Climate Change and Damage from Extreme Weather Events by

The risks of extreme weather events are typically being estimated, by federal agencies and others, with historical frequency data assumed to reflect future probabilities. These estimates may not yet have adequately factored in the effects of past and future climate change, despite strong evidence of a changing climate. They have relied on historical data stretching back as far as fifty or a hundred years that may be increasingly unrepresentative of future conditions. Government and private organizations that use these risk assessments in designing programs and projects with long expected lifetimes may therefore be investing too little to make existing and newly constructed infrastructure resistant to the effects of changing climate. New investments designed to these historical risk standards may suffer excess damages and poor returns. This paper illustrates the issue with an economic analysis of the risks of relatively intense hurricanes striking the New York City region. I. How and Why Climate Risks may be Under-estimated Over the past half-century, temperatures and precipitation in the United States have gradually increased, more of the precipitation has fallen in heavy storms, sea level and sea surface temperatures have risen, and other aspects of climate have also changed. A scientific consensus agrees that such changes will continue for many decades, whatever reductions of greenhouse gas emissions are achieved. It is not these gradual changes that are most threatening, however. Organisms and ecosystems can tolerate a range of weather conditions and man-made structures and systems are designed to do so as well. Within this range of tolerance, weather variability causes little damage and if change is sufficiently gradual, many systems can adapt or be adapted. When weather varies outside this range of tolerance, however, damages increase very disproportionately. As floodwaters rise, damages are minimal so long as the levees hold, but when levees are overtopped, damages can be catastrophic. If roofs are constructed to withstand eighty mile an hour winds, a storm bringing seventy mph winds might only damage a few shingles, but if winds rose to one hundred mph, roofs might come off and entire structures be destroyed. Plants can withstand a dry spell with little loss of yield, but a prolonged drought will destroy the entire crop. The very damaging risks from climate change arise from an increasing likelihood of such extreme weather events, not from a gradual change in average conditions. Unfortunately, even if weather conditions do not become more volatile as climate changes, which might happen, a shift in average conditions will also bring about a changing probability of weather events far removed from average conditions. For example, as more rain falls in heavy storms, the probability rises that deluges will occasionally occur that bring about extreme flooding and disastrous damages. As average temperatures rise, the likelihood of an extreme heat wave rises too. Weather risk assessments have not come to grips with the changing probabilities of extreme weather. The methodologies in use typically are backward-looking and conservative. The frequencies with which specific weather events occur are estimated from measurements in the historical record going back decades. These frequencies, calculated from past records, are then used to “fit” to the data a probability distribution with a similar mean, variance, and skewness. The probability distribution can then be used to estimate the likelihood of extreme weather, even though there are few, if any, such events in the historical record. Estimating the probability of extreme, and therefore very infrequent, weather events in this way is inherently difficult, because there are so few such events in the measured record. Extrapolating from the occurrence of rarely observed events to the probability of even more extreme events beyond the historical record is unavoidably uncertain. When climate is changing, an even more serious problem lies in assuming that the future will be like the past, and projecting probabilities estimated from historical data into the future. Not only are agencies charged with assessing weather risks making this assumption, that the estimated probability distributions are stationary, they are also ignoring measured trends in historical weather patterns. They do so for two main reasons. The first is uncertainty whether an apparent trend is real or is just a poorly understood cyclical phenomenon that will be reversed, or just a string of random events. The second is the dilemma in giving more weight to recent observations, which might better represent current conditions, but which would provide less data with which to estimate a probability distribution representative of extreme and unlikely events. Uncertainty about future climate conditions affecting particular localities and weather phenomenon is the main reason why weather risk assessments estimates are still based on historical data, despite strong scientific and empirical evidence that the future will not be like the past. Conservative agencies retain methodologies and estimates likely to be erroneous rather than make use of scientific projections of future conditions that are still quite uncertain, especially at a regional or local geographic scale. The question bedeviling weather risk assessment is “If the future will not be like the past, what will it be like?” Climate models are still unable to provide answers to this question with high reliability. Nonetheless, weather risk assessments become increasingly outdated as time passes or when projected further into the future. They provide unreliable guidance for the design, placement and construction of infrastructure that will be in place for many decades and vulnerable to extreme weather throughout its useful life. By underestimating future risks, they also provide unreliable guidance for investment and program decisions to make existing infrastructure and communities more resistant to extreme weather. As a result, according to a new report by a National Research Council panel, “Government agencies, private organizations, and individuals whose futures will be affected by climate change are unprepared, both conceptually and practically, for meeting the challenges and opportunities it presents. Many of their usual practices and decision rules—for building bridges, implementing zoning rules, using private motor vehicles, and so on—assume a stationary climate—a continuation of past climatic conditions, including similar patterns of variation and the same probabilities of extreme events. That assumption, fundamental to the ways people and organizations make their choices, is no longer valid.” This is a problem of broad and significant scope. Among the public and private sector organizations that are exposed to increasing but underestimated risks are • Local, state and federal disaster management agencies; • Local, state and federal agencies that finance and build public infrastructure in vulnerable areas as well as those that own and operate vulnerable infrastructure; • Private investors and owners of vulnerable buildings and other physical property; • Property and casualty insurers; • Creditors holding vulnerable infrastructure directly or indirectly as collateral; • Vulnerable businesses and households. Clearly, this listing encompasses a large proportion of the American economy, and an assessment of the vulnerable regions would also extend over a large part of the country, including coastal regions subject to hurricanes, storm surges, and erosion; river basins subject to flooding; and agricultural areas subject to wind, storm and drought damage. These under-estimated risks should not be neglected in any program of adaptation to climate change. Efforts to improve climate change forecasts at regional and local scale should be intensified. In these efforts, more emphasis should be placed on forecasts of the likelihood of extreme weather events. While these efforts are underway, however, agencies responsible for weather risk assessment should update their estimates, incorporating the best available scientific climate projections that provide guidance regarding future conditions. Uncertainties in these projected weather risks should be frankly acknowledged and explained. In addition to their best estimates, agencies should also present plausible uncertainty bands around those probabilities. Finally, vulnerable agencies such as those listed above should be encouraged or directed to use these revised risk estimates in their program and investment planning as an important step toward anticipatory adaptation to climate change. II. A Case Study: Hurricane Risk in the New York City Region To further clarify and illustrate the issue, a case study is presented of the risks to the New York City metropolitan region from hurricane damage. Of course, the scope of the problem is much wider. Hurricane risks imperil the entire Atlantic seaboard, the Gulf of Mexico, the Caribbean, many Pacific coastal areas, and the Indian Ocean. Nor is the issue just that of hurricane risks: risks of floods, droughts, and severe storms may also be underestimated for the same underlying reasons. The New York metropolitan region extends across three states and encompasses an extraordinarily dense concentration of infrastructure, physical assets, and business activity. In 2006, for example, the value of insured coastal property in the New York, Connecticut and New Jersey region was almost $3 trillion. The metropolitan region’s economy is vulnerable to the more extreme effects of climate change. Storm surges could reach 18-24 feet in a strong hurricane. Low-lying regions, including Kennedy Airport and lower Manhattan, would flood. Roads, subway and tunnel entrances would be submerged, along with ground level and underground infrastructure. High winds would do severe damage, partly by blowing dangerous debris through city streets. The New York City government has recognized such risks and in 2008 created the New York City Panel on Climate Change and the Climate Change Adaptation Task Force to develop an adaptation strategy. Studies toward this objective are underway. The following case study builds on several relevant investigations, incorporating them as components in an overall design that shows to what extent hurricane probabilities may be under-estimated, how economic damage risks may consequently also be underestimated, how these risks assessments can be updated and projected into the future based on relevant scientific information, and how these updated risk assessments might be used to improve decisions on investments in adaptation. The technical details of the analysis are contained in the mathematical appendix. The starting point is the probability assessment carried out by the National Hurricane Center (NHC), an office within the National Oceanic and Atmospheric Administration. The methodology used for NYC and other coastal regions counts the occurrence of hurricanes of specific intensities (defined in terms of maximum sustained wind speeds) striking within a 75mile radius during the historical record of approximately one hundred years. NHC scientists fitted a particular probability distribution, the Weibull distribution, to these observed frequencies and the probabilities of hurricanes of various intensities were then read off the fitted probability distribution. There were no actual observations of the most severe hurricanes in the historical record for the New York region, so those probabilities were extrapolations based on the fitted distribution. The results, expressed as the expected return periods, which are the reciprocals of the annual probabilities, are shown in Table I for various categories of hurricanes. Table I Estimated Hurricane Probabilities for the New York Metropolitan Region By the National Hurricane Center Hurricane Category Maximum Wind Speed (mph) Expected Return Period Annual Probability Cat 1 74-95 17 years .059 Cat 2 96-110 39 years .026 Cat 3 111-130 68 years .015 Cat 4 131-155 150 years .007 Cat 5 >155 370 years .0027 These probability estimates were constructed in 1999. It is questionable whether these estimates were valid in that year, because there has apparently been an upward trend in intense hurricanes in the North Atlantic over at least the past 35 years. The number of Category 4 and 5 hurricanes in the North Atlantic increased from 16 during the period 197589 to 25 from 1990-2004. Consequently, the earlier years in the historical record used to compute frequencies might not have been representative of the final years. There is good reason to believe that this increasing frequency of stronger hurricanes in the North Atlantic is linked to climate change through the gradual rise in sea surface temperatures. Warming ocean waters provide the energy from which more intense hurricanes are developed and sustained. According to a recent study, a 3 degree centigrade increase in sea surface temperature would raise maximum hurricane wind speeds by 15 to 20 percent. Measurements throughout the oceans have found a rising trend in sea surface temperatures at a rate of approximately 0.14 degrees centigrade per decade. The rate of warming is apparently increasing, however, and the North Atlantic warming has been faster than the global average. According to a recent examination, in the 28-year period from 1981 to 2009, warming in the North Atlantic has averaged 0.264 degrees centigrade per decade, roughly twice the global average. Rising sea surface temperatures in the North Atlantic, the driving force behind the increasing frequency of intense hurricanes, explain why backward-looking historical probability estimates, such as those generated using the National Hurricane Center’s approach, probably do not provide adequate guidance with respect to current and future risks. This problem is compounded by the rising trend in sea level, itself partly the result of increasing ocean temperatures. Higher sea levels and tides raise the probability of flooding driven by hurricane-force winds. In the North Atlantic between New York and North Carolina, sea level has also risen more rapidly than the global average, at rates between .24 and .44 centimeters per decade. These scientific findings and measurements can be used to project hurricane risk estimates into the future. The trend in sea surface temperature, linked to the relationship between sea surface temperature and maximum wind speed, provides a way to forecast changes in the intensity of future hurricanes. High and low estimates can define a range of future probabilities. Though there are considerable uncertainties inherent in forecasts based on this approach, the results are arguably more useful than static estimates based on historical data that fail to incorporate any relevant information about the effects of climate change. At a minimum, this approach can provide a quantitative sensitivity analysis indicating by how much existing estimates may be under-estimating future risks. Table 2 displays some results, based on both the higher and lower estimates of sea surface temperature trends and the relationship between sea surface temperature and maximum wind speeds. The table shows the estimated return periods for hurricanes striking the region, based on the 1999 Weibull distribution estimated by the National Hurricane Center return periods for the New York metropolitan region. (Figures differ slightly from those in Table 1 for less intense storms because of curve-fitting variances.) In addition, it presents return periods for 2010, 2020, and 2030 estimated by indexing the scale parameter of the probability distribution to a time trend based on the rate of temperature change and its effect on maximum wind speeds. The ranges shown for the decades 2010-2030 are based on the high and low estimates of the rate of sea surface temperature increase. Table 2 Estimated Hurricane Return Periods, 2000-2030 Hurricane Category 200