A Weibull Approach for Improving Climate Model Projections of Tropical Cyclone Wind-Speed Distributions

Tye, Mari R.; Stephenson, David B.; Holland, Greg J.; Katz, Richard W.

doi:10.1175/jcli-d-14-00121.1

Cited by 30 publications

(14 citation statements)

References 48 publications

(60 reference statements)

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“…Given the observations of extreme windstorms, it has been demonstrated that it is necessary to fit a left‐truncated Weibull (LTW) distribution to the set of maximum wind speeds . For a nonnegative truncation parameter, u , the left‐truncated Weibull CDF for wind speeds w is given by

F false(w false| a, b, u false) = 1 - e x p ([], {((), \frac{u}{a})}^{b} - {((), \frac{w}{a})}^{b}) f o r w > u .

…”

Section: Methodsmentioning

confidence: 99%

Windstorm risk assessment for offshore wind farms in the North Sea

Buchana

McSharry

2019

Wind Energy

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The North Sea is becoming increasingly attractive to wind energy developers and investors, with 38 wind farms belonging to five different countries and representing over€35 billion of assets. Concerns about offshore wind turbines being damaged by extreme windstorms pose a challenge to insurers, investors and regulators. Catastrophe modeling can adequately quantify the risk. In this study, a Monte Carlo simulation approach is used to assess the number of turbines that buckle using maximum wind speeds reaching each wind farm. Damage assessment is undertaken for each wind farm using a log‐logistic damage function and a left‐truncated Weibull distribution. The risk to offshore wind power in the North Sea is calculated using an exceedance probability (EP) curve for the portfolio of wind farms. The European Union Solvency II directive requires insurance companies to hold sufficient capital to guard against insolvency. The solvency capital requirement (SCR) is based on a value‐at‐risk measure calibrated to a 99.5% confidence level over a 1‐year time horizon. The SCR is estimated at €0.049 billion in the case of yawing turbines. Simulations are repeated for different climate change scenarios. If wind speeds grow by 5% and the frequency of storms increases by 40%, the SCR is seen to rise substantially to €0.264 billion. Relative to the total value of assets, the SCR is 0.14% compared with 0.08% for European property, confirming that these wind farm assets represent a relatively high risk. Furthermore, climate change could increase the relative SCR to levels as high as 0.75%.

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F false(w false| a, b, u false) = 1 - e x p ([], {((), \frac{u}{a})}^{b} - {((), \frac{w}{a})}^{b}) f o r w > u .

…”

Section: Methodsmentioning

confidence: 99%

Windstorm risk assessment for offshore wind farms in the North Sea

Buchana

McSharry

2019

Wind Energy

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“…It is also too coarse to capture the intensity of the strongest hurricanes (as discussed in Done et al, 2015). Rather than downscaling the NARR data to obtain these small-scale details using dynamical (e.g., Laprise et al, 2008) or statistical (e.g., Tye et al, 2014) methods (which could introduce further uncertainties), we choose to sacrifice the small-scale details of the wind field and peak hurricane intensity for location accuracy of the NARR data. To account for these missing wind extremes, all wind speed values are normalized by the maximum value of wind speed in the data set.…”

Section: Statistical Methodology and Data Descriptionmentioning

confidence: 99%

Demonstrating the Intensive Benefit to the Local Implementation of a Statewide Building Code

Czajkowski

Simmons

Done

2017

Risk Manage Insurance Review

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Ultimately, risk reduction from the implementation of building codes is due to not only the extent of the code as it applies to new construction, but also to the intensity of local adoption and enforcement. It is normally an open question as to how well a code is maintained and enforced at the local level, even for a relatively strong adopted statewide code such as the Florida Building Code. We test the importance of the intensity of building code implementation at the local level for reducing Florida windstorm losses by utilizing Building Code Effectiveness Grading Schedule (BCEGS®) rating data. BCEGS ratings provide a joint assessment of local building code effectiveness in terms of the strength of the adopted codes in addition to how well these adopted codes are enforced. We find that both components provide value in reducing windstorm losses in Florida, with the extent of the statewide code being the dominant effect reducing losses on the order of 72 percent. Although not as substantial in terms of its loss reduction magnitude, intensively implementing building codes at the local level by ensuring codes are properly administered and enforced at this scale provides additional loss reduction value on the order of 15–25 percent. Understanding the relative value of these two implementation components is important to better inform building code policy and enforcement efforts given continuously updated codes.

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“…As the hurricane intensity is not known in advance, β is treated as a random variable with distribution Ψ( β ). Tye, Stephenson, Holland, and Katz () note that the Weibull distribution has long been established as a useful probability distribution function for modeling hurricane wind speed. Grigoriu () reports that an extensive record of hurricane wind speeds is available at the NIST (National Institute of Science and Technology), which the author and others have used to establish the distribution parameters of Ψ( β ).…”

Section: The Frameworkmentioning

confidence: 99%

Humanitarian response to hurricane disasters: Coordinating flood‐risk mitigation with fundraising and relief operations

Chakravarty

2018

Naval Research Logistics

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To alleviate flooding, caused by hurricanes, governments build structural barriers called levees. In addition, relief providers such as the nongovernmental organizations and charities raise funds, and procure and deliver supplies (food, water, and medicines) for humanitarian relief. The strategy for managing disasters must, therefore, weigh the costs and benefits of building levees as well as procuring and delivering supplies. We use a three‐stage decision making framework to study how the investment in levee capacity can be integrated with supply procurements, fundraising, and rapid response. One of our major findings is that a large fundraising cost discourages postdisaster funding, implying relatively large investments in levee and prepositioned supplies. That notwithstanding, a large social value (of saving life) can tilt the balance in favor of postdisaster funding. If the levee capacity increases, funding for predisaster procurement is reduced without affecting postdisaster funding. For a sufficiently large increase in capacity, however, postdisaster response becomes superfluous. We also find that hurricane uncertainty motivates levees with large capacity. In contrast, levee‐failures motivate levees with small capacity.

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A Weibull Approach for Improving Climate Model Projections of Tropical Cyclone Wind-Speed Distributions

Cited by 30 publications

References 48 publications

Windstorm risk assessment for offshore wind farms in the North Sea

Windstorm risk assessment for offshore wind farms in the North Sea

Demonstrating the Intensive Benefit to the Local Implementation of a Statewide Building Code

Humanitarian response to hurricane disasters: Coordinating flood‐risk mitigation with fundraising and relief operations

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