Global temperatures are rising, and this climate change is resulting in increased uncertainties for different stakeholders. For this infographic, I teamed up with Dr. Alex Pui who is an expert in catastrophe risk management and climate risk solutions to show the impacts of climate change so far and what we can expect further and how catastrophe models can be used to quantify the impacts of physical climate change risk.
Impact of Climate Change
Since industrialization, the temperature of our world has increased by roughly 1oC and this trend is continuing faster than ever. We are pretty much locked in for the increase to go up to 1.5oC in the next 30 years. Some of the hottest years to date have occurred in the last two decades. This change in temperatures leads to a number of problems. Snow is melting faster than usual, sea levels are rising, more heatwaves and draughts are happening, and more cyclones and floods are occurring to name a few.
We can expect to see more catastrophic events in the coming years due to this change. These changes lead to a very uncertain environment which creates different challenges for different stakeholders. In light of this trend, organizations and society as a whole need to be able to plan for the future and an integral first step is to better understand how physical climate risk will evolve – for example using scenario analysis and developing improved appreciation for key uncertainties in climate projections.
How catastrophe models can help?
Quantifying climate change is challenging because there are numerous variables at play that determine when and where a catastrophe will happen and at what severity. This kind of quantification also requires a sophistication and intersection among different fields of sciences like meteorology, engineering, seismology and actuarial science.
This is where catastrophe models serve as a convenient tool to merge these different disciplines. Catastrophe models have been in use in the insurance/reinsurance industry for more than 3 decades now. The models are widely used to determine the impact of different catastrophes (like Cyclone, Earthquake, Floods etc.) on a given portfolio of interest. Models are sophisticated enough to read as detailed input as latitude/longitude of building, the material it is made of, what is it used for, its height etc. This level of sophistication allows to model different kinds of scenarios based on their likelihood of happening in that specific area. The kind of question they are currently answering are: what is a chance of cyclone developing in an area of interest and what are the factors that control that cyclone’s speed, direction, strength; if that cyclone hits the area what is the expected damage on the property of interest and at what probability level.
Catastrophe models have the groundwork and foundation laid out to take it to the next level and tackle the challenge of climate change risk quantification, i.e. by conditioning the parameters of the catastrophe models based on climate model projections. Adjusting these parameters however is not a straightforward exercise and requires a deep understanding of the science behind, and key assumptions as to how the catastrophe models operate. For example, questions like what is the quantitative economic impact of change in sea surface temperature by xoC in your area of interest to future cyclone risk can be addressed through this exercise. This sort of sensitivity analysis holds tremendous value as it allows the user to make more informed decisions around identifying key areas of interest, and prioritize mitigation and other risk management efforts accordingly.
About Dr. Alex Pui
Alex is currently Head Nat Cat and Sustainability (APAC) at Swiss Re Corporate Solutions based in Tokyo, Japan. He is also an Adjunct Lecturer at the School of Civil and Environmental Engineering, University of New South Wales (UNSW). Apart from pioneering climate and other innovative risk solutions, Alex is responsible for managing the APAC Nat Cat portfolio. His has worked in Singapore and Australia, with stints at Willis Re and Insurance Australia Group involving catastrophe risk modelling and research. Alex led the development of the world’s first parametric haze solution (“HazeShield” – co developed with Harvard University) to insure against smoke haze pollution from transboundary South East Asian haze from Indonesian forest fires. He holds a Bachelor of Law (LLB) and PhD in Applied Statistics (majoring in Climate Science) from UNSW.