Hurricane Risk

Of any single weather or climate peril, tropical cyclones constitute the largest annual average loss to the global insurance and reinsurance industry, and in any given year are often the drivers of the largest catastrophic losses to the entire industry. These losses come in the form of payments covering insurance claims, initiated through damage caused by a tropical cyclone’s physical effects. They are thus looked upon within the industry as hugely important perils for study and analysis. This chapter provides an introduction to traditional methods for pricing risk, with an emphasis on hurricanes, and how the catastrophe modeling industry has arisen out of limitations with those traditional methods specifically when looking at extreme, relatively rarely occurring perils that have the potential to cause catastrophic loss.

An approach to assessing the damage potential of tropical cyclones (TCs) is developed using a combination of physical reasoning and results of previous studies. The key TC damage parameters of intensity, size, and translational speed are incorporated into a single index of Cyclone Damage Potential (CDP). The CDP is developed to represent offshore wind, wave, and current damage. Further testing is needed to establish the importance of each TC parameter for onshore wind and coastal surge damage. The CDP is applicable to individual TCs and to seasonal, global, and climatological assessments. Global climatological summaries reveal high damage potential pathways and the dominant contribution of the Northwest Pacific to total global damage potential. Assessing actual impact requires an additional step of combining the CDP with an exposure and vulnerability assessment derived from a range of local factors.

Integrated Kinetic Energy (IKE) is a recently developed metric that measures the destructive potential of tropical cyclones (TCs) by integrating the square of the surface winds across these powerful storms. In this chapter, the previous literature is reviewed to provide insights on the factors that make IKE a desirable metric. IKE complements existing scales and metrics by considering a TC’s entire wind field, in lieu of just focusing on the maximum intensity of a storm. Using a dataset of six-hourly IKE estimates for two decades of North Atlantic TC activity, the climatology of IKE in individual storms is explored, with emphasis on seasonal and spatial variability. The driving mechanisms for IKE variability during the lifetime of a TC are also reviewed to determine which environmental and storm-scale features promote IKE growth. The historical record of IKE can also be aggregated to a seasonal metric, called Track Integrated Kinetic Energy (TIKE), which is shown to offer a comprehensive overview of seasonal TC activity and can be used to explore interannual TC variability over the last two to three decades.

Tropical cyclones (TCs), specifically their higher energy equivalents of hurricanes or typhoons, are the focus of great concern over their destructive impacts on coastal regions; this concern was enhanced as the trio of hurricanes (Harvey, Irma, and Maria) imposed spectacular damage and economic losses to parts of the United States and the Caribbean in 2017. We investigated historical TC events from the Western North Pacific and North Atlantic basins and introduced a new energy-based approach to mapping and spatially assessing TC hazards in both basins. By combining the energy index (EI) simplified from the power dissipation index (PDI) with a weighted density mapping tool, we defined a spatial energy cell which delineated a zone of intense TC energy loss. The energy cell we identified from the TC hazard map represents historical hot spots of TC events with reference to both frequency and intensity. We show that as TCs in Western North Pacific move westward from the source energy cell, energy is dissipated very rapidly over the Philippine land mass forming a dramatic energy discontinuity which we term an energy cliff. The migration of energy cells in the North Atlantic reflects inter-decadal variations of TC activity. Finally, the concept of energy dissipation discussed in this paper could be employed as a basis for the energy-based comparison of the magnitudes of all categories of natural hazards and help illuminate the nature of hazard-impact relationships.

The Tampa Bay area has not been impacted by a direct major hurricane landfall since 1921, but nearly every year the Tampa Bay region suffers effects from tropical storms and weak hurricanes brushing by the area. These weaker storms, like Hurricane Irma in 2017, still create significant damage. A stronger storm would be catastrophic. This chapter draws comparisons between past storms in the Tampa Bay area and elsewhere that have caused death and destruction, and discusses potential ecological, sociological, and human health disasters within the Tampa Bay area during a major hurricane landfall.

The 2015 North Atlantic hurricane season was particularly inactive, this inactivity occurring in the presence of a near-record El Niño, the strongest since 1997. When analyzing large-scale environmental conditions utilizing NCEP/NCAR Reanalysis 2, we show that the Caribbean was particularly inactive under very strong wind shear and positive Omega conditions. While conditions generally were not conducive in the North Atlantic, there were conducive conditions present at specific times and specific locations, and these tended to be when and where we saw tropical cyclone activity. Vorticity in particular showed large intraseasonal variability with the location of the positive vorticity relating to storms such as Ana in May, Claudette in July, multiple storms in August and September, and Joaquin in October. We assess how the active and inactive periods observed during the 2015 hurricane season were related to this month to month atmospheric variability.

Tropical cyclones (TCs) devastate nations around the world. Many different variables influence TC intensification or decay. Near Australia, one of those influences may stem from the arid interior of the landmass. The influences of aerosol optical depth (AOD), sea surface temperature (SST) and upper ocean temperature (UOT) on monthly TC days over eastern Australia and the southwest Pacific Ocean are examined using data from 1985 to 2015. The area experiences TCs in November (Nov) through June with a peak in March. Variables occurring together in time are considered as possible predictors of TC days, as well as lagged relationships between them. Spearman rank correlation tests showcase the significant relationships between all pairs of variables during a variety of months. A Poisson multiple regression model is applied on TC-SST-AOD and TC-UOT-AOD to find the most significant relationships between the variables throughout the season. Four significant models are found without violating statistical assumptions. An increase in Nov AOD and Dec SST leads to a significant increase in Jan TC days. Dec UOTs are found to be negatively related to TC days in Jan. The difference in directions is related to the difference in heating mechanisms associated with the surface conditions and the lower subsurface in environments of relatively higher AOD. Probabilities of monthly days during unfavorable and favorable conditions are found. Low to moderate TC days are expected in Jan when both Nov AOD and Dec SSTs are low. There is a chance of a higher number of Jan TC days in both high Nov AOD and Dec SSTs. This study provides scenarios between the variables to aid in forecasting.

The links between the ability of general circulation models to simulate tropical cyclones and the development of a climate theory of tropical cyclone formation are explored, with an emphasis on the potential of general circulation models (GCMs) and theory for tropical cyclone hazard and risk assessment. While GCMs can now generate a reasonable simulation of the observed tropical cyclone formation rates and intensity distributions, they are very expensive to run. Simpler methods involving statistical relationships between climate variables and tropical cyclone formation have been developed and have been used for hazard assessment, but like other methods used for projections, such as downscaling or GCMs, they do not constitute a theory of tropical cyclone formation. An outline is given of some of the possible characteristics of such a theory and its potential utility for climate science and risk.

Although it is well known that climate change will alter future tropical cyclone characteristics, there have been relatively few studies that have measured global impacts. This paper utilizes new insights about the damage caused by tropical cyclones from Bakkensen and Mendelsohn (J Assoc Env Res Econ 3:555–587, 2016) to update the original methodology of Mendelsohn et al. (Nat Clim Change 2:205–209, 2012). We find that future cyclone losses are very sensitive to both adaptation and development. Future development (higher income) is predicted to sharply reduce future fatalities. However, damage may take two distinct paths. If countries follow the United States and adapt very little, damage is predicted to increase proportionally with income, rising 400% over the century. However, if development follows the remaining OECD countries, which have done a lot of adaptation, future cyclone damage will only increase slightly.

With statistically significant trends suggesting that tropical cyclones are migrating poleward in the Southern Hemisphere, specifically in the South Pacific Ocean basin, it is important to review the current state of knowledge on poleward migrating tropical cyclone activity. Furthermore, given the potential impacts they may have on regions traditionally unaffected by tropical cyclones, review of current residential building practice in Australia is warranted. This chapter highlights the significance of the long-term poleward trends in the Southern Hemisphere and potential mechanisms that are driving the geographical shift. Residential building practice in cyclonic and non-cyclonic regions in Australia is discussed to address existing vulnerabilities and how they can lead to catastrophic impacts. Methods and tools to evaluate tropical cyclone risk as well as future research needs are then discussed in the context of adapting to and mitigating for tropical cyclone activity that may migrate poleward. Finally, the chapter concludes with a summary and some finishing thoughts about the advantages of forming multidisciplinary teams to address the grand challenge of disaster resilience in the built environment in Australia.

The offshore energy industry in the Gulf of Mexico is exposed to substantial hurricane risk. The plausible scenario of the hurricane climate changing in response to climate change could severely impact the industry, yet understanding changes in hurricanes on regional scales is challenging due to the small number of events and high variability. For impacts, loading on facilities is a complex function of wind, waves and ocean currents. To understand future loading scenarios, it therefore becomes necessary to account for these multiple load drivers. An approach is developed to assess future changes to metocean (Metocean is an offshore engineering term used to describe combined meteorological and oceanographic conditions) conditions in hurricane environments using physical modeling that captures relationships between wind, waves, and current. For a set of nine historical Gulf of Mexico hurricanes, the effects of the hurricane wind fields on ocean waves and currents are simulated using analysis winds to drive a wave model and a regional ocean model. The generalized extreme value distribution describes wind, wave height, wave period, and surface ocean current well. In addition, significant wave height is significantly correlated with wave period and wind speed in hurricane environments. The effects of the hurricane wind fields are simulated again with modified hurricane wind fields consistent with future climate scenarios, while keeping the current climate ocean forcing fixed. Under the future scenario of 10% increase in wind speed and 10% reduction in storm size, the distributions shift to higher significant wave heights and longer peak wave periods with the largest proportional increases at the highest percentiles. The higher percentiles show future increases of up to 16% across the metocean variables with significant wave heights seeing the largest proportional increases. Integrating these results with engineering design protocols is anticipated to lead to better planning guidelines that will enable improved design of structures and operating procedures, and minimize environmental and safety risks.

Quantifying the human influence on individual extreme weather events is a new and rapidly developing science. Understanding the influence of climate change on tropical cyclones poses special challenges due to their intensities and scales. We present a method designed to overcome these challenges using high-resolution hindcasts of individual tropical cyclones under their actual large-scale meteorological conditions, counterfactual conditions without human influences on the climate system, and scenarios of increased climate change. Two practical case studies are presented along with a discussion of the conditions and limitations of attribution statements that can be made with this hindcast attribution method.