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New European extreme windstorms catalogue

Damaged fallen tree on a rural road after a strong storm

May 2014 - The Met Office and the Universities of Reading and Exeter recently launched the XWS (eXtreme WindStorms) catalogue - a freely available database of the most intense winter storms to hit Europe over the last few decades.

Windstorms are a major source of natural hazard risk for many countries in Europe. These extreme weather systems are the second greatest cause of natural catastrophe insurance losses on the planet. As a recent example, on 28 October 2013 windstorm Christian (St Jude's Day storm) destroyed infrastructure and interrupted transport and business in several countries across northern Europe. This windstorm is estimated to have caused nearly £1 billion of insured losses across Europe and more than £300 million of insured losses in the UK.

Storm footprints

Looking at past events can help scientists and insurers to better quantify and understand this important source of risk. In particular, to understand the losses caused by past storms, the industry needs reliable, high resolution spatial maps of maximum gusts for each event (known as storm footprints).

The eXtreme WindStorms (XWS) catalogue, available at, contains downloadable storm footprints derived from Met Office Unified Model simulations, with their associated tracks, for 50 of the most extreme winter European windstorms over the period 1979 to 2013 (October to March).

As well as helping to understand the damage caused by individual past events, this consistent historical catalogue can provide information on the variability of storm tracks and footprints. The catalogue also highlights events from the past which may have been not so well studied because they did not hit large urban areas, or because their damage was not well documented at the time.

Major storms

Some of the more major storms included are the Great Storm of '87, the Burns' Day storm of 1990 (also known as Daria), and the series of December 1999 storms, Anatol, Lothar and Martin.

Storm footprint examples: (a) and (b) maximum 3-second gust footprints of the Great Storm of '87 and Kyrill (January 2007); (c) and (d) mean recalibrated footprints for the same storms.

The images above compare the footprints of the Great Storm of '87 and the storm Kyrill in January 2007. Both of these events caused similar insured losses (6 billion US dollars and 7 billion US dollars respectively, normalised to 2012 index), yet their footprints are very different; the Great Storm of '87 has a narrow and intense footprint, whereas Kyrill is less intense but covers a larger area over Europe.

Having a freely available catalogue such as this is in line with the general movement of greater openness of risk assessments within the (re)insurance industry. It is our hope that open access to this data will generate exciting new ideas, collaboration and innovation.

New science

During the creation of the catalogue, many science questions had to be addressed. One of the main issues was how to define an extreme storm, because unlike for hurricanes, there is currently no widely accepted scale for ranking European windstorms.

After much investigation, the XWS storms were selected by taking the top 50 storms as ranked by the index NUmax3, where N is a measure of the damaging area of the storm (the number of land grid points where the maximum gusts exceeds a threshold of 25 ms-1) and Umax is the maximum 925 hPa wind speed given in the storm track. Theoretically Umax3 is a measure of the advection of kinetic energy of the storm. This index was chosen because it was found to be a good meteorological proxy of storm damage as measured by insured loss.

Another important development was the estimation of uncertainty in the maximum wind gusts, enabled by comparing the storm footprints to observations and the development of a recalibration method to correct for model bias. Since it was found that some storms were simulated better than others, the innovation of the statistical method was to allow for storm-to-storm variation in the recalibration model. This was found to perform much better than applying the same recalibration to each storm.

It is hoped that in the future the catalogue can be extended further into the past, giving us even more understanding of these powerful events.

For further information, please visit the website at, or contact the XWS team by e-mail at Full details of the development of the catalogue can also be found in the recent discussion paper by Roberts et al. (2014).

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