Consequence forecasting: A rational framework for predicting the consequences of approaching storms

Wilkinson, Sean; Dunn, Sarah; Adams, Russell; Bossi, Nicolás Kirchner; Fowler, Hayley J.; Otalora, Sam Gonzalez; Pritchard, David; Mendes, Joana; Palin, Erika J.; Chan, Steven

doi:10.1016/j.crm.2022.100412

Cited by 9 publications

(5 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Overall, the results largely agree with previous analyses outlined in the introduction that extreme windstorms are likely to become more frequent over the UK following the RCP8.5 scenario. Furthermore, increasing the resolution of numerical models will likely provide improved input for impact models which may be valuable for future planning of infrastructure and for continued improvements in consequence forecasting for event-response planning (Dunn et al, 2018;Wilkinson et al, 2022). Large uncertainties in the projections still exist, which include random variability of cyclones at a regional level as well as the natural variability of large-scale drivers.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Projected increase in windstorm severity and contribution from sting jets over the UK and Ireland

Manning¹,

Kendon²,

Fowler³

et al. 2023

Weather and Climate Extremes

View full text Add to dashboard Cite

Section: Conclusion and Discussionmentioning

confidence: 99%

Projected increase in windstorm severity and contribution from sting jets over the UK and Ireland

Manning¹,

Kendon²,

Fowler³

et al. 2023

Weather and Climate Extremes

View full text Add to dashboard Cite

“…Under the scope of climate change impact assessments, functional damages are rarely analyzed, often just viewed as a consequence. Works related to functional damage and systemlevel loss of service, in particular, are comparatively more limited in number [17], [18]. Limiting impact assessments to the estimation of physical damages or even componentlevel functional loss overlooks the complex interdependencies of infrastructure systems [1].…”

Section: A Backgroundmentioning

confidence: 99%

A Systematic Approach to Climate Resilience Assessment of Infrastructure Networks

Li,

Punzo,

Robson

et al. 2024

IEEE Systems Journal

View full text Add to dashboard Cite

With a changing climate, the frequency and intensity of extreme weather events are likely to increase, posing a threat to infrastructure systems' resilience. The response of infrastructure systems to localized failures depends on whether assets are affected randomly, in a targeted strategic way, or in any way in between. More than that, infrastructure decisions today, including new routes or improvements to existing assets, will underpin the behavior of the systems over the next century. It is important to separate and analyze the case of climatebased disruptions and how they affect systems' resilience. This paper presents a probabilistic resilience assessment framework where failure scenarios and network disruptions are generated using weather profile data from climate prediction models with component-level fragility functions. A case study is then carried out to quantify the resilience of Great Britain's railway passenger transport system to high-temperature-related track buckling under the Representative Concentration Pathway 8.5 (RCP8.5) climate change scenario. A 95-year horizon on the resilience of the railway system is drawn. The results reveal the non-linear responses of the railway system to the increasing temperature and show that models considering random asset failures overestimate the system's resilience.

show abstract

“…Therefore, the application of a singular fragility curve is likely to be insufficient, overestimating fragility in some areas while underestimating fragility in others. Wilkinson et al (2022) present a regional analysis to develop fragility curves for specific regions, but this can potentially create difficulty in creating consistent thresholds for use and interpretation by grid operators.…”

Section: Introductionmentioning

confidence: 99%

“…As the energy sector is decarbonized and the dependence of society on reliable electricity grows (Jaroszweski et al, 2021), the ability to proactively anticipate these faults due to high wind gusts will be of increasing global importance. Fragility curves provide a useful means of achieving this aim by representing the likelihood of failure of a specific piece of infrastructure under a range of conditions and have been applied to electric power systems for a variety of extreme events including earthquakes (Lagos et al, 2020;Zareei et al, 2016) and windstorms (Dunn et al, 2018;Murray & Bell, 2014;Panteli et al, 2017;Wilkinson et al, 2022). Jeong and Elnashai (2007) group methods to develop fragility curves into four categories: (1) Analytical approaches which seek to use structural simulation models to reflect the likelihood of failure as used by Panteli et al (2017) and Zareei et al (2016); (2) Empirical approaches which rely on large amounts of historical failure data such as those used by Murray and Bell (2014) and Dunn et al (2018); (3) Judgemental approaches which form probabilities based on expert opinions; and (4) Hybrid approaches which seek to combine two or more approaches in an attempt to overcome the limitations of a single method ("scarcity of observational data, subjectivity of judgmental data and modeling deficiencies of analytical procedures") (Jeong & Elnashai, 2007, p. 1239.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing power distribution network operational resilience to extreme wind events

Donaldson

Ferranti

Quinn

et al. 2023

Meteorological Applications

View full text Add to dashboard Cite

Extreme weather events can cause significant damage to power distribution network infrastructure, often resulting in power outages. Distribution Network Operators (DNOs) are faced with the challenging task of responding to these outages in real time while maintaining a resilient grid. Our paper presents an innovative approach to alert operators about the potential risk associated with upcoming extreme weather through a normalized fragility curve. The uniqueness of the curve is the ability to capture regional differences across a DNO's territory while presenting operators with a means of setting unified risk thresholds. This can support a proactive response and allow the staging of necessary resources to minimize the threat posed by such events. Our approach captures the changes in failure probability associated with differing wind regimes and demonstrates the benefit of sub‐regional meteorological information. The proposed approach is demonstrated for wind events using 20 years of historical fault records from a DNO in the United Kingdom (UK). While its efficacy is demonstrated for windstorms in the UK, the approach could be applied globally to develop normalized fragility curves for other types of seasonal extreme weather events such as snowstorms, hurricanes, or linked hazards such as wildfires. The approach can also facilitate an understanding of how infrastructure may operate under future climate conditions, supporting proactive adaptation.

show abstract

Consequence forecasting: A rational framework for predicting the consequences of approaching storms

Cited by 9 publications

References 31 publications

Projected increase in windstorm severity and contribution from sting jets over the UK and Ireland

Projected increase in windstorm severity and contribution from sting jets over the UK and Ireland

A Systematic Approach to Climate Resilience Assessment of Infrastructure Networks

Enhancing power distribution network operational resilience to extreme wind events

Contact Info

Product

Resources

About