- Rowan Douglas, Willis Research Network
In a modelled world, advances in higher resolution climate science will provide fundamental inputs critical to driving our understanding of current and future risks from extreme events. Today, we are only at the dawn of this era.
Until recently, it was only possible to model and predict broad climate variables, such as mean temperature or precipitation. In recent years, however, the modelling community, primarily operating with academia and public science, have been developing models which simulate the world’s oceans, atmosphere and climate to provide a physically based model of the planet. The are called General Circulation Models (sometimes Global Climate Models) or GCMs. It is these models that form the basis of assessments of current and future climate. Advances in modelling techniques, coupled with the advent of even larger super-computers, has enabled scientists to resolve, or see, complex weather events, such as tropical cyclones, in these model simulations. More sophisticated modelling techniques also allow us to assess the regional impacts we can expect from a dynamic climate. These developments hold profound possibilities for the future, and are particularly crucial as more frequent and severe events hasten our need to understand and evaluate atmospheric related hazards.
As a result, climate modelling is now moving into the frontline of economic and political debate. It is the medium and laboratory to assess the current and future risk of environmental change. But there remains a range of scientific, computing and other challenges that must be overcome.
This session will help to unpack and explain those so that the audience obtains the optimum benefit from these emerging capabilities.
The re/insurance industry, for example, traditionally has relied upon historical data, enriched and enhanced by detailed re-analysis, to form the basis of the event sets that drive its loss models. This has had a revolutionary impact on the industry over the past two decades, forming the basis for its progress in catastrophe modelling.
However, we are reaching the limits of the value we can extract from historical data alone. The historical record is relatively short when examining extreme events and may be an increasingly poor indicator of risk levels in a dynamic and changing climate. We need something more to augment history alone.
A focus for this session will be how user communities can help steer and integrate this work to have maximum impact and value to the public and private sector stakeholders charged with managing natural catastrophe risk for their populations.
While the industrial epicentre of these issues may lie within the insurance and reinsurance industries, their nature renders them part of a wider public, economic and political discourse. Indeed, the concept of sharing of risk among populations at local and global scales via public and private mechanisms is on of intense focus and debate, with far-reaching implications for the science and risk management communities.
This session’s speakers represent leading research institutions with a significant focus on the expected locations, frequency and severity of extreme weather events. We can expect today’s speakers to provide their own views on the current state of the science of extreme events, future climate activity, and the uncertainties that remain.
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