Julia F. Lockwood, N. Dunstone, L. Hermanson, G. Saville, Adam A. Scaife, Doug M. Smith, H. Thornton
{"title":"为保险提供的年代际气候服务:北大西洋飓风活动和美国飓风损害的熟练多年预测","authors":"Julia F. Lockwood, N. Dunstone, L. Hermanson, G. Saville, Adam A. Scaife, Doug M. Smith, H. Thornton","doi":"10.1175/jamc-d-22-0147.1","DOIUrl":null,"url":null,"abstract":"\nNorth Atlantic hurricane activity exhibits significant variation on multi-annual timescales. Advance knowledge of periods of high activity would be beneficial to the insurance industry, as well as society in general. Previous studies have shown that climate models initialized with current oceanic and atmospheric conditions, known as decadal prediction systems, are skilful at predicting North Atlantic hurricane activity averaged over periods of 2-10 years. We show that this skill also translates into skilful predictions of real-world US hurricane damages. Using such systems, we have developed a prototype climate service for the insurance industry giving probabilistic forecasts of 5-year-mean North Atlantic hurricane activity, measured by the total accumulated cyclone energy (ACE index), and 5-year-total US hurricane damages (given in US dollars). Rather than tracking hurricanes in the decadal systems directly, the forecasts use a relative temperature index known to be strongly linked to hurricane activity. Statistical relationships based on past forecasts of the index and observed hurricane activity and US damages are then used to produce probabilistic forecasts. The predictions of hurricane activity and US damages for the coming period 2020-2024 are high, with ~95% probabilities of being above average. We note that skill in predicting the temperature index on which the forecasts are based has declined in recent years. More research is therefore needed to understand under which conditions the forecasts are most skilful.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A decadal climate service for insurance: Skilful multi-year predictions of North Atlantic hurricane activity and US hurricane damage\",\"authors\":\"Julia F. Lockwood, N. Dunstone, L. Hermanson, G. Saville, Adam A. Scaife, Doug M. Smith, H. Thornton\",\"doi\":\"10.1175/jamc-d-22-0147.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nNorth Atlantic hurricane activity exhibits significant variation on multi-annual timescales. Advance knowledge of periods of high activity would be beneficial to the insurance industry, as well as society in general. Previous studies have shown that climate models initialized with current oceanic and atmospheric conditions, known as decadal prediction systems, are skilful at predicting North Atlantic hurricane activity averaged over periods of 2-10 years. We show that this skill also translates into skilful predictions of real-world US hurricane damages. Using such systems, we have developed a prototype climate service for the insurance industry giving probabilistic forecasts of 5-year-mean North Atlantic hurricane activity, measured by the total accumulated cyclone energy (ACE index), and 5-year-total US hurricane damages (given in US dollars). Rather than tracking hurricanes in the decadal systems directly, the forecasts use a relative temperature index known to be strongly linked to hurricane activity. Statistical relationships based on past forecasts of the index and observed hurricane activity and US damages are then used to produce probabilistic forecasts. The predictions of hurricane activity and US damages for the coming period 2020-2024 are high, with ~95% probabilities of being above average. We note that skill in predicting the temperature index on which the forecasts are based has declined in recent years. 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A decadal climate service for insurance: Skilful multi-year predictions of North Atlantic hurricane activity and US hurricane damage
North Atlantic hurricane activity exhibits significant variation on multi-annual timescales. Advance knowledge of periods of high activity would be beneficial to the insurance industry, as well as society in general. Previous studies have shown that climate models initialized with current oceanic and atmospheric conditions, known as decadal prediction systems, are skilful at predicting North Atlantic hurricane activity averaged over periods of 2-10 years. We show that this skill also translates into skilful predictions of real-world US hurricane damages. Using such systems, we have developed a prototype climate service for the insurance industry giving probabilistic forecasts of 5-year-mean North Atlantic hurricane activity, measured by the total accumulated cyclone energy (ACE index), and 5-year-total US hurricane damages (given in US dollars). Rather than tracking hurricanes in the decadal systems directly, the forecasts use a relative temperature index known to be strongly linked to hurricane activity. Statistical relationships based on past forecasts of the index and observed hurricane activity and US damages are then used to produce probabilistic forecasts. The predictions of hurricane activity and US damages for the coming period 2020-2024 are high, with ~95% probabilities of being above average. We note that skill in predicting the temperature index on which the forecasts are based has declined in recent years. More research is therefore needed to understand under which conditions the forecasts are most skilful.
期刊介绍:
The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.