A robust estimator for the intensity of the Poisson point process of extreme weather events

Dalelane, Clementine; Deutschländer, Thomas

doi:10.1016/j.wace.2013.07.003

Cited by 9 publications

(4 citation statements)

References 45 publications

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“…The p value for this table is 0.0177, which supports the argument that in years with multiple storms, the storms are stronger than in years with only one storm, or, in terms of physical argument, years with conditions favorable for hurricanes in an area are likely to have both more storms and stronger storms than years in which conditions are not favorable. Problems with mixed populations and clustering can be found in GEV methods and have shown that both approaches have to be used with care in such situations (Ashkar and Tatsambon 2007;Dalelane and Deutscländer 2013) and as noted previously are recognized to create problems with GPD methods. Often these populations have recognizable physical bases that can help understand the differences between different populations, for example surges from extratropical storms versus surges from tropical storms and storms making local landfall versus those which make landfall some distance from a site.…”

Section: Storm Intensity and Storm Ratementioning

confidence: 92%

“…Problems with mixed populations and clustering can be found in GEV methods and have shown that both approaches have to be used with care in such situations (Ashkar and Tatsambon 2007 ; Dalelane and Deutscländer 2013 ) and as noted previously are recognized to create problems with GPD methods. Often these populations have recognizable physical bases that can help understand the differences between different populations, for example surges from extratropical storms versus surges from tropical storms and storms making local landfall versus those which make landfall some distance from a site.…”

Section: Examples Of Natural Structure Directly Affecting Surge Hazar...mentioning

confidence: 97%

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The effects of natural structure on estimated tropical cyclone surge extremes

2017

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The past 12 years have seen significant steps forward in the science and practice of coastal flood analysis. This paper aims to recount and critically assess these advances, while helping identify next steps for the field. This paper then focuses on a key problem, connecting the probabilistic characterization of flood hazards to their physical mechanisms. Our investigation into the effects of natural structure on the probabilities of storm surges shows that several different types of spatial-, temporal-, and process-related organizations affect key assumptions made in many of the methods used to estimate these probabilities. Following a brief introduction to general historical methods, we analyze the two joint probability methods used in most tropical cyclone hazard and risk studies today: the surface response function and Bayesian quadrature. A major difference between these two methods is that the response function creates continuous surfaces, which can be interpolated or extrapolated on a fine scale if necessary, and the Bayesian quadrature optimizes a set of probability masses, which cannot be directly interpolated or extrapolated. Several examples are given here showing significant impacts related to natural structure that should not be neglected in hazard and risk assessment for tropical cyclones including: (1) differences between omnidirectional sampling and directional-dependent sampling of storms in near coastal areas; (2) the impact of surge probability discontinuities on the treatment of epistemic uncertainty; (3) the ability to reduce aleatory uncertainty when sampling over larger spatial domains; and (4) the need to quantify trade-offs between aleatory and epistemic uncertainties in long-term stochastic sampling.

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Section: Storm Intensity and Storm Ratementioning

confidence: 92%

Section: Examples Of Natural Structure Directly Affecting Surge Hazar...mentioning

confidence: 97%

The effects of natural structure on estimated tropical cyclone surge extremes

2017

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“…A more suitable approach is to apply Poisson point process models which allow models to be fit to the point event data directly. Poisson point process models are suitable for modelling the distribution of points in space and time and have been used in a number of settings including modelling disease case data, species distributions [42] and locations of storm peaks [43].…”

Section: Spatial Modellingmentioning

confidence: 99%

A stitch in time: The importance of water and sanitation services (WSS) infrastructure maintenance for cholera risk. A geospatial analysis in Harare, Zimbabwe

Ayling,

Milusheva,

Maidei Kashangura

et al. 2023

PLoS Negl Trop Dis

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Understanding the factors associated with cholera outbreaks is an integral part of designing better approaches to mitigate their impact. Using a rich set of georeferenced case data from the cholera epidemic that occurred in Harare from September 2018 to January 2019, we apply spatio-temporal modelling to better understand how the outbreak unfolded and the factors associated with higher risk of being a reported case. Using Call Detail Records (CDR) to estimate weekly population movement of the community throughout the city, results suggest that broader human movement (not limited to infected agents) helps to explain some of the spatio-temporal patterns of cases observed. In addition, results highlight a number of socio-demographic risk factors and suggest that there is a relationship between cholera risk and water infrastructure. The analysis shows that populations living close to the sewer network, with high access to piped water are associated with at higher risk. One possible explanation for this observation is that sewer bursts led to the contamination of the piped water network. This could have turned access to piped water, usually assumed to be associated with reduced cholera risk, into a risk factor itself. Such events highlight the importance of maintenance in the provision of SDG improved water and sanitation infrastructure.

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“…This study is set in Germany where the topic of heat waves is of urgent relevance, too. The global trend of increased annual average temperatures and more extreme heat waves also applies to Europe and Germany (Dalelane & Deutschländer, 2013; Fischer & Schär, 2010; Jacob et al., 2014), provoking growing numbers of citizens experiencing negative health impacts, thus higher costs for the health system and ultimately an increase in fatalities (Forzieri et al., 2017). In Germany, the years from 2018 to 2020 were the hottest years on record to date (DWD, 2020) and almost 20,000 heat‐related fatalities occurred during these three summers (Winklmayr et al., 2022).…”

Section: Introductionmentioning

confidence: 99%

Individual heat adaptation: Analyzing risk communication, warnings, heat risk perception, and protective behavior in three German cities

Heidenreich,

Thieken

2024

Risk Analysis

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Extreme heat poses severe health threats, as the increased numbers of hospitalizations and fatalities during heat waves show, though little is known about adaptive behavior toward heat. We conducted a household survey on individual perceptions of heat stress and individual heat protection in the summer and autumn of 2019. In total, 1417 people from three medium‐sized German cities participated via telephone or online. Based on the Protective Action Decision Model (PADM), which we adapted to heat stress, we analyzed links between risk perception, environmental and demographic factors, perceptions of stakeholders, different heat warning messages, as well as actual and intended adaptive behavior. Overall, the PADM constructs explained around 16% of the variance in protection motivation, 19% in protective response, and 23% in emotion‐focused coping. Context factors (i.e., temperature, risk communication, gender, age, and homeownership) were significant predictors of the addressed outcome variables as were psychological factors (i.e., perceived personal vulnerability, response efficacy, response costs, preparedness, and perceived external responsibility). We further explored the effect of different warning messages on situational knowledge and intended behavioral adaptation in an experimental setting. Results showed that respondents felt significantly better informed after receiving a warning with action recommendations and reported more intended specific behaviors. Our research gives insights into individual protective action decision‐making processes. Based on our findings, we recommend tailoring risk communication strategies and combining heat warnings with action recommendations whenever possible to increase understanding and individual adaptation.

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A robust estimator for the intensity of the Poisson point process of extreme weather events

Cited by 9 publications

References 45 publications

The effects of natural structure on estimated tropical cyclone surge extremes

The effects of natural structure on estimated tropical cyclone surge extremes

A stitch in time: The importance of water and sanitation services (WSS) infrastructure maintenance for cholera risk. A geospatial analysis in Harare, Zimbabwe

Individual heat adaptation: Analyzing risk communication, warnings, heat risk perception, and protective behavior in three German cities

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