3 minute read

How the Royal Meteorological Society is engaging industry with

Hannah Bloomfield, Matt Wright and Daniel Skinner, Royal Meteorological Society

Extreme weather made the headlines throughout 2022: from devastating floods in Pakistan and West Africa, to heatwaves across Asia and central Europe, and Hurricane Ian in the United States. Such extreme weather events cause billions of pounds of damage and large numbers of deaths and are set to become more frequent due to climate change. This may sound quite terrifying, but the good news is that industries are starting to respond to these new challenges and are working with organisations such as the Royal Meteorological Society (RMetS, www.rmets.org) to upskill their teams in climate science. To help everyone meet ambitious net-zero targets, there needs to be collaboration across specialist sectors, and fast. This partnership between industry and the weather and climate community is critical to help adapt to our changing climate and mitigate further climate change.

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As the professional body for weather and climate, RMetS aims to advance the understanding and awareness of the science of meteorology. With a membership base of 3,000, the Society also collaborates with science and communication partners, which include academics and industry specialists. One industry group that relies heavily on weather and climate information is the insurance sector.

Why does the insurance industry care about the weather?

Insurance is a safeguard against the risk of bad things happening, such as damage or theft. Asset insurance (eg, buildings and content insurance) contains several weatherrelated hazards, which is where RMetS can support the sector.

Across Europe, most of the risks our homes are exposed to occur in winter, such as extreme precipitation, high winds, snowfall, large hail, lightning and extreme cold. However, it is becoming more common to see heightened risks during summer weather, such as heatwaves, prolonged drought and even urban wildfires. In other parts of the world, you may also require specialist insurance against tropical cyclones, tornados, tsunamis, volcanic eruptions or earthquakes if you live in an area particularly prone to these events.

The risk to a particular structure is usually calculated based on a combination of three components:

• hazard: a potentially destructive physical phenomenon;

• exposure: the location, attributes and value of assets that could be affected by a threat;

• vulnerability: the likelihood that assets will be negatively impacted when exposed to a hazard.

Insurance companies model the risk that a set of assets is exposed to using catastrophe models. Computer programs mathematically represent the characteristics of very extreme events, such as the natural catastrophes described above, or other disasters including pandemics and cyber incidents. Within these models, there will be weather-dependent models of the physical hazards as well as data on the exposure and vulnerability of the assets (normally provided by the engineering community). Academic papers, data and state- of-the-art research on the type, duration and frequency of extreme weather events are therefore critical to the insurance sector for accurate models.

Traditionally these catastrophe models focused on characterising rare but severe weather events based on historical weather information, which makes sense as you generally only purchase an insurance contract for the year ahead. However, with our ever-changing climate, this stationary view of hazards is no longer appropriate, as we regularly see record-breaking extreme weather events in our rapidly changing climate. A wealth of new science is now required by insurance companies on the impact of climate change on their hazards of interest.

As well as the potential risk to assets as objects, we must not forget that extreme weather can also negatively impact human health. The main influences here, such as extreme cold or heat, particularly affect elderly populations. In developing regions, climate change will also result in waterborne diseases like typhoid or cholera becoming more prevalent.

These extreme meteorological hazards rarely happen in isolation, and there is a growing body of meteorological research around compound weather events, ranging from extreme wind-flood events, often associated with big storms or hurricanes, to compound heatwave-drought-wildfire events, such as seen recently across California. This compound events research is important for the insurance sector as they tend to consider their hazards in isolation (eg, a single model for winds and a single model for flooding), but compounding between hazards has the potential to alter the losses experienced.

RMetS is working with academic experts and insurance practitioners to help tackle some of the key issues currently facing the insurance sector, providing access to the most upto-date learning and relevant academic research. We can also support the industry in encouraging better use of climate data for hazard modelling, and influence the academic research agenda to consider the key challenges for the insurance industry. And finally, we are looking to encourage new physical science graduates into the insurance sector. Throughout 2023, several events will be held to help with these challenges, including a Research Paper showcase, an Early Career focused networking event, and a Research Agenda setting meeting with key academics. More details on events and updates on this work will be available at www. rmets.org over the coming year.

Energy sector

In the past year, we have witnessed how weather and climate information is used extensively in the energy sector, and

Hannah Bloomfield is a Royal Meteorological Society Science Engagement Fellow and Research Associate at the University of Bristol, working for the UK Centre for Greening Finance and Investment. Matt Wright is a Royal Meteorological Society Science Engagement Fellow at the University of Oxford. Daniel Skinner is a Royal Meteorological Society Science Engagement Fellow at the University of East Anglia.