Geography Weather and Climate Damage Studies
by
Jessica Weinkle, Roger Pielke
  • LAST MODIFIED: 24 July 2018
  • DOI: 10.1093/obo/9780199874002-0194

Introduction

The long history of scientific efforts to understand and predict weather reflects society’s concern for weather’s impacts on life, property, and other values. Damage refers to any number of things that may be harmed. For instance, medical professionals are concerned with damage to public health. Understandings of damage shape political debate about the meaning of weather and climate extremes. In recent decades, the lens in which weather and climate damage is viewed has become tightly bound to the evolution of the insurance industry, technological innovations, and climate change policy debate. Popular perceptions of a link between the emission of greenhouse gases and disaster losses places research on weather extremes and damage trends at the forefront of climate change policy debate. These debates find practical meaning in the context of decision-making, particularly in estimating damage for the purposes of insurance. While a robust literature attributes observed trends in weather damages to increases in wealth and population, attributing the increases in losses to changes in the frequency or intensity of specific weather phenomena resulting from human-caused changes in climate has proved more difficult and remains an evolving area of research. In any case, the research collectively points toward societal vulnerability as the leading cause of direct economic damage and national-level macroeconomic damage. Research in resilience to environmental extremes is the most recent iteration of the longer winded discussion of weather and climate damage, vulnerability and economic development. This article is focused on studies of direct economic losses from tropical cyclones/hurricanes, floods, tornadoes, and wildfires/bushfires. There is a short section on indirect and macroeconomic damages, but this literature is very much a product of the study of disasters and economic development more generally. A short section is presented on vulnerability, as this is the natural end point for nearly all studies of weather and climate damage.

Reviews of Weather and Climate Damage Trends

Reviews of weather and climate extremes occur in two fashions. First, individual or groups of scholars will work together to review the peer-reviewed literature on weather and climate damage. Often, if not always, these are done with appeal to understanding the state of the science on the relationship between climate change and damage, including extensive assessments of the uncertainties in claims of attribution. Second, large-scale international and national research programs regularly review the climate science literature in producing consensus reports framing the state of the scientific literature on climate change and associated extreme weather events. The reports couch meaning of these findings in terms of the potential for extreme weather to cause damage. These reports are lengthy and mostly technically oriented with specific sections geared toward nontechnical audiences. Their release is often associated with much fanfare. In 1988, the United Nations convened the Intergovernmental Panel on Climate Change (IPCC) to review the climate change science literature and produce consensus statements on the state of the science. IPCC Assessment Reports (AR) consist of several volumes of information, each geared toward a different audience. AR5 is the most recent assessment (IPCC 2014). In 2012, the IPCC released a special report exclusively on extreme events, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, better known as SREX. The report included sections explicitly focused on trends in disaster damages and managing risks associated with climatic extremes. In 1990, the US Congress established the Global Change Research Program (USGCRP), a multiagency research initiative overseen by the White House Office of Science and Technology Policy. The USGCRP produces National Climate Assessment reports on the state of climate change science with a focus on observed and expected changes in the United States. The most recent is USGCRP 2017, released during the first year of the Trump administration. Independent reviews of damage trends began in the 1990s in response to several larger than expected insurance industry losses. Most notable of these is Changnon, et al. 1996. Since then, scholars initiate reviews as means of engaging with public debate about the connection between weather and climate damage and climate change. For instance, Bouwer 2011 is in response to quarrels about attribution of loss. Mohleji and Pielke 2014 sheds light on an ambiguous but commonly referenced data set. Kousky 2014 is in substantiation of preferred policy preferences.

  • Bouwer, L. M. “Have Disaster Losses Increased Due to Anthropogenic Climate Change?” Bulletin of the American Meteorological Society 92.1 (2011): 39–46.

    DOI: 10.1175/2010BAMS3092.1Save Citation »Export Citation »E-mail Citation »

    Bouwer presents a review and analysis of quantitative studies on past increases in weather disaster losses and the role of anthropogenic climate change. Analyses show that although economic losses from weather-related hazards have increased, anthropogenic climate change so far did not have a significant impact on losses from natural disasters. The observed loss increase is caused primarily by increasing exposure and value of capital at risk.

    Find this resource:

  • Changnon, S. A., D. Changnon, E. R. Fosse, D. C. Hoganson, R. J. Roth, Sr., and J. Totsch. Impacts and Responses of the Weather Insurance Industry to Recent Weather Extremes. Final Report to the University Corporation for Atmospheric Research. Mahomet, IL: Changnon Climatologists, 1996.

    Save Citation »Export Citation »E-mail Citation »

    This study is historically significant as an early work documenting the complex relationship between weather and climate damage, the insurance industry, and the atmospheric sciences. The study reviews losses during 1991–1994 and explores the causes and outcomes. The work’s tone, concerns, and verbiage set the stage of contemporary debate. The reference section is valuable for a historic perspective on relevant works.

    Find this resource:

  • IPCC. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Edited by C. B. Field, V. Barros, T. F. Stocker, et al. Cambridge, UK, and New York: Cambridge University Press, 2012.

    Save Citation »Export Citation »E-mail Citation »

    The IPCC produced this report, better known as SREX, in response, at least in part, to criticisms of how it handled reporting on damages in AR4. Relevant findings include: increasing exposure of people and economic assets has been the major cause of long-term increases in economic losses from weather and climate related disasters and low-regrets measures provide benefits under current climate and a range of future climate change scenarios.

    Find this resource:

  • IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Edited by R. K. Pachauri and L. A. Meyer. Geneva, Switzerland: IPCC, 2014.

    Save Citation »Export Citation »E-mail Citation »

    This report synthesizes reports by three IPCC working groups. Relevant findings include: low confidence that anthropogenic climate change affected the frequency and magnitude of fluvial floods on a global scale, low confidence that long-term changes in tropical cyclone activity are robust, low confidence in observed global-scale trends in droughts, and high confidence that losses from weather-related disasters increased in recent decades due to increasing exposure of people and economic assets.

    Find this resource:

  • Kousky, C. “Informing Climate Adaptation: A Review of the Economic Costs of Natural Disasters.” Energy Economics 46 (2014): 576–592.

    DOI: 10.1016/j.eneco.2013.09.029Save Citation »Export Citation »E-mail Citation »

    Framed in the context of climate adaptation, this article provides a rather thorough overview of the literature on disaster damage and, specifically, on weather-related economic losses. The work provides discussion of the many ways in which researchers approach the issue of economic losses, such as short-term and long-term impacts.

    Find this resource:

  • Mohleji, S., and R. Pielke Jr. “Reconciliation of Trends in Global and Regional Economic Losses from Weather Events: 1980–2008.” Natural Hazards Review 15.4 (2014).

    DOI: 10.1061/(ASCE)NH.1527-6996.0000141Save Citation »Export Citation »E-mail Citation »

    This study disaggregates global losses from 1980–2008 from a reinsurance data set into regional components and compares this disaggregation to the literature at the regional scale. The authors find that North American, Asian, European, and Australian storms and floods account for 97 percent of the increasing trend in losses over the time period of analysis with US hurricane losses accounting for nearly 60 percent of global losses.

    Find this resource:

  • USGCRP. Climate Science Special Report: Fourth National Climate Assessment, Volume I. Edited by D. J. Wuebbles, D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, and T. K. Maycock. Washington, DC: US Global Change Research Program, 2017.

    Save Citation »Export Citation »E-mail Citation »

    Relevant findings include: the number of “nuisance” tidal floods has increased since the 1960s in several US coastal cities, tornado activity in the United States has become more variable, the incidence of large forest fires in the western United States and Alaska has increased since the early 1980s, and detection and attribution of past changes in tropical cyclone behavior remain a challenge due to the nature of the historical data.

    Find this resource:

Weather and Climate Damage Databases

In the study of weather and climate damage, researchers regularly rely on databases of damage data. There are many such databases, public and private, and several are worth noting for their frequent reference in the literature. The EM-DAT maintained by the Center for Research on the Epidemiology of Disasters (CRED) has a global scope and is a common reference for damage events outside of the United States and in the international disaster relief community. In listing events in the EM-DAT, CRED provides each event with a unique Global Disaster Identifier (GLIDE). GLIDE data is maintained by the Asian Disaster Recovery Center (ADRC) in Japan. The US National Oceanic and Atmospheric Association’s (NOAA) National Centers for Environmental Information (NCEI) maintains a Storm Event Database of weather damage events occurring at various scales and affecting various sectors. The NCEI also maintains a database of weather damage events since 1980 causing $1 billion or more in damage. At times, publicly funded and accessible databases, such as Spatial Hazard Events and Losses Database for the United States, become fee based once public funding commitments end. In more recent years, the (re)insurance industry has played a significant role in the collection and maintenance of damage data. Munich Re and Swiss Re are common sources for data among those with privileged access to it. While the reinsurance firms provide a public interface to their data it is of too high an aggregate level to be of much more than generic use. Risk Frontiers maintains a database, PerilAUS, which is likely the most complete database of Australian damages. There are many proprietary loss databases held by companies in the insurance and reinsurance industry, but these are not readily available for academic research.

Damage Data Quality Studies

One of the more challenging aspects of research on weather and climate damage is the unequal consistency and quality of the data over time. Jarvinen, et al. 1984 describes the history of Atlantic basin hurricane observation and in turn demonstrates the role scientific advancement plays in temporal changes of data completeness and accuracy. An overarching problem in the study of weather and climate damage, or disaster damages more inclusively, is the persistent inconsistency in the criteria used for reporting and inclusion of weather damage events in databases leading to biases in the data. Tschoegl, et al. 2006 and Gall, et al. 2009 provide detailed insight to these data issues in damage databases with Gall, et al. characterizing these shortcomings as biases. United Nations Development Programme 2013 provides a more recent review of the issue, evaluating country-level and regional databases with the expectation that the UNDP can assist in international coordination of standardized data collection. In a study of US flood events and damage Downton, et al. 2005 demonstrates that the inclusion of detailed accounts of relatively minor damage incidences is particularly inconsistent. As well, nations lack a consistent means of quantifying losses, with those responsible for collecting damage estimates piecing together information as they go. The National Research Council 1999 presents an early study of this issue in the context of the United States; yet, the commitment to a framework for collecting and recording damage never really materialized beyond the agreement that one was needed. Historically, the United States has relied on the insurance industry for the collection and reporting of damage data using various estimating approaches to convert insured damages into direct damages. These methods have more recently become the target of debate, with the premise that changing the assumptions about how insured damages convert to direct damages may reveal new insight into damage trends. Smith and Katz 2013 employs a factoring method of converting insured losses into direct losses with various assumptions about insurance penetration over time and space. Even so, the findings concur with those of previous researchers who believe that there is likely persistent underestimation in the damage data the further back in time one goes.

  • Downton, M. W., J. Z. B. Miller, and R. Pielke, Jr. “Reanalysis of U.S. National Weather Service Flood Loss Database.” Natural Hazards Review 6.1 (2005): 13–22.

    DOI: 10.1061/(ASCE)1527-6988(2005)6:1(13)Save Citation »Export Citation »E-mail Citation »

    The study provides a reanalysis of data maintained in the Storm Events database from 1926–2000. The authors find that estimates for individual flood events are often inaccurate, but when estimates from many events are aggregated the errors become proportionately smaller. They also report that losses for larger events tend to be more accurate than smaller events and that small flood loss events often go unreported.

    Find this resource:

  • Gall, M., K. A. Borden, and S. L. Cutter. “When Do Losses Count? Six Fallacies of Natural Hazard Loss Data.” Bulletin of the American Meteorological Society 90.6 (2009): 799–809.

    DOI: 10.1175/2008BAMS2721.1Save Citation »Export Citation »E-mail Citation »

    This study identifies biases within disaster loss databases but does not study data quality or accuracy within the databases. The authors illustrate biases in the EM-DAT, NATHAN, SHELDUS, and the National Weather Service’s Storm Events. They identify six general biases: hazard bias, temporal bias, threshold bias, accounting bias, geographic bias, and systemic bias. The authors note a lack of transparency in the NCEI billion-dollar database.

    Find this resource:

  • Jarvinen, B. R., C. J. Neumann, and M. A. S. Davis. A Tropical Cyclone Data Tape for the North Atlantic Basin, 1886–1983: Contents, Limitations, and Uses. NOAA Technical Memorandum No. NWS-NHC-22. 1984.

    Save Citation »Export Citation »E-mail Citation »

    This technical report establishes the foundation for understanding the official record of US hurricane data, better known as HURDAT. Through a scientific history of data observations, the authors describe how the data has changed over time and the limitations in its accuracy and completeness.

    Find this resource:

  • National Research Council. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: National Academies Press, 1999.

    Save Citation »Export Citation »E-mail Citation »

    Stirred by several large US weather damage events in the 1990s, this work represents an early national-level effort to understand the economic costs of disasters. The work focuses on the United States and finds that a standard method of data collection does not exist and makes recommendations for a framework of evaluation.

    Find this resource:

  • Smith, A. B., and R. W. Katz. “US Billion-Dollar Weather and Climate Disasters: Data Sources, Trends, Accuracy and Biases.” Natural Hazards 67 (2013): 387–410.

    DOI: 10.1007/s11069-013-0566-5Save Citation »Export Citation »E-mail Citation »

    The study outlines the methodology for the US NCEI database of “Billion-Dollar Disasters” and embedded uncertainty and biases. The methodology uses a factor approach to account for limits in insurance penetration and convert from insured losses to total direct losses. The authors note an increasing trend in annual aggregate losses in the frequency of billion-dollar disasters. The net effect of all biases is an underestimation of average loss.

    Find this resource:

  • Tschoegl, L., R. Below, and D. Guha-Sapir. An Analytical Review of Selected Data Sets on Natural Disasters and Impacts. UNDP/CRED Workshop on Improving Compilation of Reliable Data on Disaster Occurrence and Impact, April 2–4, 2006, Bangkok, Thailand. Brussels: CRED, 2006.

    Save Citation »Export Citation »E-mail Citation »

    This study provides a non-exhaustive although rather thorough review of the world’s disaster databases, notes the strengths and weaknesses of each, and draws general conclusions about the state of disaster data collection and reporting. Databases reviewed cover various geographic areas, including international, national, regional, sub-national, and event specific. Conclusions of note include the fundamental differences in the definition of disaster events and a lack of methodological transparency in database creation.

    Find this resource:

  • United Nations Development Programme. A Comparative Review of Country-Level and Regional Disaster Loss and Damage Databases. New York: Bureau for Crisis Prevention and Recovery, 2013.

    Save Citation »Export Citation »E-mail Citation »

    This report analyzes fifty-seven disaster loss and damage databases covering national, regional, and subregional levels. It documents UNDP’s role in the institutionalization of such systems and examines all known, publicly accessible regional and country-level databases’ contents. The review identifies a number of issues with the databases with respect to completeness and currency, quality control, and accessibility. The report makes a number of recommendations for improvement.

    Find this resource:

Example of a Weather and Climate Damage Debate

Debate about the cause of decadal-scale variability in Atlantic hurricane frequency takes place deep within the details of hurricane data but gives rise to public debates about the impacts of climate change on weather and climate damages. The apparent variability in the observational record means that truncating the data at different points result in the (dis)appearance of trends in activity and damages. The 1970s were relatively inactive while 2004 and 2005 were exceptionally active. As a result, analyses of damage or activity trends beginning in 1970 and ending in 2005 necessarily show an upward trajectory. With more than 3,000 citations, Emanuel 2005a is one of the most widely cited scientific articles linking climate change, hurricane activity, and damage and emphasizes the 1970–2005 time period. The ensuing critique Landsea 2005 argues that the analytical methods did not account for the decadal variability; Pielke 2005 argues that damage record trends do not reflect the article’s main finding of increased hurricane “destructiveness.” In reply, Emanuel 2005b maintains, “a global-warming signal is now emerging in records of hurricane activity.” Emanuel’s truncated data resurfaced in Kunkel, et al. 2013, eliciting a similar objection by Landsea 2015 with the additional concern about the continued use of the very active 2005 season as an endpoint for trend analyses, disregarding hurricane activity since then. In their reply, Kossin and colleagues (Kossin, et al. 2015) invoked the peer-reviewed literature as a more authoritative source of data than the official reporting agency. They also suggested that an increasing trend in truncated data could not be inferred to mean anything about the entire data set, which is concurrent with finding no long-term trends.

  • Emanuel, K. “Increasing Destructiveness of Tropical Cyclones over the Past 30 Years.” Nature 436 (2005a): 686–688.

    DOI: 10.1038/nature03906Save Citation »Export Citation »E-mail Citation »

    This article presents a hurricane activity index, Power Dissipation Index, relates wind speed, sea surface temperature (SST), and storm lifetime. The work shows the index increasing since the mid-1970s and argues that storms are becoming increasingly destructive. The work was released a month before the Hurricane Katrina disaster in New Orleans, Louisiana, and quickly became a popular reference for linking hurricane losses to climate change.

    Find this resource:

  • Emanuel, K. “Emanuel Replies.” Nature 438.7071 (2005b): E13.

    DOI: 10.1038/nature04427Save Citation »Export Citation »E-mail Citation »

    Emanuel defends truncation of the data on the premise that the point is moot because the SST record serves as a better proxy of hurricane strength than does the hurricane record. He defends the inference that storms are more destructive on the premise that the basin wide record has more data than the subset of landfalling events.

    Find this resource:

  • Kossin, J. P., T. R. Knutson, K. A. Emanuel, T. R. Karl, K. E. Kunkel, and J. J. O’Brien. “Reply to ‘Comment on “Monitoring and Understanding Trends in Extreme Storms: State of Knowledge.”’ Bulletin of the American Meteorological Society (2015).

    DOI: 10.1175/BAMS-D-14-00261.1Save Citation »Export Citation »E-mail Citation »

    In their reply to Landsea, the authors note that their truncation of the data to 2005 is consistent with the peer-reviewed literature updating the hurricane time series. As well, conclusion of a robust increasing trend since 1970 that cannot be used to infer long term trends in the record “fundamentally concurs” with Landsea’s argument of no long-term trends over the hurricane record since 1900.

    Find this resource:

  • Kunkel, K. E., T. R. Karl, H. Brooks, et al. “Monitoring and Understanding Trends in Extreme Storms: State of Knowledge.” Bulletin of the American Meteorological Society 94.4 (2013): 499–514.

    DOI: 10.1175/BAMS-D-11-00262.1Save Citation »Export Citation »E-mail Citation »

    The authors argue that robust detection of century-scale trends in Atlantic and western North Pacific tropical cyclone (TC) activity is constrained by data quality and epistemic uncertainty, but that observed trends are robust since the satellite era (i.e., 1960s). The work illustrates an increasing trend in TC power dissipation from 1970–2005, but argues that the time period is too short for conclusions about long-term trends in TC activity.

    Find this resource:

  • Landsea, C. W. “Hurricanes and Global Warming.” Nature 438 (2005): E11–E12.

    DOI: 10.1038/nature04477Save Citation »Export Citation »E-mail Citation »

    This critique takes issue with three aspects of Emanuel’s methodology, challenging the validity of the author’s findings. First, the data smoothing method is not applied to the entire data set. Second, the method of accounting for known bias in the historical record misconstrues the extent of the bias. Third, the study does not consider the impacts of multi-decadal variability in hurricane activity on the results of the analysis.

    Find this resource:

  • Landsea, C. W. “Comment on ‘Monitoring and Understanding Trends in Extreme Storms: State of Knowledge.’” Bulletin of the American Meteorological Society (2015).

    DOI: 10.1175/BAMS-D-13-00211.1Save Citation »Export Citation »E-mail Citation »

    Landsea critiques the decision of Kunkel, et al. 2013 to use TC data beginning in the 1970s, a period of pronounced TC inactivity, and ending in 2005, a number of years prior to the article’s submission. Variation in activity since the 1970s accounts for the increasing trends observed by Kunkel, et al. Landsea argues that the whole data series, 1900–2014, illustrates no long-term century-scale increase in US hurricane frequencies.

    Find this resource:

  • Pielke Jr., R. “Are There Trends in Hurricane Destruction?” Nature 438 (2005): E11.

    DOI: 10.1038/nature04426Save Citation »Export Citation »E-mail Citation »

    The economic loss data does not support the conclusion that storms are more “destructive” but that wealth and population is increasingly concentrated in coastal areas. In turn, if the index accurately indicates destructiveness then the trend identified by Emanuel could be an artifact of methods or if the trend Emanuel identifies is an accurate reflection of trends in storm characteristics then the index is a weak indicator of hurricane destructiveness.

    Find this resource:

Modeled Damages

Challenges in data quality and availability, emergency management needs, and the changing technological demands and expectations of decision-makers gave rise to a powerful industry in catastrophe modeling that is tightly bound to the world’s financial infrastructure. Clark 1986 is generally cited as one of the first damage model analyses used in the insurance industry. Conventional wisdom is that the industry had little interest in Clark’s models, believing that their loss estimates were far too high. However, the industry eagerly adopted them after losses from Hurricane Hugo in 1989 and Hurricane Andrew in 1992 evidenced the potential for multibillion-dollar losses along the US coast. Whitehead 1997 introduces the political issues that have plagued the science-insurance-society relationship ever since adoption of the models. Of primary concern is the proprietary nature of the models and balancing power between industry and the public. The models are now widely used by industry and others to provide estimates of “real risk” on which to make any number of decisions. Grossi and Kunreuther 2005 is a notable source for a layperson’s introduction to catastrophe modeling and the viewpoints of its proponents. Catastrophe modeling can also be considered in a far larger context of uses and abuses of using stochastic modeling of open systems for decision-making. Oreskes, et al. 1994 reviews some of the concerns around interpreting model results, as it is nearly impossible to judge model results for accuracy. Merz, et al. 2010 provides a rather frank discussion of this difficulty as well in the context of modeling flood damage. So difficult is the task that few actually try, though Merz and colleagues believe that more effort in the research community should be put toward understanding the model output and provide a means of doing so. The difficulty in assessing catastrophe model results for accuracy enables creative and diverse means of estimating future losses. Jewson, et al. 2009 is notable for its dramatic impact on the insurance industry’s methods of calculating risk. Namely, the industry moved from estimating risk based on statistical relationships evident in past events toward assumed statistical relationships of events in the future. A Pulitzer Prize–winning series of newspaper articles, St. John 2010 documents how the political power of industry interest and scientific experts creating the models is apparent in the extent to which the models are relied upon to make decisions with rather significant impacts on the public’s economic stability.

  • Clark, K. M. “A Formal Approach to Catastrophe Risk Assessment and Management.” Proceedings of the Casualty Actuarial Society 73.140 (1986): 69–92.

    Save Citation »Export Citation »E-mail Citation »

    This work is considered the pioneer work in applying Monte Carlo modeling methods to understanding natural disaster losses and meaning for the insurance industry.

    Find this resource:

  • Grossi, P., and H. Kunreuther. Catastrophe Modeling: A New Approach to Managing Risk. Boston: Springer, 2005.

    DOI: 10.1007/b100669Save Citation »Export Citation »E-mail Citation »

    This work is a go-to primer on modeling disaster losses and the insurance industry.

    Find this resource:

  • Jewson, S., E. Bellone, T. Laepple, et al. “Five Year Prediction of the Number of Hurricanes That Make U.S. Landfall.” In Hurricanes and Climate Change. Edited by J. B. Elsner and T. H. Jagger, 73–99. New York: Springer-Verlag, 2009.

    DOI: 10.1007/978-0-387-09410-6_5Save Citation »Export Citation »E-mail Citation »

    This book chapter outlines a methodology for creating a hypothetical catalogue of hurricane events for catastrophe modeling based on theories for how hurricanes will behave in the future. These types of models are known as “near-term” models and claim to project hurricane activity over a five-year period.

    Find this resource:

  • Merz, B., H. Kreibich, R. Schwarze, and A. Thieken. “Assessment of Economic Flood Damage.” Natural Hazards and Earth System Sciences 10 (2010): 1697–1724.

    DOI: 10.5194/nhess-10-1697-2010Save Citation »Export Citation »E-mail Citation »

    This study provides a review of the literature relevant to flood damage assessment modeling including a comparison of common, publicly owned models. The authors review present challenges in the data quality of observed flood losses and the problems this poses to judging the quality of modeled damage assessments. The authors recommend ways forward for the research community, particularly in the area of improving model validation and uncertainty analyses.

    Find this resource:

  • Oreskes, N., K. Shrader-Frechette, and K. Belitz. “Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences.” Science 263.5147 (1994): 641–646.

    DOI: 10.1126/science.263.5147.641Save Citation »Export Citation »E-mail Citation »

    This highly cited article articulates the inherent problems in verification and validation of modeling geophysical phenomena over long time scales.

    Find this resource:

  • St. John, P. Article series. Paige St. John of Sarasota Herald-Tribune. 2010.

    Save Citation »Export Citation »E-mail Citation »

    A series of Pulitzer Prize–winning investigative journalism articles detailing the politics embedded in estimating and managing Florida hurricane damages as well as the impacts of this dynamic on society. The series includes a discussion of the challenges near-term catastrophe modeling presents to Florida homeowners.

    Find this resource:

  • Whitehead, S. “Risky Business: Proprietary Modeling and Insurance Ratemaking.” Journal of Insurance Regulation 5.3 (1997): 372–381.

    Save Citation »Export Citation »E-mail Citation »

    As the insurance industry adopted catastrophe modeling to estimate losses, the Journal of Insurance Regulation published a special issue on related social and scientific issues. This article is one of the first, if not the first, peer-reviewed publications voicing concern about the imbalance of power between the market and the public that would occur if regulators accepted the models for insurance ratemaking.

    Find this resource:

Normalization Studies

In the quest for understanding the role of societal change in increasing weather and climate damages, a large, diverse, and robust body of literature “normalizes” damages over time using different methods to adjust for societal changes: inflation, wealth, and population. The goal of normalization is to estimate the damage caused by a historic event if it were to happen in current times; it enables an apples to apples comparison of losses over time. Since the first such normalization study was published in 1998, there have been dozens to apply the methodology. Normalization studies are dependent on the availability of historic data and thus tend to be performed on industrialized nations. For instance, Pielke, et al. 2008 normalizes US hurricane damages. Crompton and McAneney 2008 normalizes Australian weather-related damages. Barredo 2009 normalizes European flood losses. Simmons, et al. 2013 normalizes US tornado damage. However, there is a growing collection of studies from emerging economies. Raghavan and Rajesh 2003 normalizes tropical cyclone damages from India. Chang, et al. 2009 normalizes tropical cyclone losses in China. Zhang, et al. 2009 normalizes flood losses in Korea. Crompton, et al. 2010 provides a normalization study of bushfires in Australia to which Nicholls 2011 provides a critique: they do not account for fine-scale socioeconomic differences (e.g., between neighborhoods) and the influence of structural mitigation measures on more recent damages. Neumayer and Barthel 2011 devises a normalization method that better accounts for small-scale spatiotemporal changes in socioeconomics. Yet, the authors’ results are much the same as the results of all other normalization studies: the vast majority of increasing weather and climate damages are clearly the result of changes in social and economic conditions.

  • Barredo, J. I. “Normalised Flood Losses in Europe: 1970–2006.” Natural Hazards and Earth System Sciences 9 (2009): 97–104.

    DOI: 10.5194/nhess-9-97-2009Save Citation »Export Citation »E-mail Citation »

    This normalizes flood losses in Europe to 2006 societal conditions. The author uses data from the EM-DAT and the NATHAN. The author removed inter-country price differences by adjusting losses for purchasing power parities (PPP). Results of the normalization show no detectable sign of human-induced climate change.

    Find this resource:

  • Chang, H., J. Franczyk, and C. Kim. “What Is Responsible for Increasing Flood Risks? The Case of Gangwon Province, Korea.” Natural Hazards 48 (2009): 339–354.

    DOI: 10.1007/s11069-008-9266-ySave Citation »Export Citation »E-mail Citation »

    This study normalizes Korean flood losses and finds that increasing losses are attributable to changes in land use patterns and increasing urbanization of flood plain areas.

    Find this resource:

  • Crompton, R. P., and K. J. McAneney. “Normalised Australian Insured Losses from Meteorological Hazards: 1967–2006.” Environmental Science and Policy 11.5 (2008): 371–378.

    DOI: 10.1016/j.envsci.2008.01.005Save Citation »Export Citation »E-mail Citation »

    This study normalizes weather-related insured losses to 2006 societal conditions. The authors use changes in the number and average nominal value of dwellings over time, where nominal dwelling values exclude land value. In the case of tropical cyclones, they also include a factor adjusting for the influence of building mitigation. Normalized results exhibit no obvious trend over time that might be attributed to other factors, including human-induced climate change.

    Find this resource:

  • Crompton, R. P., K. J. McAneney, K. Chen, R. A. Pielke, and K. Haynes. “Influence of Location, Population, and Climate on Building Damage and Fatalities Due to Australian Bushfire: 1925–2009.” Weather, Climate, and Society 2.4 (2010): 300–310.

    DOI: 10.1175/2010WCAS1063.1Save Citation »Export Citation »E-mail Citation »

    This study normalizes Australian wildfire damage and loss of life from 1925–2009 to 2008/2009 conditions based on state or territory historic dwelling and population data. The authors find relationships between normalized building damage and the El Niño–Southern Oscillation and Indian Ocean dipole phenomena. However, they find no evidence of an anthropogenic climate change signal in the normalized data.

    Find this resource:

  • Neumayer, E., and F. Barthel. “Normalizing Economic Loss from Natural Disasters: A Global Analysis.” Global Environmental Change 21.1 (2011): 13–24.

    DOI: 10.1016/j.gloenvcha.2010.10.004Save Citation »Export Citation »E-mail Citation »

    This study introduces an alternative method for normalizing wealth in disaster damages that accounts for differences in wealth across space at any given point of time. However, the authors find that their method overcomes the spatial “problem in theory, but faces many more problems in its empirical application.” Using both the common and alternative methodologies, results do not find significant trends in normalized damages from 1980–2009 globally, regionally, or by event.

    Find this resource:

  • Nicholls, N. “Comments on ‘Influence of Location, Population, and Climate on Building Damage and Fatalities due to Australian Bushfire: 1925–2009.’” Weather, Climate, and Society 3.1 (2011): 61–62.

    DOI: 10.1175/WCAS-D-10-05001.1Save Citation »Export Citation »E-mail Citation »

    This essay provides a good example of common critique of normalization studies. The author argues that methods presented by Crompton, et al. 2010 do not account for spatiotemporal rates of change (e.g., urbanization) and building mitigation or other behavioral changes that may have decreased damage in more recent years, thereby dampening the potential for identifying a climate change signal in the damage data.

    Find this resource:

  • Pielke Jr., R. A., J. Gratz, C. W. Landsea, D. Collins, M. A. Saunders, and R. Musulin. “Normalized Hurricane Damage in the United States: 1900–2005.” Natural Hazards Review 9.1 (2008): 29–42.

    DOI: 10.1061/(ASCE)1527-6988(2008)9:1(29)Save Citation »Export Citation »E-mail Citation »

    This paper normalizes mainland US hurricane damage from 1900–2005 to 2005 values using methods that provide for changes in inflation and wealth at the national level and changes in population and housing units at the coastal county level. There is no remaining trend of increasing absolute damage in the normalized data set. This is a commonly referenced method. The work is in the process of being updated to reflect recent data changes to 2017.

    Find this resource:

  • Raghavan, S., and S. Rajesh. “Trends in Tropical Cyclone Impact: A Study in Andhra Pradesh, India.” Bulletin of the American Meteorological Society 84 (2003): 635–644.

    DOI: 10.1175/BAMS-84-5-635Save Citation »Export Citation »E-mail Citation »

    This article analyzes cyclones affecting the state of Andhra Pradesh, India, in the last quarter century by normalizing cyclone damage for economic and demographic factors. Results show that greater vulnerability is attributable mainly to socioeconomic factors and not to any increase in frequency or intensity of cyclones. It is one of the rare articles employing these methods in nations with less developed economies.

    Find this resource:

  • Simmons, K. M., D. Sutter, and R. Pielke Jr. “Normalized Tornado Damage in the United States: 1950–2011.” Environmental Hazards 12.2 (2013): 132–147.

    DOI: 10.1080/17477891.2012.738642Save Citation »Export Citation »E-mail Citation »

    This study normalizes US tornado damage from 1950 to 2011. Using several methods, results demonstrate a sharp decline in damage corresponding with a decline in reported frequency of the most intense tornadoes since 1950. The authors note limitations in historical data quality but also that results suggest some part of the decline may reflect actual changes in tornado incidence, beyond changes in reporting practices.

    Find this resource:

  • Zhang, Q., L. Wu, and Q. Liu. “Tropical Cyclone Damages in China: 1983–2006.” Bulletin of the American Meteorological Society 90.4 (2009): 489–495.

    DOI: 10.1175/2008BAMS2631.1Save Citation »Export Citation »E-mail Citation »

    This study normalizes direct economic losses in China. The results show that no trend is found after losses are scaled with the annual total GDP of China and the annual GDP per capita, suggesting that the upward trend in direct economic losses is primarily a result of Chinese economic development.

    Find this resource:

Indirect and Macroeconomic Damage

In considering indirect and macroeconomic damage, one must consider the literature on this topic as it broadly relates to disasters rather than specifically as it relates to weather and climate damage studies. That said, many of the world’s natural disasters are linked to meteorological hazards, and the literature covering indirect and macroeconomic damage gleans its knowledge largely from case studies of weather and climate damage events. Researchers widely accept that disaster events cause economic impacts to communities and nations well beyond direct damage to property. However, researchers are somewhat divided as to the extent of impact on economies and whether or not the effects are cumulatively positive or negative, over different temporal and spatial scales. A common reference point for this debate is Skidmore and Toya 2002, which argues that disaster losses can have long-term positive effects on economies. The review Kellenberg and Mobarak 2011 provides a closer look at some of the nuances present in scholarly debates about the effects of disasters on economies, including that presented by Skidmore and Toya 2002. One of the difficulties involved in studying indirect and macroeconomic damage is that defining the scope of analysis can be a bit ambiguous. Rose 2004 aims to gather the research community on the same page by providing definitions for common terms and concepts. Benson and Clay 2004 emphasizes the importance of context, as different social and political environments influence the ways in which extreme events affect economies. Consider, for instance, the discussion in Cavallo, et al. 2013 that some disasters spur political revolutions resulting in rather long-term economic affects. Cavallo and Noy 2009 provides a review indicating that it appears there is a general agreement that macroeconomic impacts are more severely experienced by developing countries as compared to developed ones. Nevertheless, Noy 2009 notes that countries that are similar economically do not experience disasters in the same ways. Socioeconomic factors such as literacy rate contribute to the severity of the impacts.

  • Benson, C., and E. J. Clay. Understanding the Economic and Financial Impacts of Natural Disasters. Disaster Risk Management Series No. 4. Washington DC: World Bank, 2004.

    DOI: 10.1596/0-8213-5685-2Save Citation »Export Citation »E-mail Citation »

    A commonly cited study demonstrating the short- and long-term economic impacts of disasters in developing countries. The work emphasizes a qualitative approach in methods as means of considering the unique “pathways” through which extreme geophysical events affect an economy.

    Find this resource:

  • Cavallo, E., S. Galiani, I. Noy, and J. Pantano. “Catastrophic Natural Disasters and Economic Growth.” Review of Economics and Statistics 95.5 (2013): 1549–1561.

    DOI: 10.1162/REST_a_00413Save Citation »Export Citation »E-mail Citation »

    Using several case studies, the authors study the average causal impact of catastrophic natural disasters on economic growth. They find that only the largest disasters have a negative effect on economic growth but that these results stem from specific events resulting in political revolutions. The authors control for these political changes and find that even extremely large disasters do not display significant effects on economic growth.

    Find this resource:

  • Cavallo, E., and I. Noy. The Economics of Natural Disasters: A Survey. IDB Working Paper Series No. IDB-WP-124. Inter-American Development Bank, 2009.

    Save Citation »Export Citation »E-mail Citation »

    This report reviews determinants of the direct effects of disasters and distinguishes between short- and long-run indirect effects. The paper examines some policy issues and makes projections about future disasters in the context of climate change.

    Find this resource:

  • Kellenberg, D., and A. M. Mobarak. “The Economics of Natural Disasters.” Annual Review of Resource Economics 3.1 (2011): 297–312.

    DOI: 10.1146/annurev-resource-073009-104211Save Citation »Export Citation »E-mail Citation »

    This review provides an overview of the literature on the ways nations are economically affected by natural disasters with an emphasis on the importance of context for understanding affects and the potential for success of risk mitigation policies.

    Find this resource:

  • Noy, I. “The Macroeconomic Consequences of Disasters.” Journal of Development Economics 88.2 (2009): 221–231.

    DOI: 10.1016/j.jdeveco.2008.02.005Save Citation »Export Citation »E-mail Citation »

    This article shows that not only do natural disasters have an adverse impact on the macroeconomy in the short run but also that developing countries and smaller economies face much larger output declines following disasters than do developed countries or bigger economies. Several socioeconomic factors, such as literacy rate and per capita, contribute to explaining these macroeconomic findings.

    Find this resource:

  • Rose, A. “Economic Principles, Issues, and Research Priorities in Hazard Loss Estimation.” In Modeling Spatial and Economic Impacts of Disasters. Edited by Y. Okuyama and S. Chang, 13–36. Berlin: Springer, 2004.

    DOI: 10.1007/978-3-540-24787-6_2Save Citation »Export Citation »E-mail Citation »

    With an economic lens, this book chapter provides clarification of several economic terms, economic models, and research-related topics (e.g., resiliency) relevant to the study of disaster damages.

    Find this resource:

  • Skidmore, M., and H. Toya. “Do Natural Disasters Promote Long-Run Growth?” Economic Inquiry 40.4 (2002): 664–687.

    DOI: 10.1093/ei/40.4.664Save Citation »Export Citation »E-mail Citation »

    This article uses cross-country data to examine the long-run relationships among disaster risk, investment decisions, total factor productivity, and economic growth. The analysis shows that climatic disasters are positively correlated with economic growth and human capital investment, as well as providing impetus to update the capital stock and adopt new technologies improving total factor productivity. Geologic disasters are negatively correlated with growth.

    Find this resource:

Vulnerability

People engage in weather and climate damage research for different political and scientific reasons, but they collectively point toward societies’ growing vulnerability to extreme weather as the cause of damages. The famous geographer Gilbert White (White 1945) brought initial attention to this issue through his study of the role that land use and risk mitigation infrastructure (e.g., levees) play in weather damages. This initial framing of vulnerability as a product of exposed infrastructure and the movement of populations created the foundation for decades of research in hazards and losses. Gaillard 2010 covers the history of the academic understanding of disasters steming from White’s study and a new vulnerability paradigm developed in the late 20th century advocating for deeper consideration of historic and social causes of loss. Wisner, et al. 2004 is a classic treatment outlining this social approach to vulnerability that uses examples from all over the globe. The more socially focused vulnerability paradigm (as compared to White’s more technocratic paradigm) introduces the reader to a rich collection of stories about national histories, oppressive forces, and scandalous politics. Steinberg 2006 is well regarded for the author’s narration of these issues in the American South. The two trajectories in vulnerability studies create two generally separate efforts of damage reduction: structural mitigation and support for marginalized populations. The effectiveness of structural mitigation on reducing economic loss is not well studied in part due to the time scales required. Benson and Twigg 2004 is the often cited authority on the potential of mitigation to reduce damages. Sadowski and Sutter 2008 provides a theoretical approach to estimating the benefits of investment in structural mitigation based on the premise that people invest in mitigation post disaster. Sociology and geography have merged in the area of disaster research, creating indices for identifying populations most vulnerable to disaster events. Cutter, et al. 2003 creates the Social Vulnerability Index (SoVI), which is highly referenced in the US literature. Charged by the World Bank to identify the world’s most vulnerable, Dilley, et al. 2005 compiles geophysical, economic, and social data to designate disaster “hot spots.” Kellenberg and Mobarak 2008 challenges the conventional wisdom that advancing economic growth necessarily results in less vulnerable populations and damage. These authors show that reduction in damages occurs only after a certain level of income is obtained, and, therefore, reductions in damages are achieved by simultaneously addressing social and structural vulnerabilities. Puerto Rico’s experience with Hurricane Maria (2017) is a recent example of the combined roles structural and social vulnerabilities play in weather and climate damage (e.g., Zorilla 2017).

  • Benson, C., and J. Twigg. “Measuring Mitigation”: Methodologies for Assessing Natural Hazard Risks and the Net Benefits of Mitigation—a Scoping Study. Geneva, Switzerland: International Federation of Red Cross and Red Crescent Societies, 2004.

    Save Citation »Export Citation »E-mail Citation »

    Beginning with several indications that mitigation efforts reduce damages from extreme geophysical events, this report facilitates the development of tools to analyze and measure the costs and benefits of mitigation. The authors explore cost-benefit analysis, environmental impact assessment, and related methodologies as potential opportunities to better understand the merits and drawbacks of mitigation practices.

    Find this resource:

  • Cutter, S. L., B. J. Boruff, and W. L. Shirley. “Social Vulnerability to Environmental Hazards.” Social Science Quarterly 84.2 (2003): 242–261.

    DOI: 10.1111/1540-6237.8402002Save Citation »Export Citation »E-mail Citation »

    This work presents the methodology and results to create an index of social vulnerability to environmental hazards, SoVI. The SoVI is widely referenced especially in regards to studies of vulnerability in the United States.

    Find this resource:

  • Dilley, M., R. S. Chen, U. Deichmann, A. L. Lerner-Lam, and M. Arnold.Natural Disaster Hotspots: A Global Risk Analysis. Washington, DC: World Bank, 2005.

    DOI: 10.1596/0-8213-5930-4Save Citation »Export Citation »E-mail Citation »

    This study provides an analysis of areas most prone to disasters in respect to probability of extreme geophysical event population vulnerability as characterized by socioeconomic factors. The work creates a depiction of “hot spots” of high disaster risk areas.

    Find this resource:

  • Gaillard, J. C. “Vulnerability, Capacity and Resilience: Perspectives for Climate and Development Policy.” Journal of International Development 22 (2010): 218–232.

    DOI: 10.1002/jid.1675Save Citation »Export Citation »E-mail Citation »

    Provides a succinct review of the literature on the concepts of vulnerability, capacity, and resilience. The author then critiques current approaches to disaster risk reduction, arguing that efforts are too strongly focused on the technocratic hazard paradigm and give too little attention to the more socially inclusive vulnerability paradigm.

    Find this resource:

  • Kellenberg, D. K., and A. M. Mobarak. “Does Rising Income Increase or Decrease Damage Risk from Natural Disasters?” Journal of Urban Economics 63 (2008): 788–802.

    DOI: 10.1016/j.jue.2007.05.003Save Citation »Export Citation »E-mail Citation »

    Counter to the expectation that rising incomes increase disaster risk, this study shows that the decline in disaster risk occurs only after a certain income level is reached.

    Find this resource:

  • Sadowski, N. C., and D. Sutter. “Mitigation Motivated by Past Experience: Prior Hurricanes and Damages.” Ocean and Coastal Management 51.4 (2008): 303–313.

    DOI: 10.1016/j.ocecoaman.2007.09.003Save Citation »Export Citation »E-mail Citation »

    This study proposes a new test of the effectiveness of mitigation using a past landfalling hurricane as a proxy. The authors find that a prior landfalling hurricane—and by implication mitigation—can significantly reduce damages, by the equivalent of about a one category reduction on the Saffir–Simpson scale of hurricane intensity.

    Find this resource:

  • Steinberg, T. Acts of God: The Unnatural History of Natural Disaster in America. New York: Oxford University Press, 2006.

    Save Citation »Export Citation »E-mail Citation »

    This book discusses the unequal ways extreme geophysical events affect marginalized populations in the context of political power by decision-makers. The author argues that framing disasters as a chance outcome of natural processes has enabled politicians and business figures to skirt responsibility for disaster outcomes.

    Find this resource:

  • White, G. F. Human Adjustment to Floods. Research Paper 29. Chicago: University of Chicago, 1945.

    Save Citation »Export Citation »E-mail Citation »

    This work originates with White’s dissertation at the University of Chicago. It is most known for the following statement: “floods are acts of God, but flood losses are largely acts of man. Human encroachment upon floodplains of rivers accounts for the high annual total of flood losses.” While the sentiment may seem obvious in today’s research era, its articulation, for better or worse, shaped decades of disaster research and disaster risk reduction policies.

    Find this resource:

  • Wisner, B., P. M. Blaikie, T. Cannon, and I. Davis. At Risk: Natural Hazards, People’s Vulnerability and Disasters. 2d ed. London: Routledge, 2004.

    Save Citation »Export Citation »E-mail Citation »

    This is a classic work outlining the range of social attributes contributing to a community risk of natural disasters. The second edition appears more frequently in references. The first edition was by the same group of authors with Blaikie as lead.

    Find this resource:

  • Zorilla, C. D. “The View from Puerto Rico—Hurricane Maria and Its Aftermath.” New England Journal of Medicine 377 (2017): 1801–1803.

    DOI: 10.1056/NEJMp1713196Save Citation »Export Citation »E-mail Citation »

    In this personal account of tending to the obstetrics ward of a hospital during Hurricane Maria, a physician tells of the difficulty declining infrastructure and socioeconomic conditions presented for weathering the storm and its impacts.

    Find this resource:

Journals

Several peer-reviewed scholarly journals address weather and climate damage, though not as an exclusive focus. Natural Hazards Review, a journal of the American Society of Civil Engineers, maintains an explicit focus on disaster losses and includes research pertaining to understanding and documenting historical losses, and modeling loss potential. The International Journal of Disaster Risk Reduction is a journal of the Global Risk Forum (GRF) Davos, an organization that aims to bridge the gap between science and practice in activities of risk management and climate change adaptation. The journal publishes on a wide range of research efforts aimed at reducing the impact of natural and technological disasters. Environmental Hazards: Human and Policy Dimensions has a broad, international, and interdisciplinary focus on the ways society defines, understands, and manages of all types of hazards. Natural Hazards is a journal of the International Society for the Prevention and Mitigation of Natural Hazards and maintains a focus on technical research aimed enhancing hazard mitigation. Weather and climate damage research also appears in journals geared toward the meteorological community and with a research focus on societal interactions with weather and climate. For instance, Weather, Climate and Societyis a social science journal of the American Meteorological Society and maintains a research focus on the socio-behavioral aspects of society’s interface with weather and climate.

back to top

Article

Up

Down