Selecting the storms

Fifty of the most extreme storms of the 5730 that passed through the region 15°W-25°E, 35°N-70°N in the period 1979-2013 have been selected for the XWS catalogue. The challenge when selecting these storms was defining an `extreme storm'. A storm can be defined as extreme in many ways, for example in terms of a meteorological index, or extreme values of insured losses.

Insurance loss storms

An initial list of insurance loss storms (hereafter `insurance storms' ) was compiled after consultation with Willis Research Network, containing 22 storms that had caused large insurance losses. Of these 22, only one (Capella, January 1976) was not in the period covered by ERA-Interim and was therefore excluded from the list. In addition to these 21 events, a further 2 events, which were known to have caused significant damage and were well researched, were included as being typical of the type of event that we wished to capture in the catalogue.

There were numerous other events that were considered, e.g. polar lows and other named storms, however they were not included due to either not causing damage over Europe (the polar lows) or due to there being very little information on them. The final list included 23 'insurance' events; these are the named storms in the table below, as opposed to storms identified by dates (e.g. Nov 84).

The aim for this catalogue was to find an optimal meteorological index that could capture the high insurance loss storms (by ranking them highly), and identify other similar events that were not recorded as high loss. These other storms may not have recorded high insurance losses either because they missed large urban areas, or because of incomplete loss data records.

Meteorological Indices

Meteorological indices from both the track and footprint of the storm were investigated. These indices included the maximum wind speed of the storm (U_max), defined as the maximum 925hPa wind speed (from ERA-Interim) over the Continental European land mass within a 3° radius of the cyclone track. Radii of 6° and 10° were considered, both resulting in a slightly poorer performance by the index (i.e. the insurance storms tended to be ranked lower when ranked by this index).

The size of the storm (N) was also considered, defined as the number of footprint grid points over European and Scandinavian land for which the maximum gust exceeds 25ms-1, which is proportional to the land area exceeding this threshold. A threshold of 25ms^-1 was used as it is recognised as being the wind speed at which damage starts to occur. The use of a relative local 98^th percentile threshold, as used by Klawa & Ulbrich (2003), was also considered. This resulted in the selection of relatively weak, small scale Mediterranean storms (`medicanes') which are not well represented in the re-analysis data.

Indices U_max and N can be combined to form a storm severity index (SSI). The SSIs tested were (i) S_ft, derived by combining the track index (U_max)³ (intensity) and footprint index N (size):

S_ft = (U_max)³ N,

and (ii), S_f, which is estimated only from the footprint data, defined as the sum of the excess gust speed cubed at grid points over European and Scandinavian land:

Sf   =   ΣU>25(U-25)3

Results

The index S_ft was found to be the most successful index at identifying the insurance loss storms, i.e. when ranking storms by this index, the insurance loss storms ranked higher compared to the other indices. This index depends on both the area and maximum wind speed intensity of the storm. The index S_ft selects storms located over the UK and Northern Europe and samples storms over the full time period of the XWS catalogue hence giving a good representation of the meteorologically extreme and severe Atlantic storms that occurred throughout the period. For these reasons we have chosen to use S_ft to select the 50 storms for the XWS catalogue.

A more detailed discussion of the results will be given in the forthcoming paper (link to come).

Table showing the meteorological index values for the 50 storms selected for the XWS catalogue

Rank in Sft	Name	Date of Umax	Umax (ms-1)	N	Sft(x106)
1	Jeanette	27 Oct 2002	36.92	1497	75.37
2	Kyrill	18 Jan 2007	36.38	1234	59.43
3	Nov 84	23 Nov 1984	35.54	1300	58.36
4	Dec 93	8 Dec 1993	36.97	980	49.52
5	13 Jan 93	13 Jan 1993	40.48	734	48.70
6	Daria (Burns' Day Storm	25 Jan 1990	37.92	881	48.05
7	Anatol	3 Dec 1999	39.86	742	47.01
8	23 Jan 93	23 Jan 1993	36.54	882	43.04
9	Vivian	26 Feb 1990	35.16	940	40.86
10	Great storm of 87 (87J)	16 Oct 1987	39.53	622	38.42
11	Oratia (Tora)	30 Oct 2000	38.45	645	36.67
12	Erwin (Gudrun)	8 Jan 2005	39.22	598	36.08
13	Nov 81	2 Nov 1981	36.01	687	32.07
14	Jan 86	20 Jan 1986	31.86	921	29.77
15	13 Jan 84	13 Jan 1984	33.75	716	27.53
16	14 Jan 84	14 Jan 1984	34.71	649	27.14
17	Oct 86	20 Oct 1986	35.80	584	26.79
18	5 Jan 91	5 Jan 1991	38.52	449	25.67
19	Wiebke	28 Feb 1990	32.24	751	25.16
20	Nov 92	25 Nov 1992	39.07	418	24.93
21	Klaus	24 Jan 2009	37.23	472	24.36
22	Feb 83	1 Feb 1983	32.29	718	24.16
23	Xynthia	27 Feb 2010	32.62	666	23.11
24	Jan 02	28 Jan 2002	34.23	551	22.10
25	Dec 11	16 Dec 2011	40.02	342	21.91
26	Martin	27 Dec 1999	37.18	415	21.33
27	Stephen	26 Dec 1998	39.53	317	19.58
28	Ulli	3 Jan 2012	36.32	397	19.02
29	8 Jan 91	8 Jan 1991	35.97	407	18.94
30	Lothar	26 Dec 1999	36.72	380	18.82
31	Nov 88	29 Nov 1988	30.84	625	18.33
32	Nov 96	6 Nov 1996	36.19	385	18.26
33	Jan 83	18 Jan 1983	34.53	436	17.94
34	Gero	11 Jan 2005	39.13	293	17.55
35	Feb 88	9 Feb 1988	35.79	380	17.42
36	Jan 95	22 Jan 1995	36.33	356	17.07
37	Oct 96	28 Oct 1996	35.87	368	16.98
38	11 Feb 90	11 Feb 1990	31.90	515	16.72
39	Mar 86	25 Mar 1986	30.77	563	16.40
40	Feb 09	9 Feb 2009	31.54	510	16.00
41	Feb 96	7 Feb 1996	33.66	418	15.94
42	Herta	3 Feb 1990	33.16	437	15.94
43	Mar 97	28 Mar 1997	31.22	523	15.92
44	8 Feb 90	8 Feb 1990	35.02	370	15.90
55	Lore	28 Jan 1994	31.60	438	13.82
57	Yuma	24 Dec 1997	39.92	205	13.04
62	Fanny	4 Jan 1998	34.60	297	12.30
63	Emma	29 Feb 2008	25.12	768	12.17
123	Xylia	28 Oct 1998	26.72	295	5.63
309	Dagmar (Patrick)	26 Dec 2011	30.08	65	1.77

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