At the end of last year, the Willis Research Network (WRN) set a challenge to its members to come up with ideas for short collaborative research projects that focus on specific elements of risks associated with climate change. From the ideas submitted, three were chosen to pursue during 2021 and have recently presented their findings.
Fast moving science, can industry analytics keep up?
Before outlining their findings, first some context. The aim of these projects is to advance research into climate change-related risks and accelerate the development of our WRN project portfolio in this area. It is a chance to experiment with some new ideas and try new methods to answer the kinds of questions we are seeing from the industry. These projects will be used to develop the ideas further, and to guide and feed into our analytical offerings in the climate risk space.
The science is moving fast, and practical applications of science are running to catch up
And clearly, it’s an important and exciting time to be working on climate risk analytics. The science is moving fast, and practical applications of science are running to catch up. In my 20 years of working in the weather and climate industry, in operational and science application roles, there has never been such an appetite for understanding and using academic models and methods to advance industry practice.
It is more important than ever to leverage the best science has to offer
After the positive steps at COP26, both large and small, it is more important than ever to leverage the best science has to offer to guide decision takers and policy makers. As Willis Towers Watson creates a science-led suite of services based on our academic partnerships, we try to use our projects to provide credible and robust solutions. At the same time, academic endeavours are advancing overall understanding of the risks relating to climate change as society increases efforts to mitigate global warming and adapt to the consequences of the carbon emissions already locked into the climate system.
On 8 December 2021, the WRN hosted a webinar for the project teams to present their work to a mixed audience of industry practitioners and academic experts, followed by a question and answer session. A recording can be found here of the projects featured at the webinar, which were:
“Towards physically-based and usable climate event scenarios”, presented by Dr James Done, National Center for Atmospheric Research (NCAR), and Prof Gabriele Villarini, University of Iowa, but including contributions from Dr John Hillier, Loughborough University, and Dr Jeff Czajkowksi, Director Center for Insurance Policy and Research at National Association of Insurance Commissioners (NAIC), .
The idea of this project is to provide a framework for using climate model outputs in a variety of different ways to assess physical risks from extreme events. In this case, the team used Community Earth System Model (CESM) climate model outputs to investigate tropical cyclone impacts across a global portfolio and flooding in a specific region, in this case Iowa, under various climate change projections compared with today’s risk. The key here is to use the same source of climate model information to make two assessments of different risks but, by using the single source, to keep them physically consistent. If different models, data sources, methodologies are used for this kind of work, significant biases can be introduced which reduce the usefulness of any comparisons or multi-peril assessments. It is hoped that this project can feed into the discussions of regulatory requirements in the U.S. on climate risk and help respond to requirements around the world.
“Convective storm characteristics in a changing climate (CSTOCC)”, presented by Dr Chiara Lepore, Columbia University and Prof Dr Michael Kunz, Karlsruhe Institute of Technology (KIT).
This project leverages the work already undertaken via the WRN by both research partners in recent years to develop a view of risks associated with severe convective storms in future warmer projected climates. KIT is focusing on developing proxies for extreme hail events that can be applied to both reanalysis data and climate model outputs alike. This enables us to compare current and future risks. The representation of future risk from climate models is what Columbia University has developed using the latest climate models in the Coupled Model Intercomparison Project sixth phase (CMIP6) and through understanding how the models represent convective indices in the future to relate to current climate conditions. This can help us understand how these CMIP6 models represent changes to severe convective events in the future.
“Proposed realistic climate change stress tests approaches for disaster prone southeast Asia domain”, presented by Prof Shie-Yui Liong, National University of Singapore.
Yui and his team worked on this project to enhance one of our existing WRN projects focused on flood risk in south East Asia. Specifically, they used climate model outputs to develop intensity density frequency curves for cities in the region in the current climate and in the future based on high-emissions scenarios. This can help us assess changes to flood risk in a manner consistent with previous work to model flood risks in current climate conditions.
We used this year’s Challenge Fund to focus on physical climate risks, and encouraged collaborative projects looking into techniques that can derive tangible outputs from the years of research and expertise that have underpinned the scientific advances supported by the WRN and our academic partners.
We are about to launch our next round of challenge fund themes for 2022, so watch this space for future research targeting new and untapped areas that broadens the range of activities in the WRN.
