Overview

Might the severe risk posed by hurricanes become worse if they increasingly link with deadly heatwaves? As global temperatures rise, individual climate-driven hazards might become more intense or frequent. But, perhaps our concern should focus on entirely new or unrecognized risks caused by combinations of two or more hazards [e.g. Hillier et al, 2015], which may prove to be the most catastrophic. After all, it is events beyond human experience which are most likely to result in game changing consequences for society [Zscheischler et al., 2018]. “Black-swan” events are surprises that could not have been be anticipated (e.g. the terrorist attacks of September 11th 2001), but with suitable physical understanding of the climate system it should be possible to identifying likely devastating natural hazard combinations before they first impact. This predictability renders such potential surprises “grey swan” events. Clearly, the stakes are high in detecting such emergent threats and there is strong incentive to develop plans for minimizing their impact.

This PhD project will contribute in this regard by addressing the rising grey swan hazard of deadly (humid) heat events following tropical cyclones (TCs). The supervisors’ initial work shows that this compound hazard has so far missed densely populated regions, but that good fortune looks unlikely to hold as dangerously hot weather and powerful TCs are expected to become more frequent as the climate continues to warm  [Matthews, 2018; Matthews et al., 2017; Kang and Elsner, 2015]. The possible impacts from such a hurricane-heatwave “multiplier” hazard actually unfolding cannot be overstated, given the growing dependency on air conditioning, and the mega blackouts that have followed recent major TCs [Houser and Marsters, 2018; Barreca et al., 2013] (Fig. 1).

The most sophisticated multi-hazard probabilistic risk modelling (i.e. catastrophe modelling) is in insurance [Kappes et al., 2012], with the World Bank now leading efforts to drive these expertise into the Disaster Risk Finance (DRF) community [Mitchell-Wallace et al., 2017]. This PhD will feed into that effort, contributing to pursuit of the United Nations Sustainable Development Goals, and equipping the student with a highly-employable skill set, knowledge and experience.

Figure 1: Night-time lights on Puerto Rico before (top) and after (bottom) Hurricane Maria made landfall. Millions were left without power and potentially vulnerable to extreme heat for months after the storm’s passage.

Methodology

Through co-design with stakeholders from the outset, the project will deliver a global-scale assessment of TC-heat risk in a changing climate. Specific objectives are listed below.

O1 - Characterise contemporary TC-heat risk. Media sources, scientific literature, historical meteorology (e.g. ERA-20C) and event catalogues (e.g. IBTrACS) will be used to gain a historical perspective on the risk of compound heat-TC events. Simulation-based (or “stochastic”) modelling with synthetic TC tracks will help rigorously constrain the current risk of compound TC-heat events.

O2 - Quantify the sensitivity of the heatwave-TC hazard probability to changes in the timing and frequency of extreme heat events and landfalling TCs using tailored stochastic modelling experiments (in Python, R or Matlab).

O3 - Assess climate model projections (CMIP5/6 or HighResMIP) to determine likely changes in compound hazard frequency under given scenarios of climate warming.

Training and Skills

For this project in particular, the PhD student will gain state-of-the-art skills in the analysis of “big data”, including:

  • Geographic Information Systems and computer programming (e.g. Python, R, Matlab)
  • Environmental modelling concepts

They will also learn background to the key topics required to understand low-latitude climate risks:

  • Atmospheric thermodynamics
  • Biometeorology and human thermoregulation
  • Risk communication

The “catastrophe modelling” at the core of the PhD underpins natural hazard financial risk assessment and is critical in Disaster Risk Reduction and humanitarian efforts. The student will therefore be ideally placed with respect to a range of exciting careers upon completion of the project.

Timeline

Year 1: Firstly, the student will identify TCs and extreme heat events using the IBTrACS and observation-based meteorological datasets, respectively. Cross referencing to scientific literature and media sources will deliver a rich dataset of near misses and avoided impacts from the compound heat-TC hazard. The work will then statistically characterise current hazard using appropriate multivariate extreme value methods [e.g. Heffernan and Tawn, 2004].

Year 2: The project will move on to focus on modelling the evolving risk of compound hazard using stochastic modelling techniques. Generating a large  number of possible TC tracks and extreme heat events to explore alternative, equally plausible versions of the current climate will crucially enables us to overcome the relatively brief observation record (i.e. have we been lucky so far in the current climate to avoid a TC-heat hazard?).  Next, the likely impact of climate change will be assessed by determining properties linked to key elements in the statistical characterization (e.g. TC frequency) that are reliably represented in climate models. This will facilitate the stochastic experiments and allow the physical processes driving trends to be understood.

Year 3: Finally, the student will synthesise the analyses to provide and explain estimates of spatially-differentiated risk of the evolving compound heat-TC hazard, highlighting results for key mega-city regions to maximise clear communication to decision makers.

 

Partners and collaboration (including CASE)

The project will be pursued in collaboration with Matthew Foote, a senior DRF individual who will contribute expertise in hazard impacts and facilitate engagement with stakeholders (e.g. UK Department for International Development; World Bank).

Further Details

For information about this project, please contact Dr Tom Matthews (t.matthews@lboro.ac.uk). For enquiries about the application process, please contact SocSciResearch@lboro.ac.uk. Please quote CENTA18-LU1 when completing your online application form: http://www.lboro.ac.uk/study/apply/research/.