Last modified on Oct 09, 2023 16:16

Contributors: Kevin Hodges (University of Reading)

Issued by: Kevin Hodges (University of Reading)

Issued Date: 09/06/2021

Ref:  C3S_435_LOT3_KNMI_2020 – Storm Tracks

Official refence number service contract: 2020/C3S_435_Lot3_KNMI

Acronyms

1. Introduction

European winter wind storms are a major cause of losses to the insurance sector. To help the sector better understand this risk the Operational Wind Storm Service for the Insurance Sector has been developed. The development of the service follows from a Proof of Concept for a Sectorial Information Service to provide information about European wind storms, which is the Windstorm Information Service (WISC), part of the Copernicus Climate Change Service (C3S). This document describes the storm tracking part of the development performed by the University of Reading.

1.1. Executive Summary

The operational storm tracks, available from the Climate Data Store (CDS), are derived from ERA5 reanalysis data for the period 1979 to 2020 using the following methodology. Extratropical cyclones are identified and tracked in the ERA5 reanalysis data for the October to March periods of 1979-2020 using an automated cyclone tracking algorithm based on the method described by Hodges (1995, 1999) and previously used for WISC and XWS (Roberts et al, 2014). Major European wind storms are identified (118) based on region and simple wind intensity criteria which are subsequently downscaled in the storm footprinting part of the system. The 118 storms for this period was the result of the application of a 25m/s threshold with minor adjustments to include additional well known storms just below this value.

1.2. Scope of Documentation

This document describes the C3S Storm Track dataset using the standard C3S format for product descriptions, i.e., in terms of product target requirements, product overview, input data and methodology as well as use of the dataset. It is the primary document for users.

1.3. Version History

Version 1.0. The underlying methodology used to derive the storm tracks has been consistent within this project and the previous proof of concept contract, WISC.

2. Product Description

2.1. Product Target Requirements

The cyclone track dataset consists of the most intense European wind storms in the period 1979-2020 of which there are 118. The track database provides information on the locations and intensities of the cyclones of use to the Insurance industry in combination with the storm footprinting and wind storm economic loss calculations which constitute the complete C3S windstorm operational system.

Extratropical cyclones are identified and tracked in the ERA5 reanalysis data using the 3-hourly data for the October to March periods of 1979-2020 using an automated cyclone tracking algorithm based on the method described by Hodges (1995,1999) following the approach used in Hoskins and Hodges (2002) and previously used for WISC and XWS. This method uses the 850 hPa relative vorticity (at T42 resolution, which corresponds to about 480 km) to identify and track the cyclones over the full lifecycles in the northern hemisphere. For a feature to be tracked it must reach a relative vorticity maximum greater than 1×10−5s−1 in the filtered vorticity and post tracking the tracks are filtered to retain those that last for a least 1 day and travel more than 1000km.

Following the tracking other variables are added to the tracks by searching for the nearest pressure minimum with a 5° radius (geodesic) of the vorticity centre as well as the maximum winds at 925hPa and 10m within a 6° radius of the vorticity centre and the wind maxima (925hPa and 10m) over the land masses of Europe (15W-25E, 35N-70N) within a 3° radius of the vorticity centre. The last are obtained by first masking the wind field using the land-sea mask from the reanalysis before sampling the data along the tracks. The additional field information is determined at the full reanalysis resolution. A plot of all tracks is shown in Figure 1.

The spatial range requirement for the tracks is Pan-European approximately covering an area defined by 15W to 25E, 35N to 70N though in fact the storms were tracked over their full course from formation over the Atlantic.

Storms, identified for downscaling and footprinting, and are selected by applying a threshold value of 25m/s to land only 10m wind speeds attached to the tracks. Some tracks identified in the original XWS and WISC catalogue are not selected based on this criterion but because they are considered as important storms for the insurance industry, they were also identified and added to the sample. The number of selected tracks is 118.

Figure 1: Tracks selected for downscaling. Coloured dots indicate the 10m wind speeds within the 60 search radius.

2.2. Product Overview

The Operational Storm Tracks consist of 118 cyclone tracks that impact Europe with wind speeds above 25m/s together with additional cyclones of importance to the insurance industry.

2.2.1. Data Description

Table 1: Overview of key characteristics of the Operational Storm Tracks dataset.

2.2.2. Variable Description

The tracks, which are provided in asci format, include the following fields:

• Time
• longitude of vorticity maximum
• latitude of vorticity maximum
• maximum T42 850 hPa relative vorticity
• longitude of Mean Sea Level Pressure (MSLP) minimum within 5° of vorticity centre
• latitude of MSLP minimum
• minimum MSLP
• longitude of 925 hPa wind speed maxima within 6° of vorticity centre
• latitude of 925 hPa wind speed maxima
• maximum 925 hPa wind speed
• longitude of 10m wind speed maxima within 6° of vorticity centre
• latitude of 10m wind speed maxima
• maximum 10m wind speed
• longitude of 925 hPa wind speed over land within 3° of vorticity centre
• latitude of 925 hPa wind speed over land
• maximum 925 hPa wind speed over land
• longitude of 10m wind speed over land within 3° of vorticity centre
• latitude of 10m wind speed over land
• maximum 10m wind speed over land

Missing values are delineated by a value of 1.0e+25.

Table 2. Overview and description of variables.

2.3. Input Data

The input data to the cyclone track production is summarised in Table 3 and described below.

Table 3: Overview of climate model data for input to Operational Storm Track, summarizing the model properties and available scenario simulations.

2.3.1. Input Data 1

ERA5 Reanalysis
Data from the ECMWF ERA5 reanalysis (Hersbach et al, 2020) extracted directly from the mars archive for the period 1979-2020 at 3 hourly intervals for the seasonal period of October to March when the majority of European wind storms occur. The 850hPa relative vorticity is spectrally filtered prior to applying the tracking algorithm. Full resolution MSLP, 925hPa winds and 10m winds are also added to the cyclone tracks.

2.4. Method

2.4.1. Background

The same tracking methodology has been applied to the ECMWF ERA5 data set as was used with ERA- Interim (Dee et al, 2011) in the C3S Proof of Concept contract Wind Storm Information Service (WISC¹) and eXtreme Wind Storms' (XWS²) catalogue (Roberts et al, 2014) projects. However, since ERA5 has 3-hourly analyses there is no need to use the forecast splicing to get 3-hourly data as was used for WISC and XWS. The ERA5 3 hourly analysis fields are used to be consistent with WISC and XWS.

2.4.2. Model / Algorithm

The 850hPa relative vorticity is first spectrally smoothed to T42 and the large-scale background removed in Hoskins and Hodges (2002), this reduces the inherent noisiness of the vorticity and makes the tracking more reliable. The cyclones are identified by determining the vorticity maxima by steepest ascent maximization on a polar stereographic projection in the filtered data as described in Hodges (1995). These feature points are linked together, initially using a nearest-neighbour search, and then refined by minimising a cost function for track smoothness (Hodges,1995) subject to adaptive constraints on the displacement distance and track smoothness (Hodges,1999). These constraints have been modified from those used for 6-hourly data to be suitable for the 3-hourly data. Storms that last longer than 1 day are retained for further analysis.

The MSLP minima and 925 hPa and 10m wind speed maxima associated with the vorticity maxima are added to the tracks. This is done by searching for a minimum/maximum within a certain radius of the vorticity maximum. A radius of 5° is used for the MSLP. For the 925 hPa and 10m wind speed, radii of 3° and 6° as these were found to be the best indicators of storm severity (Roberts et al 2014). For MSLP the minima are determined using a steepest descent minimization method, while for winds a direct search of the grid point values is used. For the MSLP the location of the minimum is only given if it is a true minimum. If not, the MSLP value given is that at the vorticity centre. For the winds the search is made for both the full fields and the land only fields.

2.4.3. Validation

Unlike for Tropical Cyclones where observational tracks and intensities are produced by the different operational centre's called Best Track data, there is no such data set for extra-tropical cyclones and effectively no "truth" to contrast with for the quality of the cyclone tracks. Therefore, the assessment of the cyclone tracks is made by comparing track locations and intensities with those obtained previously from ERA-Interim for WISC for the region 15W to 25E and 35N to 70N to highlight the uncertainties. The first comparison is for the total number of cyclones found in the region that have lifetimes more than 1 day and travel more than 1000km.

Using cyclone matching between ERA5 and ERA-Interim for the European region and for the period 1979-2018 we can obtain how many cyclones match, the mean separation distances and temporal overlap for the cyclones that match and the intensity distributions for the cyclones that do and do not match. The matching is performed using the criteria of a mean separation distance less than 4° and temporal overlap greater than 50% of pair of track points. Based on the above criteria 175.5 and 181.54 storm tracks were found on average per season in the region from ERA-Interim and ERA5 respectively. The overlap (storm tracks selected from both ERA-Interim and ERA5) amounts to

152.24 storm tracks (on average), which corresponds to 87% and 84% of identified storms from ERA- Interim and ERA5 respectively. Relaxing the temporal overlap to 25% changes the matches to 156.62 (89% and 86%). The temporal overlap and separation distances for different intensity metrics are shown in Figure 2. This shows that the actual tracks have very similar lengths in both ERA5 and ERA- Interim. For the intensities, the tracked T42 vorticity centres indicate very similar locations for the storms at the time of the maximum intensity within the region, however, for the full resolution MSLP minima the distribution is broader indicating larger differences for location based on this measure of intensity. For the maximum winds, 925hPa or 10m over land, the distributions for location are broader still indicating a larger differences in the locations of the maximum winds between ERA5 and ERA-Interim. Figure 3 shows that the maximum winds within the region for the cyclones are larger for ERA5 than ERA-Interim at both 925hPa (full winds) and 10m (land masked).

Figure 2: PDF's of temporal overlap (red) and separation distances of T42 vorticity maxima (black), MSLP minima (blue), maximum 925hPa winds (green) and maximum 10m winds over land (violet) between ERA5 and ERA-Interim.

Figure 3: Maximum intensity distributions for 925hPa and 10m winds (land) for ERA5 and ERA- Interim.

3. Concluding Remarks

The operational storm tracks are derived from ERA5 reanalysis data for the period 1979 to 2021. Extratropical cyclones are identified and tracked in the ERA5 reanalysis data for the October to March periods of 1979-2021 using an automated cyclone tracking algorithm based on the method described by Hodges (1995, 1999) and previously used for WISC and XWS (Roberts et al, 2014). 118 European wind storms are identified based on region and simple wind intensity criteria, which are subsequently downscaled in the storm footprinting part of the system. The 118 storms for this period was the result of the application of a 25m/s threshold with minor adjustments to include additional well-known storms just below this value. The storm tracks were used as the basis for the statistical downscaling of storm footprints.

The track data should not be considered as the same as Best Track data, as produced for Tropical Cyclones, as it is dependent on the reanalysis used to produce the tracks. Comparisons between cyclone tracks identified in different reanalyses have shown a good correspondence between the tracks but varying degrees of uncertainty in the intensities depending on what intensity variable is considered (Hodges et al, 2011). It should also be noted that different cyclone tracking schemes can produce different tracks depending on whether vorticity or MSLP is used as the tracking variables, although the correspondence for the most intense storms is better than for the weak storms (Neu et al, 2013).

References

Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553-597.

Hersbach, H, Bell, B, Berrisford, P, et al. The ERA5 global reanalysis. Q J R Meteorol Soc. 2020; 146: 1999– 2049.

Hodges, K. I. (1995) Feature tracking on the unit-sphere. Monthly Weather Review, 123 (12): 3458- 3465. doi:10.1175/1520-0493(1995)123;

Hodges, K.I. (1999) Adaptive Constraints for Feature Tracking, Mon. Weather Rev., V127, 1362-1373.

Hoskins, B. J. and Hodges, K. I. (2002) New Perspectives on the North-ern Hemisphere Winter Storm Tracks, J. Atmos. Sci., 59, 1041–1061.

K. I. Hodges, R. W. Lee and L. Bengtsson, (2013). A Comparison of Extratropical Cyclones in Recent Reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25 , J. Clim. , 24, 4888-4906.

Neu U. , Akperov M. G. , Bellenbaum N. , Benestad R. , Blender R. , co-authors . IMILAST: a community effort to intercompare extratropical cyclone detection and tracking algorithms. Bull. Am. Meteorol. Soc. 2013; 94: 529–547.

Roberts, J. F., Champion, A. J., Dawkins, L. C., Hodges, K. I., Shaffrey, L. C., Stephenson, D. B., Stringer,

M. A., Thornton, H. E., and Youngman, B. D. (2014) The XWS open access catalogue of extreme European windstorms from 1979 to 2012, Nat. Hazards Earth Syst. Sci., 14, 2487-2501

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