Changnon (1996a) studied the effects of potential shifts in summer precipitation on transportation in Chicago, using data for 1977–79 and assuming continued use of current modes of transport. The study suggests that a future climate with more summer rainy days, somewhat higher rain rates, and more rainstorms would increase total vehicular accidents and total injuries in vehicular accidents, reduce travel on public transportation systems, and cause more aircraft accidents and delays. A drier climate probably would experience fewer moderate to heavy rain events, but results show that rain events during drier conditions produce a greater frequency of accidents and injuries per event than during wetter conditions. If high-heat events became more common with warmer climate, they also could become a problem. They have been known to soften asphalt roads, “explode” or buckle concrete roads, warp railroad rails, close airports because of lack of “lift” in extremely hot air, and increase mechanical failures in automobiles and trucks. On the other hand, there might be fewer mechanical failures resulting from extreme cold (Adams, 1997). Floods are costly to transportation systems, as they are to other infrastructure. Although the effect of climate change on flying weather is not clear, transportation by air is known to be sensitive to adverse weather conditions; major systemwide effects sometimes follow from flight cancellations, rerouting, or rescheduling. For example, one diverted flight can cause anywhere from 2 to 50 flight delays, and one canceled flight can result in 15–20 flight delays. The cost of a diverted flight can be as much as US$150,000, and a cancellation can cost close to US$40,000. The corresponding direct annual costs to 16 U.S. airlines are US$47 million and US$222 million, respectively (Qualley, 1997). Several additional examples of impacts on transportation are cited in Chapter 13.

Flooding and other extreme weather events that damage buildings and infrastructure could cost the world’s economies billions of dollars under climate change simply to replace the damage—a cost that could divert funds from other needed investment (see Chapter 8). However, Mimura et al. (1998) note that cost increases for disaster rehabilitation and countermeasures against natural calamities could expand the market for the construction industry. Although no direct studies have been done, it is likely that a greater incidence of summer heat waves would reduce the productivity of this sector, but a lower incidence of cold waves and snowy conditions would increase the amount of year-round construction that could be accomplished in climates that currently have long, cold winters. Changes in design requirements for infrastructure, leading to additional requirements for construction, are discussed in the SAR.

Manufacturing industries that are not directly dependent on natural resources generally would not be affected by climate unless key infrastructure is destroyed by flood or landslides, or unless shipments of inputs and outputs are affected (e.g., by snow blocking roads, airports, and train tracks; flooding or low flow that make river transportation untenable; or low water supplies that make process cooling and environmental activities more difficult). However, manufacturers are influenced by climate change in two other ways. First, they would be affected through the impact of government policies pertaining to climate change, such as carbon taxes (thereby increasing the cost of inputs). Second, they could be affected through consumer behavior that in turn is affected by climatic variations. For example, less cold-weather clothing and more warm-weather clothing might be ordered. Manufacture that depends on climate-sensitive natural resources would be affected by impacts on those resources. For example, food processing activity would follow the success of agriculture. Very little is known concerning the effects of warming on industry, and most information is highly speculative.

Climate change increases risks for the insurance sector, but the effect on profitability is not likely to be severe because insurance companies are capable of shifting changed risks to the insured, provided that they are “properly and timely informed” on the consequences of climate change (Tol, 1998). For example, during the great storms in the early 1990s, the insurance sector reacted to increased risk and large losses by restricting coverage and raising premiums. Tucker (1997) also shows that increased climatic variability necessitates higher insurance premiums to account for the higher probability of damages. However, insurance companies still can be destabilized by large losses in a major weather-related catastrophe in a region where actuarial tables and estimated risks do not adequately reflect true weather risk (including greater variability), and companies therefore may not have made adequate provision for losses. See Chapter 8 for a description of impacts on financial services.

Valuation of climate impacts remains difficult on three grounds. The first is uncertainty associated with determining physical changes and responses to these changes. The second is economic valuations of these changes that vary across regions. Fankhauser et al. (1998) show that damage cost estimates are sensitive to assumptions made on the basis of valuation (willingness to pay versus willingness to accept), accountability for impacts, differentiation of per unit values, and aggregation of damage costs over diverse regions. A third problem can be expressed as follows: “Which metric?” Five popular metrics are used: market costs, lives lost, species lost, changes in the distribution of costs/benefits, changes in quality of life (loss of heritage sites, environmental refugees, etc). Schneider et al. (2000) conclude that when aggregation exercises are undertaken, disaggregation of all estimated effects into each of five numeraires is needed first, followed by a traceable account of any aggregation so others holding different weighting schemes for each numeraire can re-aggregate. This is done rarely, if ever.

The Workshop on the Social and Economic Impacts of Weather at the National Center for Atmospheric Research, 2–4 April 1997, in Boulder, CO, estimated that property losses from extreme weather of all types currently costs the United States about $15 billion yr^-1 ($6.2 billion related to hurricanes), as well as about 1,500 deaths (about half resulting from cold events); the worst flood and hurricane years yield about $30–40 billion in property losses.

Smith (1996) standardized estimates of climate change damages for the United States for a 2.5°C warming, a 50-cm sea-level rise, 1990 income and population, and a 4% real rate of return on investments. Total damage estimates are slightly less than 1% of United States gross national product (GNP) in 1990. Within individual sectors such as agriculture and electricity, however, standardized damages differ by more than an order of magnitude. This level of uncertainty appears to apply among experts as well. For example, Nordhaus (1994) surveyed experts, and their damage estimates ranged over more than an order of magnitude.

Yohe et al. (1996) calculated the cost of a 50-cm sea-level rise trajectory for developed property along the U.S. coastline. Transient costs in 2065 were estimated to be approximately $70 million (undiscounted and measured in constant 1990 US$). These costs are nearly an order of magnitude lower than estimates published prior to 1995 (e.g., Fankhauser, 1995). This is because Yohe et al. (1996) incorporated the cost-reducing potential of market-based adaptation in anticipation of the threat of sea-level rise. In addition, they assumed efficient discrete decisions to protect or abandon small tracts of property, based on their economic merit. Some work since suggests that maladaptation may cause the costs of sea-level rise to be somewhat higher (West and Dowlatabadi, 1998).

Current impact assessment methods focus on comparing current conditions to a single alternative steady state—that associated with doubling of GHGs. Mendelsohn and Schlesinger (1999) attempt to estimate climate response functions for market sectors in the United States that reflect how damages change as climate changes through a range of values. Impacts are generated by using national climate values, rather than global values, and the timing of climate change is included in the modeling of capital-intensive sectors such as coastal resources and timber, which cannot adjust quickly. Empirical estimates of climate response functions are based on laboratory experiments coupled with process-based simulation models and cross-sectional studies (Mendelsohn and Neumann, 1998). Both methods indicate that agriculture, forestry, and energy have a bell-shaped relationship to temperature. Similarly, an increase in precipitation is likely to be beneficial to some agriculture, forestry, and water sectors, although this effect is reversed at sufficiently high levels. However, this work captures neither the transient response of the climate system nor the actual dynamics of the energy sector in response to climate (e.g., Schneider, 1997).

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