Applied Studies in Climate Adaptation

By Jon Barnett

The book advances knowledge about climate change adaptation practices through a series of case studies. It presents important evidence about adaptation practices in agriculture, businesses, the coastal zone, community services, disaster management, ecosystems, indigneous populations, and settlements and infrastructure. In addition to 38 case studies across these sectors, the book contains horizon-scoping essays from international experts in adaptation research, including Hallie Eakin, Susanne Moser, Jonathon Overpeck, Bill Solecki, and Gary Yohe.

Australia’s social-ecological systems have a long history of adapting to climate variability and change, and in recent decades has been a world-leader in implementing and researching adaptation, making this book of universal relevance to all those working to adapt our environment and societies to climate change.

• Language: English
• Publisher: Wiley
• Release date: Oct 27, 2014
• ISBN: 9781118845035

Book preview

Section 1

Frameworks for enabling adaptation

3

Thoughts on the context of adaptation to climate change

GARY YOHEa

Department of Economics, Wesleyan University, USA

Working Group II of the Intergovernmental Panel on Climate Change (IPCC 2007a) focused their attention on adaptation and vulnerability in their contribution to the IPCC’s Fourth Assessment Report. It made the case that contemplating adaptation to climate change should no longer be dismissed as evidence that society is giving up on trying to ameliorate the problem at its source (by reducing emissions of heat-trapping gases of all sorts). Rather, the Working Group II report argued that adaptation must be included as an essential part of society’s portfolio of responses to growing risks arising from climate change. Reports on adaptation to climate change released by the National Research Council of the United States (NRC 2010a) under the rubric of ‘America’s Climate Choices’ adopted and reinforced this conclusion by, for example, recognising the evolving adaptation strategies of governments at all levels around the world. This is also true for the New York (City) Panel on Climate Change (NPCC 2010a, b) and the US National Climate Assessment. The latter contributed directly to President Obama’s Climate Action Plan (White House 2013) by speaking of the necessity, if not the means, of increasing ‘preparedness’.

Indeed, in language that was unanimously approved by all of the nations who have signed the United Nations Framework on Climate Change (word by word), the nations of the world closed their ‘Summary for policymakers’ for the Fourth Assessment Report Synthesis document by emphasising the necessity that decision-makers across the globe consider the concept of risk as their primary perspective in their international and national deliberations on responses to climate change. To be specific, they agreed that: ‘Responding to climate change involves an iterative risk management process that includes both adaptation and mitigation and takes into account climate change damages, co-benefits, sustainability, equity and attitudes to risk’ (IPCC 2007b, p. 22, emphasis added).

To be clear, national governments throughout the world have, by accepting this language, clearly stated their fundamental understanding of the urgency of responding with adaptation as well as mitigation and that managing risks associated with climate change must be the central theme in present and future planning and policy decisions concerning both. Moreover, they have identified critical criteria upon which they will weigh their options and they have recognised that ‘mid-course corrections’ must be anticipated as part of the process.

Societies notice many of the impacts of climate change by detecting increasingly intense and/or more frequent extreme weather events and attributing the observed change in weather to climate change. Long a part of the Reasons for Concern (beginning with IPCC 2001) under the title ‘Risk of extreme weather events’, modern analysis has carefully begun to assess relative confidence in statements of detection and attribution across extreme events by assessing evidence and agreement in the published literature (see Mastrandrea et al. 2010). These assessments are of course the foundation for using observed changes to support projections of further change over the next decades and centuries. Of particular importance here are extreme events such as heavier precipitation events (snow in the winter and rain in the summer), more intense coastal storms (at least with respect to their manifestation when they come ashore, impacts that are driven by observed and projected sea-level rise for all types of storms), and severe droughts, floods, wildfires and heat waves (with appropriate recognition of confounding factors, but also exposure of human and natural systems).

In these events, direct attribution to anthropogenic sources of climate change is difficult. The preponderance of evidence continues to lead IPCC and other assessments to focus on changes that can however, to some degree, be attributed to human activity. The magnitude of these changes will very likely be exacerbated over the near and more distant future as natural climate variability (through extreme events) is distributed around the increasingly worrisome central tendencies of climate change--especially since observed temperature increases driven by higher greenhouse-gas concentrations reflect only 50% of the corresponding equilibrium warming (Solomon et al. 2009). It follows that near-term decisions to mitigate climate change modestly (or not at all) may actually commit the planet to sudden, irreversible changes by the end of the century (Solomon et al. 2009; NRC 2010b).

Urgency in that regard is amplified by the emerging understanding that long-run equilibrium temperature is determined by the maximum of atmospheric concentrations (of greenhouse gases such as carbon dioxide calibrated in terms of carbon-dioxide equivalents; Solomon et al. 2009). Does this mean that converging to a lower concentration limit buys us very little? Probably, but to be clear the question raised here is ‘Why should the planet waste resources to lower concentrations from an observed maximum if equilibrium temperature and therefore damages cannot be lowered significantly for thousands of years?’ The answer is that even with a low discount rate, doing so would be a bad investment because temperature and associated damages will have been determined by higher concentrations. Investments designed to converge to a lower concentration target from above would produce only a few benefits that would likely be dwarfed by the mitigation costs of doing so.

Given this evidence, it is safe to say that climate is changing (the old normal is broken even if the new normal has not yet been established). In the absence of significant reductions in emissions of greenhouse gases designed to stabilise concentrations at some as-yet-undetermined (but higher than current) level, the climate will continue to change at an accelerating pace over the short run and into the longer run with growing, if uncertain, consequences. The manifestations of this change will therefore demand that more attention be paid to adaptation as part of plans to promote sustainable development, but without giving up on mitigation.

In interpreting this last point, it is essential to emphasise the fundamental linkages between adaptation (specifically with respect to climate change) and sustainable development more broadly defined (which includes responding to many other sources of societal stress). This point was made explicitly in chapter 20 of IPCC (2007a) where authors noted that then-recent work had confirmed the chapter 18 IPCC (2001) conclusion that any system’s vulnerability to climate change, climate variability and/or any other external stress is the product of exposure and sensitivity to that stress (or to multiple sources of multiple stress, for that matter). Nothing has really changed since. It is still the case that exposure and sensitivity can be influenced positively or negatively by individual or societal responses to climate change and/or other stresses. Reducing exposure and sensitivity as well as building capacity to adapt, in combination with reductions in greenhouse gases, remain among the essential elements of responses to manage climate risks.

References

IPCC (2001) Climate Change 2001: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change. McCarthy, J.J., Canziani, O.F., Leary, N.A., Dokken, D.J. and White, K.S. (eds) Cambridge University Press, Cambridge.

IPCC (2007a) Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, P.J. and Hanson, C.E. (eds) Cambridge University Press, Cambridge.

IPCC (2007b) Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Pachauri, R.K. and Reisinger, A. (eds) Cambridge University Press, Cambridge.

Mastrandrea, M., Field, C., Stocker, T. et al. (2010) Guidance Notes for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental Panel on Climate Change, Geneva.

National Research Council (NRC) of the United States (2010a) Adapting to the Impacts of Climate Change. National Academies Press, Washington, DC.

National Research Council (NRC) of the United States (2010b) Climate Stabilization Targets: Emissions, Concentrations, and Impacts of Decades to Millennia. Prepublication. National Academies Press, Washington, DC.

New York Panel on Climate Change (NPCC) (2010a) Climate change adaptation in New York City: Building a risk-management response. Annals of the New York Academy of Sciences 1196.

New York Panel on Climate Change (NPCC) (2010b) Adaptation Assessment Guidebook. NPCC Workbook. New York Academy of Sciences, New York.

Solomon, S., Plattner, G-K., Knutti, R. and Friedlingstein, P. (2009) Irreversible climate change due to carbon dioxide emissions. Proceedings of the National Academies of Science 106(6), 1704–1709.

White House (2013) Climate Action Plan. Executive Office of the President, Washington.

Yohe, G. (2010) Risk assessment and risk management for infrastructure planning and investment. The Bridge 40(3), 14–21.

Yohe, G. (2013) Climate change adaptation: a risk-management approach. In: Atkinson, G., Dietz, S., Neumayer, E. and M. Agarwala (eds) Handbook of Sustainable Development, 2nd edition. Edward Elgar Publishing, Cheltenham, UK.

Note

aThis essay relies heavily on Yohe (2010) and Yohe (2013), in thought as well as exposition.

4

Reflections on disaster loss trends, global climate change and insurance

JOHN MCANENEY¹, RYAN CROMPTON¹, RADE MUSULIN², GEORGE WALKER², DELPHINE MCANENEY¹ AND ROGER PIELKE JR³

¹ Risk Frontiers, Macquarie University, Australia

² Aon Benfield Analytics Asia Pacific, Australia

³ Center for Science & Technology Policy Research, University of Colorado, USA

4.1 Introduction

This paper summarises salient findings from the NCCARF-funded report entitled ‘Market-based mechanisms for climate change adaptation’ by McAneney et al. (2013). It first examines the mechanisms responsible for the increasing cost of natural disasters, the implications of this for climate change adaptation and briefly explores the capacity of insurance markets to incentivise such adaptation. For commentary on catastrophe bonds and capital market funding of disaster losses (Froot 2001), the reader is referred to the original report (McAneney et al. 2013).

The increase in natural disaster losses has led to concerns that anthropogenic climate change is contributing to this trend. Perils of concern are those likely to cause damage to property assets, in particular tropical cyclones, storms including hailstorms, floods and bush (wild) fires. This paper summarises recent Australian scholarship on this topic as well as efforts to estimate the timescale at which an anthropogenic climate change signal might be detectable in US hurricane loss data. US hurricanes warrant special attention because: (1) of their impact on the global insurance market through the supply of and demand for reinsurance; (2) the availability of a long-term normalised economic loss history from land-falling hurricanes; and (3) high-quality modelling of the impact of anthropogenic warming on basin-wide hurricane activity.

This paper also addresses the potential for insurance to be a positive actor in helping to reduce the risk to property by extreme weather that may be influenced by future climate change. This is not a responsibility that the private sector can shoulder on its own however, so we review government involvement in the provision of natural catastrophe insurance. We conclude with some brief observations about the challenge posed by the rising toll of natural disasters and whether the insurance industry can play a role in incentivising risk reduction.

4.2 Property losses and natural disasters due to extreme weather

Before apples-with-apples comparisons can be made between the impacts of past and more recent natural-hazard loss events, changes in various societal factors known to influence the magnitude of losses must first be accounted for. Climate-related influences stem from changes in the frequency and/or intensity of natural perils, whereas socio-economic factors comprise changes in the vulnerability and exposure to the natural hazard. Adjustment for the latter (non-climate-related) factors has become known as loss normalisation (Pielke and Landsea 1998; Pielke et al. 2008). Loss normalisation attempts to answer the question: what would be the losses if historic events were to recur under current societal conditions? In what follows we describe recent Australian responses to this question.

Crompton and McAneney (2008) normalised Australian weather-related insured losses over the period 1967–2006 to 2006 values. Loss data obtained from the Insurance Council of Australia (ICA; http://www.insurancecouncil.com.au/) were adjusted for changes in dwelling numbers and nominal dwelling values (excluding land value) since the time of the original event. In a marked departure from previous normalisation studies, an additional adjustment was applied to tropical cyclone losses to account for improvements in construction standards mandated for new buildings in tropical cyclone-prone parts of the country (McAneney et al. 2007; Mason et al. 2013). The success of improved building standards in reducing losses has been demonstrated repeatedly in more recent events including tropical cyclones Larry (in 2006) and Yasi (in 2011).

Figure 4.1a and b shows the annual aggregate losses and the annual aggregate normalised losses (2011/12 values) for weather-related events in the ICA’s Disaster List. These figures are updated from those of Crompton and McAneney (2008) using a more refined methodology described in Crompton (2011). Importantly, no trend is evident in the normalised losses (Fig. 4.1b), implying that socio-economic factors alone are sufficient to explain the increase in the cost of insurance sector losses (Fig. 4.1a). In other words, it is not possible to detect the role of anthropogenic climate change once losses are normalised. We note that despite record high 2012/13 summer air temperatures across Australia, industry losses for the financial year (1 July 2012 to 30 June 2013) were very close to the long-term average normalised loss of AU$ 1.1 billion.

c4-fig-0001c4-fig-0001

Figure 4.1 (a) Annual aggregate insured losses (AU$ million) for weather-related events in the ICA Disaster List for years beginning 1 July; (b) as in (a) but with losses normalised to 2011/12 values.

Source: Crompton 2011. Reproduced with permission of Risk Frontiers.

Readers might imagine bushfire losses to be more sensitive to increasing air temperatures than some other perils. Following the large loss of life and building damage experienced in the 2009 bushfire in Victoria, Crompton et al. (2010) examined the history of fatalities and building damage since 1925. Figure 4.2a and b shows the actual and normalised building damage expressed in numbers of residential homes destroyed. Once building damage is adjusted for increases in dwelling numbers, no residual trend was found that might be attributed to anthropogenic climate change or other factors, for that matter. A similar result was found for fatalities.

c4-fig-0002c4-fig-0002

Figure 4.2 (a) Annual aggregate building damage expressed as the number of House Equivalents (HE) destroyed due to bushfire events in Australia for year beginning 1 July. (b) As in (a) but with HE normalised to 2008/09 values. The time series begins in 1925, the first year in the 20th century to experience large numbers of building destruction due to bushfires. HE refers to all building damage but in this case can be interpreted as numbers of residential dwellings.

Source: Crompton et al. 2010. © American Meteorological Society. Used with permission.

Bouwer (2011) provides a comprehensive review of loss normalisation studies which concur that, despite widespread assertions to the contrary, it is not yet possible to detect or attribute an anthropogenic influence on disaster losses. McAneney et al. (2013) updated the Bouwer (2011) review and noted that the Special Report of the Intergovernmental Panel on Climate Change came to the same conclusion (IPCC 2012) on the lack of attribution.

After also examining these issues, Barthel and Neumayer (2012, p. 229) concluded that: ‘Climate change neither is nor should be the main concern for the insurance industry. Accumulation of wealth in disaster prone areas is and will always remain by far the most important driver of future economic disaster damage.’

We agree that climate change is not likely to be a material threat for the insurance industry, but in Section 4.5 we turn the question around and ask whether or not insurance has a role in encouraging climate change adaptation.

4.3 Timescale at which an anthropogenic climate change signal might be observed in US tropical cyclone losses

Crompton and colleagues posed the following question in respect to US hurricanes: ‘If changes in storm characteristics happen as projected in a warming climate, then on what time frame – the emergence timescale – might we expect to detect the effects of those changes in economic loss data with some scientific certainty, say with 95% confidence?’ (Crompton et al. 2011, p. 2).

The point of departure for Crompton et al. (2011) was projections of future Atlantic basin hurricane activity from the NOAA Geophysical Fluid Dynamics Laboratory (Bender et al. 2010). Combining these with the Pielke et al. (2008) normalised loss history, a bootstrapping analysis showed anthropogenic signals to emerge at timescales of between 120 and 550 years. This wide range derives from the different Global Climate Models (GCMs) that set the boundary conditions for the downscaling. It took 260 years for an 18-model ensemble-based signal to emerge!

Emanuel (2011) implemented an alternative methodology to Crompton et al. (2011), also finding the time to detection to be long: in excess of a century for three of four models analysed, with one indistinguishable from background noise even after 200 years. These long time scales reflect the challenging signal-to-noise problem facing climate change attribution in disaster loss time series. It also argues strongly against using abnormally large losses from individual Atlantic hurricanes or seasons as evidence of anthropogenic climate change.

4.4 Government provision of catastrophe insurance

Government involvement in the provision of catastrophe insurance has usually arisen in the face of perceived market failures of the private market, often following a significant natural disaster. Such residual market mechanisms or pools have assumed the legacy of inappropriate land use, unrealistic risk assessment and lack of consideration to risk reduction. The issue has high currency in Australia after large economic losses caused by flooding in Queensland and Victoria in 2011 and widespread criticism of insurers whose policy covers at the time often excluded damage due to riverine flood (van den Honert and McAneney 2011).

In their examination of various government pools, McAneney et al. (2013) identify some key distinctions between private and public insurance schemes as follows.

Government insurance systems can raise funds post-event by issuing government bonds, levies on policies or new taxes, for example.

Private insurance systems must prefund all losses; it is not acceptable to have a loss and then try to collect funds to pay for it after an event (American Academy of Actuaries 2012).

Private insurance systems usually attract taxes on profits, which can mean that earnings on funds needed to pay claims from infrequent events are taxed away because they show up as income in years without extreme events. Government insurance systems are not bound by this constraint.

Private insurance systems operating in a competitive market increasingly set prices related to risk.

Governments can use their sovereign power to compel one group of consumers to pay too much in order to provide a subsidy to another.

Both private and government insurance systems can in principal encourage mitigation through premium discounts and risk-informed underwriting. However, government insurance systems often dilute the incentives for mitigation by subsidising high risks from low risks or by raising revenue for losses from an unrelated source, like a tax levy.

With financial back-up or guarantees from the state, government pools can fall back on resources not available to the private sector. This was the case for the Earthquake Commission in New Zealand after the 2010 and 2011 Christchurch earthquakes and more generally in situations where losses become so large that the private sector cannot efficiently handle them without extreme disruption (such as would be the case for a possible $100 billion US hurricane in Florida). In this case the ‘actuarially sound’ premium and the affordable premium diverge to the point where in effect everyone goes uninsured, which may be an undesirable outcome.

Just like their private sector counterparts, public sector insurance schemes differ around the world. In Spain, the provision of catastrophe insurance is socialised with a standard levy applied to all insurance products. In New Zealand, the Earthquake Commission covers the first NZ$ 100 000 of loss to residential property insured with the private sector and with a single premium. In the UK a new arrangement to deal with flood risk is being negotiated in which a not-for-profit organisation, Flood Re, is expected to assume responsibility for homes at risk to events more frequent than a 1-in-200 year flood. Insurance companies in France are required to cover most hazards as part of standard policies, with the government offering subsidised reinsurance as an alternative to the commercial reinsurance market. In none of the schemes examined were premiums risk-rated. In the Netherlands, which faces flooding as an existential threat, no government insurance exists to cover the threat for residential homeowners; the focus has been on national flood defences.

Government pools usually contain an inherent contradiction in trying to provide reduced (or subsidised) cost insurance to high-risk properties, and so the funding of deficits to which they are inevitably prone is important (McAneney et al. 2013). As stated above, pools can in principle minimise deficits over time by encouraging risk mitigation but, as for Kunreuther (1996, 2006), we found little evidence of this. The National Flood Insurance Program (NFIP) and Texas Windstorm Insurance Association (TWIA) were exceptions to the rule. A positive outcome of the NFIP is the high percentage of local authorities imposing floodplain management schemes based on the 100-year return period flood height; however, Burby (2001) questions the extent to which this has inhibited construction activity in flood-hazard areas or had much impact on federal disaster relief costs. Because the NFIP is voluntary, it also suffers from adverse selection with only those at high risk likely to buy cover. The TWIA has had a big effect on building standards, particularly for houses and other low-rise buildings.

An ongoing contentious issue in the US has been the degree of political influence exerted to keep premiums low and to have policyholders in low- and high-risk areas charged similar rates. In the absence of adequate regulation, this lack of financial incentives for mitigation encourages development in high-risk areas (Jaffe and Russell 2013). Calls for reform in the US may bring about some positive changes in the residual market mechanisms, but there is debate as to the place of a state-run entity in the insurance market (Jaffe and Russell 2006).

4.5 Can insurers promote climate change adaptation?

The primary goal of the insurance sector is the assessment and transfer of risk, as it is currently understood. Insurance policies generally have a duration of a single year, a period at odds with the lifespan of a building (generally 50–100 years) and the timescale at which climate change amplification of extreme weather might become measurable in loss data. This mismatch makes it difficult for insurers to materially influence adaptation to future climate change except through the rigorous pricing of the existing risk. A move to risk-rated premiums could have socially desirable outcomes if it were to encourage changes by government and other actors to invest in mitigation infrastructure, better building codes and risk informed land-use planning practices, and so over time act to quell the increase in disaster losses.

When we look to ways to address the increasing trend in losses it is impossible to overlook the decisive role that poor land-use planning has played in recent disasters. We note just two examples of loss of life and buildings from Australia: the 2009 Victorian bushfires and the 2010/11 Queensland floods. In the first case, work undertaken for the 2009 Royal Commission (Chen and McAneney 2010; Crompton et al. 2010) showed that a large proportion of buildings destroyed either lay within bushland or at a very small distance from it. In fact, 25% of destroyed homes were situated within a metre of the bush and so were effectively part of the fuel