Lauren E. Pounds, Conrad L. Ziegler, Rebecca D. Adams-Selin, Michael I. Biggerstaff
{"title":"2012年5月29日模拟冰雹轨迹对冰雹产生的分析","authors":"Lauren E. Pounds, Conrad L. Ziegler, Rebecca D. Adams-Selin, Michael I. Biggerstaff","doi":"10.1175/mwr-d-23-0073.1","DOIUrl":null,"url":null,"abstract":"Abstract This study uses a new, unique dataset created by combining multi-Doppler radar wind and reflectivity analysis, diabatic Lagrangian analysis (DLA) retrievals of temperature and water substance, and a complex hail trajectory model to create millions of numerically simulated hail trajectories in the Kingfisher, OK supercell on 29 May 2012. The DLA output variables are used to obtain a realistic, 4-D depiction of the storm's thermal and hydrometeor structure as required input to the detailed hail growth trajectory model. Hail embryos are initialized in the hail growth module every three minutes of the radar analysis period (2251-0000 UTC) to produce over 2.7 million hail trajectories. A spatial integration technique considering all trajectories is used to identify locations within the supercell where melted particles, sub-severe, and severe hailstones reside in their lowest and highest concentrations. It is found that hailstones are more likely to reside for longer periods closer to the downshear updraft within the midlevel mesocyclone in a region of decelerated mid-level mesocyclonic horizontal flow, termed the downshear deceleration zone (DDZ). Additionally, clusters of trajectories are analyzed using a trajectory clustering method. Trajectory clusters show there are many trajectory pathways that result in hailstones ≥ 4.5 cm, including trajectories that begin upshear of the updraft away from ideal growth conditions and trajectories that grow within the DDZ. There are also trajectory clusters with similar shapes, yet experience widely different environmental and hailstones characteristics along the trajectory.","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":"4 3","pages":"0"},"PeriodicalIF":2.8000,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Hail Production via Simulated Hailstone Trajectories in the 29 May 2012 Kingfisher, OK Supercell\",\"authors\":\"Lauren E. Pounds, Conrad L. Ziegler, Rebecca D. Adams-Selin, Michael I. Biggerstaff\",\"doi\":\"10.1175/mwr-d-23-0073.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This study uses a new, unique dataset created by combining multi-Doppler radar wind and reflectivity analysis, diabatic Lagrangian analysis (DLA) retrievals of temperature and water substance, and a complex hail trajectory model to create millions of numerically simulated hail trajectories in the Kingfisher, OK supercell on 29 May 2012. The DLA output variables are used to obtain a realistic, 4-D depiction of the storm's thermal and hydrometeor structure as required input to the detailed hail growth trajectory model. Hail embryos are initialized in the hail growth module every three minutes of the radar analysis period (2251-0000 UTC) to produce over 2.7 million hail trajectories. A spatial integration technique considering all trajectories is used to identify locations within the supercell where melted particles, sub-severe, and severe hailstones reside in their lowest and highest concentrations. It is found that hailstones are more likely to reside for longer periods closer to the downshear updraft within the midlevel mesocyclone in a region of decelerated mid-level mesocyclonic horizontal flow, termed the downshear deceleration zone (DDZ). Additionally, clusters of trajectories are analyzed using a trajectory clustering method. Trajectory clusters show there are many trajectory pathways that result in hailstones ≥ 4.5 cm, including trajectories that begin upshear of the updraft away from ideal growth conditions and trajectories that grow within the DDZ. 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Analysis of Hail Production via Simulated Hailstone Trajectories in the 29 May 2012 Kingfisher, OK Supercell
Abstract This study uses a new, unique dataset created by combining multi-Doppler radar wind and reflectivity analysis, diabatic Lagrangian analysis (DLA) retrievals of temperature and water substance, and a complex hail trajectory model to create millions of numerically simulated hail trajectories in the Kingfisher, OK supercell on 29 May 2012. The DLA output variables are used to obtain a realistic, 4-D depiction of the storm's thermal and hydrometeor structure as required input to the detailed hail growth trajectory model. Hail embryos are initialized in the hail growth module every three minutes of the radar analysis period (2251-0000 UTC) to produce over 2.7 million hail trajectories. A spatial integration technique considering all trajectories is used to identify locations within the supercell where melted particles, sub-severe, and severe hailstones reside in their lowest and highest concentrations. It is found that hailstones are more likely to reside for longer periods closer to the downshear updraft within the midlevel mesocyclone in a region of decelerated mid-level mesocyclonic horizontal flow, termed the downshear deceleration zone (DDZ). Additionally, clusters of trajectories are analyzed using a trajectory clustering method. Trajectory clusters show there are many trajectory pathways that result in hailstones ≥ 4.5 cm, including trajectories that begin upshear of the updraft away from ideal growth conditions and trajectories that grow within the DDZ. There are also trajectory clusters with similar shapes, yet experience widely different environmental and hailstones characteristics along the trajectory.
期刊介绍:
Monthly Weather Review (MWR) (ISSN: 0027-0644; eISSN: 1520-0493) publishes research relevant to the analysis and prediction of observed atmospheric circulations and physics, including technique development, data assimilation, model validation, and relevant case studies. This research includes numerical and data assimilation techniques that apply to the atmosphere and/or ocean environments. MWR also addresses phenomena having seasonal and subseasonal time scales.