Seasonal forecast skill for extratropical cyclones and windstorms
Extratropical cyclones and their associated extreme wind speeds are a major cause of vast damage and large insured losses in several European countries. Reliable seasonal predictions of severe extratropical winter cyclones and associated windstorms would thus have great social and economic benefits,...
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| Veröffentlicht in: | Quarterly journal of the Royal Meteorological Society Jg. 145; H. 718; S. 92 - 104 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Chichester, UK
John Wiley & Sons, Ltd
01.01.2019
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| ISSN: | 0035-9009, 1477-870X |
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| Abstract | Extratropical cyclones and their associated extreme wind speeds are a major cause of vast damage and large insured losses in several European countries. Reliable seasonal predictions of severe extratropical winter cyclones and associated windstorms would thus have great social and economic benefits, especially in the insurance sector. We analyse the climatological representation and assess the seasonal prediction skill of wintertime extratropical cyclones and windstorms in three multi‐member seasonal prediction systems: ECMWF‐System3, ECMWF‐System4 and Met Office‐GloSea5, based on hindcasts over a 20‐year period (1992–2011).
Small to moderate positive skill in forecasting the winter frequency of extratropical cyclones and windstorms is found over most of the Northern Hemisphere. The skill is highest for extratropical cyclones at the downstream end of the Pacific storm track and for windstorms at the downstream end of the Atlantic storm track. We also assess the forecast skill of windstorm frequency by using the North Atlantic Oscillation (NAO) as the predictor. Prediction skill improves when using this technique over parts of the British Isles and North Sea in GloSea5 and ECMWF‐System4, but reduces over central western Europe. This suggests that using the NAO is a simple and effective method for predicting windstorm frequency, but that increased forecast skill can be achieved in some regions by identifying windstorms directly using an objective tracking algorithm. Consequently, in addition to the large‐scale influence of the NAO, other factors may contribute to the predictability of windstorm frequency seen in existing forecast suites, across impact‐relevant regions of Europe.
Overall, this study reveals for the first time significant skill in forecasting the winter frequency of high‐impact windstorms ahead of the season in regions that are vulnerable to such events.
In this study, the skill of three state‐of‐the‐art seasonal prediction systems is analysed for Northern Hemisphere extratropical windstorm and cyclone events. Results show significant skill for the eastern Atlantic/central Europe in the latest two systems (see Figure showing rank coefficients of annual track densities for windstorms). Furthermore, using the North Atlantic Oscillation (NAO) as predictor for windstorm activity adds some value over northern Europe but for large areas over Europe using the full model information is superior. |
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| AbstractList | Extratropical cyclones and their associated extreme wind speeds are a major cause of vast damage and large insured losses in several European countries. Reliable seasonal predictions of severe extratropical winter cyclones and associated windstorms would thus have great social and economic benefits, especially in the insurance sector. We analyse the climatological representation and assess the seasonal prediction skill of wintertime extratropical cyclones and windstorms in three multi‐member seasonal prediction systems: ECMWF‐System3, ECMWF‐System4 and Met Office‐GloSea5, based on hindcasts over a 20‐year period (1992–2011).
Small to moderate positive skill in forecasting the winter frequency of extratropical cyclones and windstorms is found over most of the Northern Hemisphere. The skill is highest for
extratropical cyclones
at the downstream end of the Pacific storm track and for
windstorms
at the downstream end of the Atlantic storm track. We also assess the forecast skill of windstorm frequency by using the North Atlantic Oscillation (NAO) as the predictor. Prediction skill improves when using this technique over parts of the British Isles and North Sea in GloSea5 and ECMWF‐System4, but reduces over central western Europe. This suggests that using the NAO is a simple and effective method for predicting windstorm frequency, but that increased forecast skill can be achieved in some regions by identifying windstorms directly using an objective tracking algorithm. Consequently, in addition to the large‐scale influence of the NAO, other factors may contribute to the predictability of windstorm frequency seen in existing forecast suites, across impact‐relevant regions of Europe.
Overall, this study reveals for the first time significant skill in forecasting the winter frequency of high‐impact windstorms ahead of the season in regions that are vulnerable to such events. Extratropical cyclones and their associated extreme wind speeds are a major cause of vast damage and large insured losses in several European countries. Reliable seasonal predictions of severe extratropical winter cyclones and associated windstorms would thus have great social and economic benefits, especially in the insurance sector. We analyse the climatological representation and assess the seasonal prediction skill of wintertime extratropical cyclones and windstorms in three multi‐member seasonal prediction systems: ECMWF‐System3, ECMWF‐System4 and Met Office‐GloSea5, based on hindcasts over a 20‐year period (1992–2011). Small to moderate positive skill in forecasting the winter frequency of extratropical cyclones and windstorms is found over most of the Northern Hemisphere. The skill is highest for extratropical cyclones at the downstream end of the Pacific storm track and for windstorms at the downstream end of the Atlantic storm track. We also assess the forecast skill of windstorm frequency by using the North Atlantic Oscillation (NAO) as the predictor. Prediction skill improves when using this technique over parts of the British Isles and North Sea in GloSea5 and ECMWF‐System4, but reduces over central western Europe. This suggests that using the NAO is a simple and effective method for predicting windstorm frequency, but that increased forecast skill can be achieved in some regions by identifying windstorms directly using an objective tracking algorithm. Consequently, in addition to the large‐scale influence of the NAO, other factors may contribute to the predictability of windstorm frequency seen in existing forecast suites, across impact‐relevant regions of Europe. Overall, this study reveals for the first time significant skill in forecasting the winter frequency of high‐impact windstorms ahead of the season in regions that are vulnerable to such events. In this study, the skill of three state‐of‐the‐art seasonal prediction systems is analysed for Northern Hemisphere extratropical windstorm and cyclone events. Results show significant skill for the eastern Atlantic/central Europe in the latest two systems (see Figure showing rank coefficients of annual track densities for windstorms). Furthermore, using the North Atlantic Oscillation (NAO) as predictor for windstorm activity adds some value over northern Europe but for large areas over Europe using the full model information is superior. |
| Author | Wild, Simon Knight, Jeff R. Leckebusch, Gregor C. Hermanson, Leon Thornton, Hazel E. Lockwood, Julia F. Weisheimer, Antje Befort, Daniel J. Bett, Philip E. |
| Author_xml | – sequence: 1 givenname: Daniel J. orcidid: 0000-0002-2851-0470 surname: Befort fullname: Befort, Daniel J. email: daniel.befort@physics.ox.ac.uk organization: University of Oxford – sequence: 2 givenname: Simon orcidid: 0000-0002-1089-5579 surname: Wild fullname: Wild, Simon organization: Barcelona Supercomputing Center – sequence: 3 givenname: Jeff R. surname: Knight fullname: Knight, Jeff R. organization: Met Office Hadley Centre – sequence: 4 givenname: Julia F. surname: Lockwood fullname: Lockwood, Julia F. organization: Met Office Hadley Centre – sequence: 5 givenname: Hazel E. surname: Thornton fullname: Thornton, Hazel E. organization: Met Office Hadley Centre – sequence: 6 givenname: Leon orcidid: 0000-0002-1062-6731 surname: Hermanson fullname: Hermanson, Leon organization: Met Office Hadley Centre – sequence: 7 givenname: Philip E. orcidid: 0000-0002-4508-7192 surname: Bett fullname: Bett, Philip E. organization: Met Office Hadley Centre – sequence: 8 givenname: Antje orcidid: 0000-0002-7231-6974 surname: Weisheimer fullname: Weisheimer, Antje organization: University of Oxford – sequence: 9 givenname: Gregor C. orcidid: 0000-0001-9242-7682 surname: Leckebusch fullname: Leckebusch, Gregor C. organization: University of Birmingham |
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| Cites_doi | 10.1002/joc.3917 10.1002/2014GL059637 10.1007/s10113-012-0400-8 10.1002/joc.5481 10.3402/tellusa.v66.22830 10.1126/science.269.5224.676 10.5194/nhess-15-1437-2015 10.1007/s00382-013-1850-5 10.1002/qj.2479 10.1002/joc.1982 10.1029/2012JD018020 10.1127/0941-2948/2013/0420 10.1175/JAMC-D-15-0102.1 10.1127/0941-2948/2008/0323 10.1175/BAMS-D-15-00118.1 10.1007/s00382-008-0396-4 10.1038/nclimate2341 10.1175/2011MWR3518.1 10.1016/j.gloplacha.2004.06.011 10.1002/asl.694 10.1002/qj.2396 10.1002/qj.828 10.1175/1520-0434(1999)014<0878:SECBIE>2.0.CO;2 10.1002/qj.2910 10.1002/asl.598 10.1002/qj.625 10.1016/j.jmarsys.2008.11.026 10.1175/MWR3160.1 10.1016/S0074-6142(06)80036-7 10.1007/s00382-013-1975-6 10.1175/BAMS-D-11-00154.1 |
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| Snippet | Extratropical cyclones and their associated extreme wind speeds are a major cause of vast damage and large insured losses in several European countries.... |
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| SubjectTerms | ECMWF‐System3 ECMWF‐System4 extratropical cyclones GloSea5 seasonal forecast seasonal prediction tracking algorithms windstorms |
| Title | Seasonal forecast skill for extratropical cyclones and windstorms |
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