Tag Archives: Windstorm

Europe’s Winter Windstorms – the Only Certainty is Uncertainty

The annual damage from European windstorms can range significantly: from years when there are clusters of severely damaging storms to other years with almost no windstorm loss. How much of this volatility can we predict, and how much remains a roll of the dice? And more specifically, what storm activity can we expect over the next few months?

Forecasting Storminess

Our understanding of the drivers of annual storminess has increased greatly in recent years, allowing us to provide more forecasting insight than ever before. However, there is a cautionary tale for the industry, one that shows the limitations of even the most sophisticated seasonal forecasts.

The Atlantic Multidecadal Oscillation (AMO) is a pattern of long-duration variability in sea surface temperature in the North Atlantic. It is known to influence the climate over much of the northern hemisphere including the level of storminess in Europe1. As north-south gradients of heat in the Atlantic act to fuel extra-tropical storms2 these longer term changes in sea surface temperature tend to alter the odds of extreme storm occurrence over timescales of 60-80 years. Today, the ongoing positive (warm) phase of the AMO favors lower than average storminess this winter.

Annual average values for the AMO Index, 1856-2015 (data from NOAA ESRL3). Positive values (red bars) indicate warmer sea surface temperatures across the North Atlantic, while negative values (blue bars) indicate cooler temperatures.

That’s the multi-decadal perspective. But it will come as no surprise for Europeans to hear that as well as these longer phases of relative activity and inactivity, the continent also experiences variability of storminess from year to year. We know that the jet stream is a main ingredient of storms, and that in turn these storms strengthen the jet itself, in a positive feedback loop that leads to the term “eddy-driven jet.”  This “storms-beget-storms” mechanism typically plays out over a few weeks, and more severe storms are likelier to occur during these periods. The positive feedback between jet and storms amplifies swings in annual damage, and explains a substantial amount of the storm clustering found in longer range historical weather records4. This coupling between storms and jet is reflected in the version 16.0 of the RMS Europe Windstorm Clustering Model.

Researchers have identified various drivers of seasonal storminess in the North Atlantic which, for the coming winter, are ambiguous. For instance: we are three years after the peak of a prolonged but subdued solar cycle and this timing suggests less forcing of storminess. But in contrast the predictions are for neutral to weak La Niña phases of the El Niño–Southern Oscillation (ENSO) which points to a chance of increased forcing of North Atlantic storminess. Whilst, to complicate things further, the anticipated values of tropical stratosphere winds, linked to the Quasi-Biennial Oscillation (QBO), are related to less storminess in the mid-latitude Atlantic – with the caveat that they are in an unusually disrupted pattern.

So is it possible to get off the meteorological fence and make a call? Yes: overall, the multi-decadal and seasonal drivers indicate slightly below average storminess.

Severe Events Can Occur During Any Season

But this does not mean that we as an industry should be entirely relaxed about the new storm season, as the outlook for annual storm damage is blurred by the vagaries of local weather. This is exemplified by storm Kyrill in January 2007.

Then, ahead of the 2006/07 winter, the seasonal and multi-decadal drivers indicated below average storminess, just as they do today. But Kyrill occurred and turned an otherwise innocuous season into a bad one for many. The gusts and damage during this storm were much more extreme than its general circulation, because convection cells embedded in the cold front contributed to extreme damage intensity in some areas5. Storm Kyrill showed how processes on small space and time scales can dominate annual storm damage. These drivers have seriously short predictability windows of just a few hours.

More generally, some of the past variations in annual storminess have no known driver. We are not quite sure how much, but a reasonable ball-park figure is one half. This random part is found in climate models, where the tiniest possible changes at the start of a forecast often grow into large changes in seasonal average storminess.

Although our understanding of the drivers of storminess has greatly increased over the past few years and the odds do favor less storm damage this winter, we should not be complacent. As its tenth anniversary approaches, Storm Kyrill reminds us that major losses can happen in any season, regardless of the forecast.

Web links to references above

1Peings and Magnusdottir (2014)  [ http://iopscience.iop.org/article/10.1088/1748-9326/9/3/034018/pdf ]

2Shaffrey and Sutton (2006)  [ http://journals.ametsoc.org/doi/pdf/10.1175/JCLI3652.1 ]

3NOAA ESRL AMO data [http://www.esrl.noaa.gov/psd/data/timeseries/AMO/ ]

4Cusack (2016)  [ http://www.nat-hazards-earth-syst-sci.net/16/901/2016/nhess-16-901-2016.pdf ]

5Fink et al. (2009)  [ http://centaur.reading.ac.uk/32783/1/nhess-9-405-2009.pdf ]

This post was co-authored by Peter Holland and Stephen Cusack.

A Perennial Debate: Disaster Planning versus Disaster Response

In May we saw a historic first: the World Humanitarian Summit. Held in Istanbul, representatives of 177 states attended. One UN chief summarised its mission thus: “a once-in-a-generation opportunity to set in motion an ambitious and far-reaching agenda to change the way that we alleviate, and most importantly prevent, the suffering of the world’s most vulnerable people.”

And in that sentence we find one of the enduring tensions within the disaster field: between “prevention” and “alleviation.” Between on the one hand reducing disaster risk through resilience-building investments, and on the other reducing suffering and loss through emergency response.

But in a world of constrained political budgets, where should we concentrate our energies and resources: disaster risk reduction or disaster response?

How to Close the Resilience Gap

The Istanbul summit saw a new global network launched to engage business in crisis situations through “pre-positioning supplies, meeting humanitarian needs and providing resources, knowledge and expertise to disaster prevention.” It is, of course, prudent to have stockpiles of humanitarian supplies strategically placed.

But is the dialogue still too focused on response? Could we not have hoped to see a greater emphasis on driving the disaster-resilient behaviours and investments, which reduce the reliance on emergency response in the first place?

Politics & Priorities

“Cost-effectiveness” is a concept with which humanitarian aid and governmental agencies have struggled over many years. But when it comes to building resilience, it is in fact possible to cost-justify the best course of action. After all, the insurance industry, piqued by the dual surprise of Hurricane Andrew and then the Northridge earthquake, has been using stochastic models to quantify and reduce catastrophe risk since the mid-1990s.

Unfortunately risk/reward analyses are rarely straightforward in practice. This is less a failing of the models to accurately characterise complex phenomena, though that certainly is a challenge. It’s more a question of politics.

It is harder for any government to argue that spending scarce public funds on building resilience in advance of a possible disaster is money well spent. By contrast, when disaster strikes and human suffering is writ large across the media, then there is a pressing political imperative to intervene. As a result many agencies sadly allocate more funds to disaster response than to disaster prevention, even though the analytics mostly suggest the opposite would be more beneficial.

A New, Ambitious form of Public Private Partnership

But there are signs that across the different strata of government the mood is changing. The cities of San Francisco and Berkeley, for example, have begun to use catastrophe models to quantify the cost of inaction and thereby drive risk-reducing investments. For San Francisco the focus has been on protecting the city’s economic and social wealth from future sea level rise. In Berkeley, resilience models have been deployed to shore-up critical infrastructure against the threat of earthquakes.

In May, RMS held the first international workshop on how resilience analytics can be used to manage urban resilience. Attended by public officials from several continents the engagement in the topic was very high.

The role of resilience analytics to help design, implement, and measure resilience strategies was emphasized by Arnoldo Kramer, the first Chief Resilience Officer (CRO) of the largest city in the western hemisphere, Mexico City. The workshop discussion went further than just explaining how these models can be used to quantify the potential, risk-adjusted return on investment from resilience initiatives. The group stressed the role of resilience metrics in helping cities finance capital investments in new, protective infrastructure.

Stimulated by commitments under the Sendai Framework to work more closely with the private sector, lower income regions are also increasingly benefiting from such techniques – not just to inform disaster response, but also to finance the reduction of disaster risk in the first place. Indeed there are encouraging signs that these two different worlds are beginning to understand each other better. At the inaugural working group meeting of the Insurance Development Forum in Singapore last month there was a productive dialogue between the UN Development Programme and the risk transfer industry. It was clear that both sides wanted action, not just words.

Such initiatives can only serve to accelerate the incorporation of resilience analytics into existing disaster risk reduction programmes. This may be a once-in-a-generation opportunity to address the shameful gap between the economic costs of natural disasters and the fraction of those costs that are insured.

We cannot prevent natural disasters from happening. But neither can we continue to afford to spend billions of dollars picking up the pieces when they strike. I am hopeful that we will take this opportunity to bring resilience analytics into under-served societies, making them tougher, more resilient, so that when catastrophe strikes, the impact is lessened and societies can bounce back far more readily.

Lessons Hidden In A Quiet Windstorm Season

Wind gusts in excess of 100mph hit remote parts of Scotland earlier this month as a strong jet stream brought windstorms Elon and Felix to Europe. The storms are some of the strongest so far this winter; however, widespread severe damage is not expected because the winds struck mainly remote areas.

These storms are characteristic of what has largely been an unspectacular 2014/15 Europe windstorm season. In fact the most chaotic thing to cross the North Atlantic this winter and impact our shores has probably been the Black Friday sales.

This absence of a significantly damaging windstorm in Europe follows on from what was an active winter in 2013/14, but which contained no individual standout events. More detail of the characteristics of that season are outlined in RMS’ 2013-2014 Winter Storms in Europe report.

There’s a temptation to say there is nothing to learn from this year’s winter storm season. Look closer, however, and there are lessons that can help the industry prepare for more extreme seasons.

What have we learnt?

This season was unusual in that a series of wind, flood, and surge events accumulated to drive losses. This contrasts to previous seasons when losses have generally been dominated by a single peril—either a knockout windstorm or inland flood.

This combination of loss drivers poses a challenge for the (re)insurance industry, as it can be difficult to break out the source of claims and distinguish wind from flood losses, which can complicate claim payments, particularly if flood is excluded or sub-limited.

The clustering of heavy rainfall that led to persistent flooding put a focus on the terms and conditions of reinsurance contracts, in particular the hours clause: the time period over which losses can be counted as a single event.

The season also brought home the challenges of understanding loss correlation across perils, as well as the need to have high-resolution inland flood modeling tools. (Re)insurers need to understand flood risk consistently at a high resolution across Europe, while understanding loss correlation across river basins and the impact of flood specific financial terms, such as the hours clause.

Unremarkable as it was, the season has highlighted many challenges that the industry needs to be able to evaluate before the next “extreme” season comes our way.

Location, location, location: what makes a windstorm memorable?

While wind speed can indicate a storm’s damageability, two storms with similar peak wind speeds can cause vastly different levels of damage if they pass over locations with different concentrations of exposure.

This month marks the 15th anniversary of Lothar and Martin. Two powerful storms that tracked violently across Europe on December 26-28, 1999.

The combined European loss of both storms is in excess of $11 billion (2013 values). Since the storms occurred within days of each other it’s difficult to calculate the exact split of damage, however a 70:30 ratio is commonly accepted, ranking Lothar as the second largest Europe windstorm loss on record after Daria (1990).

France was hit hardest by the stormsparticularly Paris, which was right in the bullseye of Lothar’s most extreme physical characteristics. The recorded wind speeds in the low-lying regions of Paris were above 160 km/h and as high as 200 km/h at the top of the Eiffel Tower.

An exceptional storm

While Lothar’s wind speeds are comparable to other historical Europe windstorms, it’s considered an exceptional event for the insurance industry because of its track and the timing of its maximum intensification over Paris. Today, Lothar is a key benchmark used by the industry to understand the potential magnitude of Europe windstorm losses.

Lothar – a one-off for France?

Many industry experts believe Lothar to be higher than a 100-year return period loss event for France; however this should be interpreted as a long-term average and France could potentially experience a similarly extreme storm this winter.

Using current industry exposures, RMS calculated the potential French losses that would result from a Lothar-like storm striking different locations in France. By relocating Lothar’s peak gusts along points up to 500 km in each direction from their original location, our modelers concluded that Lothar was the fourth worst-case storm that could have happened out of a total of 437 scenarios.

The worst-case scenario for France is a Lothar-like storm relocated approximately 100 km west of the original event but which would still significantly impact Paris. The losses from this scenario are not much higher than Lothar’s. At only 15 percent higher the small increase in loss reinforces Lothar as an exceptional benchmark for the insurance industry.

We found that the majority of scenarios in the study produced notably lower losses. This is because the displacement of the storm, by even small distances, meant that the most extreme wind speeds impacted much lower concentrations of insured exposures. The study reinforces our understanding of the sensitivity of windstorm loss to a storm’s path. It also highlights the importance of using a stochastic model containing tens of thousands of events to be able to comprehensively evaluate potential windstorm losses.

London at risk

No European city is immune from damaging windstorms. RMS also re-located Lothar over Londononly a 350 km shift to the northto see what the impacts would be. We calculated the insured loss for Europe could be as much as 25 percent higher than Lothar’s losses and potentially bigger than the $8.6 billion loss caused by Daria.

The uncertainty inherent to the climatic phenomena that drive windstorms makes it impossible to forecast exactly when and where the next strong storm will hit France or Europe. However, catastrophe models can at least help to evaluate the potential financial impact of extreme storms like Lothar.

What to expect this 2014-2015 Europe Winter Windstorm Season

When it rains in Sulawesi it blows a gale in Surrey, some 12,000 miles away? While these occurrences may sound distinct and uncorrelated, the wet weather in Indonesia is likely to have played some role in the persistent stormy weather experienced across northern Europe last winter.

Weather events are clearly connected in different parts of the world. The events of last winter are discussed in RMS’ 2013-2014 Winter Storms in Europe report, which provides an in-depth analysis of the main 2013-2014 winter storm events and why it is difficult to predict European windstorm hazard due to many factors, including the influence of distant climate anomalies from across the globe.

Can we predict seasonal windstorm activity during the 2014-2015 Europe winter windstorm season?

As we enter the 2014-2015 Europe winter windstorm season, (re)insurers are wondering what to expect.

Many consider current weather forecasting tools beyond a week to be as useful as the unique “weather forecasting stone” that I came across on a recent vacation.

I am not so cynical; while weather forecasting models may have missed storms in the past and the outputs of long-range forecasts still contain uncertainty, they have progressed significantly in recent years.

In addition, our understanding of climatic drivers that strongly influence our weather, such as the North Atlantic Oscillation (NAO), El Niño Southern Oscillation (ENSO), and the Quasi-Biennial Oscillation (QBO) is constantly improving. As we learn more about these phenomena, forecasts will improve, as will our ability to identify trends and likely outcomes.

What can we expect this season?

The Indian dipole is an oscillation in sea surface temperatures between the East and West Indian Ocean. It has trended positively since the beginning of the year to a neutral phase and is forecast to remain neutral into 2015. Indonesia is historically wet during a negative phase, so we are unlikely to observe the same pattern that was characteristic of winter 2013-2014.

Current forecasts indicate that we will observe a weak central El Niño this winter. Historically speaking this has led to colder winter temperatures over northern Europe, with a blocking system drawing cooler temperatures from the north and northeast.

The influence of ENSO on the jet stream is less well-defined but potentially indicates that storms will be steered along a more southerly track. Lastly, the QBO is currently in a strong easterly phase, which tends to weaken the polar vortex as well as westerlies over the Atlantic.

Big losses can occur during low-activity seasons

Climatic features like NAO, ENSO, and QBO are indicators of potential trends in activity. While they provide some insight, (re)insurers are unlikely to use them to inform their underwriting strategy.

And, knowing that a season may have low overall winter storm activity does not remove the risk of having a significant windstorm event. For example, Windstorm Klaus occurred during a period of low winter storm activity in 2009 and devastated large parts of southern Europe, causing $3.4 billion in insured losses.

Given this uncertainty around what could occur, catastrophe models remain the best tool available for the (re)insurance industry to evaluate risk and prepare for potential impacts. While they don’t aim to forecast exactly what will happen this winter, they help us understand potential worst-case scenarios, and inform appropriate strategies to manage the exposure.

Lessons Learned from Winter Windstorm Season in Europe

The 2013–2014 winter windstorm season in Europe will be remembered for being particularly active, bringing persistent unsettled weather to the region, and with it some exceptional meteorological features. The insurance industry will have much to learn from this winter.

Past extreme windstorms, such as Daria, Herta, Vivian, and Wiebke in 1990, each caused significant losses in Europe. In contrast, the individual storms of 2013–2014 caused relatively low levels of loss. While not extreme on a single-event basis, the accumulated activity and loss across the season was notable, primarily due to the specific characteristics of the jet stream.

A stronger-than-usual jet stream off the U.S. Eastern Seaboard was caused by very cold polar air over Canada and warmer-than-normal sea-surface temperatures in the sub-tropical West Atlantic and Caribbean Sea. Subsequently, this jet stream significantly weakened over the East Atlantic.

Therefore, the majority of systems were mature and wet when they reached Europe. These storms, while associated with steep pressure gradients, brought only moderate peak gust wind speeds onshore, mainly to the U.K. and Ireland. In contrast, the storms that hit Europe in 1990 were mostly still in their development phase under a strong jet stream as they passed over the continent.

The 2013––2014 storms were also very wet, and many parts of the U.K. experienced record-breaking rainfall resulting in significant inland flooding. Again, individual storms were not uniquely severe, but the impact was cumulative, especially as the soil progressively saturated.

Not all events this winter season weakened before impact. Windstorms Christian and Xaver were exceptions, only becoming mature storms after crossing the British Isles into the North Sea and were more damaging.

Christian impacted Germany, Denmark, and Sweden with strong winds. RMS engineers visited the region and observed that the majority of building damage was dominated by the usual tile uplift along the edges of the buildings. Fallen trees were observed, but in most cases, there was sufficient clearance to prevent them from causing building damage.

Xaver brought a significant storm surge to northern Europe, although coastal defenses mostly withstood the storm. Xaver, as well as some of this year’s other events, demonstrated the importance of understanding tides when assessing surge hazard as many events coincided with some of the highest tides of the year. The size of a storm-induced surge is much smaller than the local tidal range; consequently, if these events had occurred a few days earlier or later, the astronomical tide would have been reduced, significantly reducing the high water level.

Windstorm3

Wind, flood, and coastal surge are three components of this variable peril that can make the difference between unsettled and extreme weather. This highlights the importance of modeling the complete life cycle of windstorms, the background climate, and antecedent conditions to fully understand the potential hazard.

This season has also raised questions about the variability of windstorm activity in Europe, how much we understand this variability, and what we can do to better understand it in the future. While this winter season was active, we have been in a lull of storm activity for about 20 years.

Given the uncertainty that surrounds our ability to predict the future of this damaging peril, perhaps for now we are best positioned to learn lessons from the past. This past winter provided a unique opportunity, compared to the more extreme events that have dominated the recent historical record.

RMS has prepared a detailed report on the 2013–2014 Europe windstorm season, which analyzes the events that occurred and their insurance and modeling considerations. To access the full report, visit RMS publications.

How Does Southern Europe Weather the Storm?

The 2013-14 European winter storm season has been pretty active so far. Early in the season, Windstorm Christian raced across northern Europe, followed by Xaver in early December, and then storms Dirk, Erich, Felix and Anne hit the U.K., Ireland, and northwest France over the Christmas and New Year period.

To date the season has been a great demonstration of how northern Europe is a common target for winter storms. However, this week sees the 5th anniversary of Windstorm Klaus, reminding us that storms can also impact southern Europe, affecting regions not acclimatized to extreme winds and causing severe damage.

What happened when Klaus hit and what have we learned from it?

Can such a storm occur again in the near future and more importantly, can we predict it, or at least estimate how bad it could be?

Windstorm Klaus sprung to life on January 23, 2009 in the central Atlantic, directly in line with southern France. The climate backdrop to this storm was pretty uncharacteristic. The large-scale Icelandic low-pressure system and the Azores high-pressure system were farther south than usual. Also, the North Atlantic Oscillation (NAO) was entering a negative phase.

A positive phase of the NAO creates favorable conditions for strong storms to pass over northern Europe, as Lothar and Anatol did in 1999. But a neutral or negative phase of the NAO can lead to storms that affect southern Europe and this is exactly what happened with Windstorm Klaus.

By midnight on January 24, as Klaus approached land, it had a central pressure of 963 hPa, comparable to Windstorm Lothar. Winds reached severe gale force in the southwest of France, peaking with gusts above 140 km/h at coastal locations near Bordeaux, accompanied by violent seas with wave heights of several meters. Local infrastructure was severely disrupted by fallen trees and electricity pylons.

Over 1.7 million households were without power immediately after the storm and over 60% of maritime pines in the Forêt des Landes were destroyed. Once the damage had been appraised, Klaus was estimated to have caused insured losses of €2.5billion (US$3.4 billion).

Shortly after the event, RMS scientists Dr. Navin Peiris and Dr. Christos Mitas conducted a reconnaissance survey, which helped to enhance our understanding of building vulnerability in this region. They observed frequent non-structural wind damage, such as the uplifting of roof tiles and collapsed chimneys, but also direct wind damages from tree fall, due to the high density of trees in close proximity to properties.

Source: RMS 2009 reconnaissance

Closer examination of the roof damage revealed little evidence of proper fixation, particularly along roof edges, leaving them more vulnerable to wind damage. Another observation was the use of canal-type tiles, which are prone to uplift from the build up of air pressure, caused by strong winds. Also, damage was more frequent in residential properties, compared to commercial or industrial buildings that are generally engineered in line with building codes.

This survey, combined with an assessment of claims data, provided us with an enhanced understanding of regional vulnerability differences. For example, we observed a significantly lower fragility of buildings in the Perpignan area compared to the southwest of France.

Ratio of the modeled and observed losses by postcode using non-regionalized vulnerability functions. Variation supports need for distinct vulnerability regions.

Ratio of the modeled and observed losses by postcode using non-regionalized vulnerability functions. Variation supports need for distinct vulnerability regions.

This information is vital for us to continually develop and inform our models, in order to represent the risk accurately. Due to the inherent uncertainty in the climatic phenomena driving windstorms, it is not possible to forecast exactly when the next strong storm will hit southern Europe. Catastrophe models provide a range of possible events, which can help the insurance industry prepare for the next big event.

The RMS Europe Windstorm Model contains storms comparable to Klaus, including some that impart larger wind intensities and damages. The below image compares two examples of stochastic storms with the actual Klaus wind footprint to illustrate storms that could potentially cause insured losses similar to or higher than Klaus.

Klaus and Stochastics

Currently we are in a close to neutral phase of the NAO, so does that mean a Klaus type storm could occur this winter? No one can answer that question for certain, but a model at least enables us to explore the possible worst-case scenarios and be prepared.

Windfall or a Windy Fall?

On my recent trip to Warsaw, the fall leaves were in full color – yellows and oranges lined the wide streets. Beautiful to look at but a reminder that it is a worrying time for (re)insurers as the European windstorm season commences.

With the recent passage of Windstorm Christian, (re)insurers will be watching to see what the remainder of the season brings… A quiet windstorm season means lower catastrophe losses but a windy fall could cost billions.

In a typical season, only a small number of the many depressions that form along the jet stream develop into potentially damaging windstorms.

In recent decades, however, there has been considerable variability in windstorm frequency. The chart below demonstrates the average annual loss (AAL) from windstorms over varying periods since 1972.

While Europe has experienced significant windstorm events during this time, notably in 1987, 1990, 1999 and 2007, there is an apparent trend of decreasing AAL over time.

Europe windstorm AAL for selected periods relative to long-term AAL based on RMS storm reconstructions from windspeed anemometer data, using the RMS v11 model

Europe windstorm AAL for selected periods relative to long-term AAL based on RMS storm reconstructions from windspeed anemometer data, using the RMS v11 model

So what’s going on?

Of course this trend could be just noise in the system and it may not continue, but what if it does?

Can we forecast seasonal activity?

European windstorms are often linked to the North Atlantic Oscillation (NAO), a measure of the surface-level pressure between the Azores and Iceland. When anomalously positive, the possibility of damaging windstorms across northern Europe increases. Currently, however, the NAO cannot be predicted on a timeframe that makes seasonal forecasts possible.

Even if we could make seasonal forecasts, uncertainty remains regarding where and when storms strike. We are all familiar with the infamous windstorm seasons of 1990 and 1999, when clusters of powerful windstorms caused insured losses of $18 billion and $14 billion, respectively (2012, Swiss Re).

Clustering can be spatial and/or temporal.

  • Spatial clustering refers to the occurrence of multiple storms in the same region
  • Temporal clustering occurs when multiple storms occur at the same time

Windstorms Lothar and Martin were clustered spatially and temporally, as was the extraordinary sequence of storms in January – February 1990 that swept across Europe.

Clustering is meteorologically complex; the scientific community doesn’t know enough about the dynamics of clustering to be able to forecast the phenomenon on sufficiently useful lead times.

And what about climate change?

In the recent IPCC report, there was low confidence associated with their forecasts of future Europe windstorm behavior. And compared to inter-decadal variability, the climate change signal is weaker, so perhaps that should be of greater concern to the (re)insurance industry.

These are front-of-mind topics requiring further exploration. At a recent workshop co-hosted by RMS and the Risk Prediction Initiative (RPI), leading academics from the field of European windstorm research (ETH Zürich, University of Reading, Freie University Berlin, University of Oxford; University of Birmingham) met with RMS scientists to discuss their latest research, helping us to develop our understanding of these important topics.

In summary, there is no easy answer to the topic of seasonal European storm forecasts.

In the meantime, industry participants will take a view, and wait to see whether they experience a windy fall or a windfall. Only time will tell.