Gust prediction is an important element of weather forecasting services, yet reliable methods remain elusive. Peak wind gusts estimated by the meteorologically stratified gust factor (MSGF) model were evaluated at 15 locations across the United States during 2010-17. This model couples gust factors, site-specific climatological measures of "gustiness," with wind speed and direction forecast guidance. The model was assessed using two forms of model output statistics (MOS) guidance at forecast projections ranging from 1 to 72 h. At 11 of 15 sites the MSGF model showed skill (improvement over climatology) in predicting peak gusts out to projections of 72 h. This has important implications for operational wind forecasting because the method can be utilized at any location for which the meteorologically stratified gust factors have been determined. During particularly windy conditions the MSGF model exhibited skill in predicting peak gusts at forecast projections ranging from 6 to 72 h at roughly half of the sites analyzed. Site characteristics and local wind climatologies were shown to exert impacts on gust factor model performance. The MSGF method represents a viable option for the operational prediction of peak wind gusts, although model performance will be sensitive to the quality of the necessary wind speed and direction forecasts.
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Univ Wisconsin, Dept Math Sci, Atmospher Sci Program, Milwaukee, WI 53201 USAUniv Wisconsin, Dept Math Sci, Atmospher Sci Program, Milwaukee, WI 53201 USA
Harris, Austin R.
Kahl, Jonathan D. W.
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Univ Wisconsin, Dept Math Sci, Atmospher Sci Program, Milwaukee, WI 53201 USAUniv Wisconsin, Dept Math Sci, Atmospher Sci Program, Milwaukee, WI 53201 USA
机构:Sonderforschungsbereich 210, Wind Engineering Division, Institute for Hydrology and Water Resources Planning, University of Karlsruhe, Kaiserstr. 12
WACKER, J
PLATE, EJ
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机构:Sonderforschungsbereich 210, Wind Engineering Division, Institute for Hydrology and Water Resources Planning, University of Karlsruhe, Kaiserstr. 12
机构:
Chongqing Jiaotong Univ, State Key Lab Breeding Base Mt Bridge & Tunnel En, Chongqing 400074, Peoples R China
Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai 200092, Peoples R ChinaChongqing Jiaotong Univ, State Key Lab Breeding Base Mt Bridge & Tunnel En, Chongqing 400074, Peoples R China
Wang Xu
Huang Peng
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Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai 200092, Peoples R ChinaChongqing Jiaotong Univ, State Key Lab Breeding Base Mt Bridge & Tunnel En, Chongqing 400074, Peoples R China
Huang Peng
Yu Xian-feng
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South China Univ Technol, State Key Lab Subtrop Bldg Sci, Guangzhou 510640, Guangdong, Peoples R ChinaChongqing Jiaotong Univ, State Key Lab Breeding Base Mt Bridge & Tunnel En, Chongqing 400074, Peoples R China
Yu Xian-feng
Huang Chao
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机构:
Chongqing Jiaotong Univ, State Key Lab Breeding Base Mt Bridge & Tunnel En, Chongqing 400074, Peoples R ChinaChongqing Jiaotong Univ, State Key Lab Breeding Base Mt Bridge & Tunnel En, Chongqing 400074, Peoples R China
机构:
State Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering,Chongqing Jiaotong University
State Key Laboratory of Disaster Reduction in Civil Engineering,Tongji UniversityState Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering,Chongqing Jiaotong University
王旭
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黄鹏
余先锋
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机构:
State Key Laboratory of Subtropical Building Science,South China University of TechnologyState Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering,Chongqing Jiaotong University
余先锋
黄超
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State Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering,Chongqing Jiaotong UniversityState Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering,Chongqing Jiaotong University