present interglacial condition occurred over millennia but this is still less than 5% of the time that the previous s tate had lasted (Barnosky et al. 2012) . The geographic scale of the event™s impact may also be regional (e.g., Western Europe in the case of changes in the thermohaline circulation guiding ocean currents), continental (e.g., monsoon season change in Africa ), or global (e.g., methane releases from thaw ing permafrost) . Events that scientists classify as abrupt or sudden also vary in the affected physical end points (e.g., temperature, precipitation, storms ), and th e overall impact will depend on the interacti on between all of these characteristics . Choosing how to define a potentially catastrophic event given this variation has led to multiple methods of ad -hoc classification . Some authors have proposed using geographic scale as the metric. For instance, an e vent would qualify as a potential catastrophe when it occurs on a country or even continent -wide basis (e.g. NRC 2002; Clark et al. 2002; Lenton et al. 2008; USCCSP 2008). Posner (2004) proposes limiting the definition of a catastrophe to events that are t ruly global in scale: those that could end advanced civilization as we know it . Others have proposed that the time scale should also be used to classify potentially catastrophic events . Posner (2004) points out that ﬁa span of a million years, let alone of a billion or a trillion, belongs to a timescale that cannot have real meaning for human beings living today.ﬂ Lenton et al. (2008) proposes a short list of ﬁpolicy relevant tipping pointsﬂ based on two time scales: Earth system changes that may be trigge red within this century Œ on the ﬁpolitical time horizonﬂ Œ and those that would undergo a qualitative change within this millennium Œ within the ﬁethical time horizon.ﬂ Uncertainty The scientific literature also has given notable thought to how the level of uncertainty surrounding a particular tipping point might influence its potential classification as a catastrophe . As noted by Alley et al. (2003), there is a high degree of uncertainty inherent in attempting to identify and quantify the causes of abrup t climate change, particularly near thresholds where the behavior of natural systems can become unpredictable . Therefore large error bounds exist around when a catastrophic event might be triggered, in addition to substantial uncertainty about how the tran sition would occur, and the ultimate impacts associated with them (e.g . Schlesinger et al. 2007; Keller et al. 2008). From a modeling perspective, it is difficult to capture processes that are deeply uncertain and where our understanding of that uncertaint y exists with a low level of confidence . Perrings (2003) notes that the nature of the
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8 uncertainty will be inherently difficult to characterize in the case of climate change induced catastrophic events when both the full set of possible outcomes in addition to the probability distribution of the outcomes are largely unknown. However, some researchers have attempted to better classify and understand the uncertainties associated with these events (see Lenton et al. (2008), Lenton (2011) for summaries) . Another difficulty in assessing the uncertainty around tipping points is that many aspects of the se events will be path dependent such that ﬁthe same forcing might produce different responses depending on the pathway followed by the systemﬂ (Schneider, 200 3). For instance, Schlesinger et al. (2007) indicate that even a ﬁslow, smooth forcing can induce abrupt, persistent changes in the climate system or a ‚threshold™ response.ﬂ Shindell (2007) has noted that sudden climate change can occur due to either ﬁra pid changes in the forcings or from the potential for feedbacks to be strong and perhaps nonlinear.ﬂ Numerous authors note that the forcing that could trigger a large response in the climate system may not by itself be all that notable .6 Finally, it is w orth noting that the nature of a surprise is that it is unanticipated (Schneider 2003) . Schneider argues for differentiating between abrupt events that are imaginable or expected (or at least not unexpected) and those that are ﬁtrue surprisesﬂ where the ou tcome is unknown . In the former case, even with all the inherent uncertainties discussed above, we may be able to bring modeling expertise to bear with regard to potential impacts . In the latter case, however, it may only be possible to ﬁidentify imaginabl e conditions for surpriseﬂ (Schneider 2003) . Noting this important caveat we proceed to a discussion of how economists currently define and model catastrophes. 6 These uncertainties affect the ability to model and predict Earth system behavior. Overpeck and Cole (2006) note that ﬁthe biggest obstacle to reliable abrupt climate change prediction is the limited state of our coupled atmosphere -ocean and ice sheet modeling capability–.A major challenge to the scientific community is to buil d models that can simulate the observed record of past abrupt climate change in a realistic manner.ﬂ Lenton (2009) points out that IPCC projections of climate change response do a relatively poor job of predicting abrupt or nonlinear effects of climate cha nge because they: (1) focus on global mean quantities (i.e. regional -scale spatial variability is smoothed out) ; (2) use simple climate models such as MAGICC that are designed to capture some aspects of more complicated large -scale general circulation mode ls (GCMs) but exclude their non -linear and stochastic aspects ; and (3) often average GCM output over long time horizons and sometimes over a group of runs, which smoothes out short -term temporal variability .
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9 3. How Economists Define and Model Climate Catastrophes There are several differences in the way potential climate catastrophes are characterized and discussed in economics compared to the scientific literature . An economic catastrophe is often defined with regard to how rapidly it will occur relative to the time required for mankind to adapt to this new state of the world . For instance, the NRC (2002) defines abrupt climate change from a societal perspective as ﬁhaving sufficient impacts to make adaptation difficult.ﬂ Likewise, Williams (2009) defines rapid climate change as fast enough Œ a decade or two Œ that adaptation is impossible even for the richest countries. Despite the importance of the time scale in economics Hulme (2003) notes that this area i s a major source of confusion and miscommunication between the scientific and policy communities as the term ﬁabrupt as used by the paleoclimate community has different meanings to abrupt as used in more popular discourse.ﬂ In turn the economics literature has typically assumed time scale s over which impact s will become fully realized that are often m uch shorter than the broader, more inclusive definition of ﬁrapidﬂ or ﬁabruptﬂ used by the scientific community . This disconnect is indicative of the way economists tend to use the notion of a climate induced catastrophe more loosely, rarely applying the same degree of precision as found in the scientific literature . How th e treatment within economic studies lines up with the scientific community™s evaluation of which tipping points are likely to occur, when, and on what time scale impacts will unfold is r arely evaluated. The disconnect may also in part stem from the practice of discounting in economic models, which puts a practical limit on what is typically viewed as catastrophic in economic terms . Economists typically measure economic damages associated with an increase in global mean temperature in terms of the change in societal welfare or foregone consumption in future years, discounted to the present . At positive discount rates, impacts thousands of years in the future are quantitatively negligible wh en expressed in present value terms . Other differences in the treatment of climate change induced events may stem from the role of discounting in economic models, which places a practical limit on which events would be viewed as catastrophic in economic t erms . With a positive discount rate, the present value of social welfare losses due to climate change will be negligibly affected by events occurring far in the future (e.g., in thousands of years). In this section we first examine the theoretical evidenc e to support the assertion that climate catastrophes may play an important role in understanding socially efficient abatement policy . Then we review how the economics field has chosen to model the types of events the scientific literature refers to as ﬁcat astrophes.ﬂ
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