Modeling Extreme Hurricane Damage Using the Generalized Pareto Distribution

Dey, Asim Kumer; Das, Kumer Pial

doi:10.1080/01966324.2015.1075926

Cited by 7 publications

(6 citation statements)

References 7 publications

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“…Extreme value models evaluate the tail of a distribution and they have a wide range of applications in climate and atmospheric science to industrial risks, geosciences, finance, economics, and insurance [ 6 , 7 , 9 , 11 , 15 , 33 , 35 , 40 ].…”

Section: Methodsmentioning

confidence: 99%

How do mobility restrictions and social distancing during COVID-19 affect oil price?

Dey

Das

2022

J Stat Theory Pract

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This paper provides an analysis of the effect of the COVID-19 outbreak on the crude oil price. Using a newly developed air mobility index and Apple’s driving trends index, we assess the effect of human mobility restrictions and social distancing during the COVID-19 pandemic on the crude oil price. We apply a quantile regression model, which evaluates different quantiles of the crude oil price. We also conduct an extreme value modeling, which examines the lower tail of the crude oil price distribution. We find that both the air mobility index and driving trends index significantly influence lower and upper quantiles of the WTI crude oil price. The extreme value models suggest that there is a potential risk of a negative crude oil price for a sudden extreme fall of air mobility.

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Section: Methodsmentioning

confidence: 99%

How do mobility restrictions and social distancing during COVID-19 affect oil price?

Dey

Das

2022

J Stat Theory Pract

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“…The main objective of this study is to determine the 1 in 10 and 1 in 100 year daily average electron flux for the specified energies and L shells. Since daily averages are available and to compare with our previous studies (Meredith et al., 2015, 2016a, 2016b, 2017), we use the exceedances over a high threshold approach (Dey & Das, 2016; Thomson et al., 2011). For this approach, also known as the Peaks Over Threshold method, the appropriate distribution function is the generalized Pareto distribution (GPD), first introduced by Picklands (1975).…”

Section: Extreme Value Analysismentioning

confidence: 99%

“…This assumption is likely to be valid for the outer radiation belt studied here, but would not necessarily hold for the inner radiation belt (e.g., Shprits et al., 2011). This approach has been used successfully in many fields to estimate, for example, extremes of rainfall (e.g., Li et al., 2005), surface temperature (e.g., Nogaj et al., 2006), geomagnetic storm events (Tsubouchi & Omura, 2007), wind speed (e.g., Della‐Marta et al., 2009), geomagnetic activity (Thomson et al., 2011), storm surge (e.g., Tebaldi et al., 2012), hurricane damage (Dey & Das, 2016), and the probability of Carrington‐like solar flares (Elvidge & Angling, 2018).…”

Section: Extreme Value Analysismentioning

confidence: 99%

Extreme Relativistic Electron Fluxes in GPS Orbit: Analysis of NS41 BDD‐IIR Data

Meredith,

Cayton,

Cayton

et al. 2023

Space Weather

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Modern society is increasingly reliant on satellites for a wide variety of applications including communication, navigation, Earth observation, and defense. For example, in 2021, the overall global space economy generated revenues of $386 billion, an increase of 4% compared to 2020 (Satellite Industry Association, 2022). This ever growing infrastructure is increasingly vulnerable to the potentially damaging effects of space weather (Krausmann, 2011). The concern at government level in the UK is such that severe space weather was added to the UK National Risk Register of Civil Emergencies in 2011, where the likelihood of the reasonable worst case scenario occurring in the next year is currently estimated to be between 1 in 20 and 1 in 100 (HM National Risk Register, 2020).The impacts of space weather on satellite operations range from momentary interruptions of service to total loss of capabilities when a satellite fails. For example, during a major storm in 2003, 47 satellites experienced anomalies, more than 10 satellites were out of action for more than 1 day, and the joint US-Japanese US$640M Midori 2 environmental research satellite was a complete loss (Webb & Allen, 2004).Relativistic electrons (E > 0.5 MeV) are a major source of radiation damage to satellites. These, so-called "killer" electrons can penetrate satellite surfaces and embed themselves in insulating materials and ungrounded conductors. Here, the charge can accumulate over time resulting in the build up of high electric fields which

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“…escallonioides is light‐limited and its population dynamics are driven by hurricanes; hurricanes increase light availability by removing trees in the canopy and damage level depends on hurricane magnitude (Pascarella and Horvitz ). Modeling hurricanes using the GEV is the standard in climate science (e.g., Jagger and Elsner , Dey and Das ), typically for insurance and disaster relief planning on a statewide or regional scale (>10 5 km 2 ; Katz , Jagger and Elsner , Dinan ). Here, we fit the GEV to historical data on a much smaller spatial scale (<10 3 km 2 ) appropriate for our empirically rooted population model.…”

Section: Introductionmentioning

confidence: 99%

How climate affects extreme events and hence ecological population models

Rypkema

Horvitz

Tuljapurkar

2019

Ecology

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Extreme events significantly impact ecosystems and are predicted to increase in frequency and/or magnitude with climate change. Generalized extreme value (GEV) distributions describe most ecologically relevant extreme events, including hurricanes, wildfires, and disease spread. In climate science, the GEV is widely used as an accurate and flexible tool over large spatial scales (>105 km2) to study how changes in climate shift extreme events. However, ecologists rarely use the GEV to study how climate change affects populations. Here we show how to estimate a GEV for hurricanes at an ecologically relevant (<103 km2) spatial scale, and use the results in a stochastic, empirically based, matrix population model. As a case study, we use an understory shrub in southeast Florida, USA with hurricane‐driven dynamics and measure the effects of change using the stochastic population growth rate. We use sensitivities to analyze how population growth rate is affected by changes in hurricane frequency and intensity, canopy damage levels, and canopy recovery rates. Our results emphasize the importance of accurately estimating location‐specific storm frequency. In a rapidly changing world, our methods show how to combine realistic extreme event and population models to assess ecological impacts and to prioritize conservation actions for at‐risk populations.

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Modeling Extreme Hurricane Damage Using the Generalized Pareto Distribution

Cited by 7 publications

References 7 publications

How do mobility restrictions and social distancing during COVID-19 affect oil price?

How do mobility restrictions and social distancing during COVID-19 affect oil price?

Extreme Relativistic Electron Fluxes in GPS Orbit: Analysis of NS41 BDD‐IIR Data

How climate affects extreme events and hence ecological population models

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