1980–2010 Variability in U.K. Surface Wind Climate
The climate of the northeast Atlantic region comprises substantial decadal variability in storminess. It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate...
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description | The climate of the northeast Atlantic region comprises substantial decadal variability in storminess. It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameterkspatially varying from 1.4 to 2.1, highlighting that the commonly assumedk= 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors’ analyses place the particularly ‘‘low wind’’ year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. The findings are discussed in the context of current existing challenges to improve predictability in the Euro-Atlantic sector over all time scales. |
doi_str_mv | 10.1175/JCLI-D-12-00026.1 |
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It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameterkspatially varying from 1.4 to 2.1, highlighting that the commonly assumedk= 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors’ analyses place the particularly ‘‘low wind’’ year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. 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It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameterkspatially varying from 1.4 to 2.1, highlighting that the commonly assumedk= 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors’ analyses place the particularly ‘‘low wind’’ year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. 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Variability in U.K. Surface Wind Climate</title><author>Earl, Nick ; Dorling, Steve ; Hewston, Richard ; von Glasow, Roland</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c389t-a67ce47a0ce9307a4544b846bb4370ec542efca61fc211b5cc3ca6954c47df333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>20th century</topic><topic>Annual variations</topic><topic>Bgi / Prodig</topic><topic>Climate</topic><topic>Climate change</topic><topic>Climatic zones</topic><topic>Cold</topic><topic>Context</topic><topic>Distribution</topic><topic>Earth, ocean, space</topic><topic>Energy</topic><topic>Energy density</topic><topic>Energy industry</topic><topic>Europe</topic><topic>Exact sciences and technology</topic><topic>External geophysics</topic><topic>Flux density</topic><topic>Insurance</topic><topic>Insured losses</topic><topic>Interannual variability</topic><topic>International 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It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameterkspatially varying from 1.4 to 2.1, highlighting that the commonly assumedk= 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors’ analyses place the particularly ‘‘low wind’’ year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. The findings are discussed in the context of current existing challenges to improve predictability in the Euro-Atlantic sector over all time scales.</abstract><cop>Boston, MA</cop><pub>American Meteorological Society</pub><doi>10.1175/JCLI-D-12-00026.1</doi><tpages>20</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 20th century Annual variations Bgi / Prodig Climate Climate change Climatic zones Cold Context Distribution Earth, ocean, space Energy Energy density Energy industry Europe Exact sciences and technology External geophysics Flux density Insurance Insured losses Interannual variability International studies Low wind speeds Meteorology Networks Physical geography Rayleigh distribution Seasons Storm damage Storms Surface wind The British Isles Variability Weibull distribution Wind Wind data Wind direction Wind measurement Wind power Wind power generation Wind speed Wind turbines Wind variability Wind velocity Winds Winds and their effects Winter |
title | 1980–2010 Variability in U.K. Surface Wind Climate |
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