Evaluation of Parametric Tropical Cyclone Surface Winds over the Eastern Australian Region

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Monthly Weather Review Pub Date : 2024-01-01 DOI:10.1175/mwr-d-23-0063.1
Julian O’Grady, Hamish Ramsay, Kathy McInnes, Rebecca Gregory
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Abstract

Hazard studies based on thousands of synthetic tropical cyclone (TC) events require a validated model representation of the surface wind field. Here, we assess three different TC parametric vortex models with input from four along-track parameter studies of the TC size and shape, based on statistical formulation of the relationships to observed TC intensity, geographic location, and forward transition speed. The 12 model combinations are compared to in situ 10-min observed surface mean wind speeds for 10 TCs that made landfall over Queensland, Australia, which occurred over the period 2006–17. Empirical wind reduction factors to reduce gradient winds to the surface are recalculated for the more recent TCs at both offshore (ocean, small islands, reefs, and moorings) and onshore (land) locations. To improve the wind comparisons over ocean and land, a secondary reduction factor was developed based on an inland decay function. Pearson correlations for the unadjusted modeled peak wind speed from 118 instances of a TC passing a weather station sit between a range of 0.57 and 0.65 for the 12 model combinations. Using the secondary reduction factor based on the inland decay function increases the range of correlation to 0.74–0.81. Based on the assessment of the instances of peak surface wind speed correlations, bias, and root-mean-square error, along with the correlation 48 h around the peak, the top-ranked performing model combination for the region was an along-track parameter study with a double-vortex model, both previously tested for the South Pacific basin. When assessing tropical cyclone hazards, users are presented with several simplified parametric models to describe the surface wind field of tropical cyclones. These parametric models are used routinely for risk assessment of cyclonic winds, as well as for input to surge and wave models used in coastal hazard assessments. Differences between the models include the formulation of the parametric cyclone model, the way winds above the boundary layer are specified at the surface and along-track parameters that describe the cyclones’ size and shape. Of the 12 model combinations investigated in this study, the top-ranked performing model combination for the region was an along-track parameter equation with a double-vortex model, which were both tested previously for the South Pacific basin. Analysis is performed to show unadjusted modeled winds overestimate observed 10-min surface winds over the ocean by around 13% (median) and over land by around 73.9% (median), which is resolved in this study with a secondary empirical wind reduction factor. These findings will support future modeling of tropical cyclone winds for multiple applications, including regional risk assessment and coastal hazard studies.
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澳大利亚东部地区热带气旋表面风参数评估
基于数千个合成热带气旋(TC)事件的危害研究需要一个经过验证的模式来表示表面风场。在此,我们评估了三种不同的热带气旋参数涡旋模式,这些模式的输入来自对热带气旋大小和形状进行的四次沿路径参数研究,其基础是观测到的热带气旋强度、地理位置和前向过渡速度之间关系的统计公式。将 12 个模型组合与 2006-17 年期间在澳大利亚昆士兰登陆的 10 个热带气旋的现场 10 分钟观测表面平均风速进行了比较。对近海(海洋、小岛屿、礁石和系泊设施)和陆地(陆地)位置的近期热带气旋重新计算了经验风力减弱系数,以减弱地表的梯度风力。为了改进海洋和陆地的风力比较,根据内陆衰减函数开发了一个二次衰减因子。在 12 个模式组合中,118 次经过气象站的热带气旋的未调整模式峰值风速的皮尔逊相关性介于 0.57 和 0.65 之间。使用基于内陆衰减函数的二次缩减因子后,相关范围增加到 0.74-0.81。根据对峰值表面风速相关性、偏差和均方根误差的评估,以及峰值周围 48 小时的相关性,该地区表现最好的模式组合是沿路径参数研究和双涡旋模式,这两种模式之前都在南太平洋盆地进行过测试。这些参数模式通常用于气旋风的风险评估,以及用于沿岸灾害评估的浪涌和波浪模式的输入。这些模式之间的差异包括参数气旋模式的表述、边界层以上的地表风的指定方式以及描述气旋大小和形状的沿迹参数。在本研究调查的 12 个模式组合中,该地区表现最好的模式组合是沿迹参数方程和双涡旋模式,这两个模式以前都在南太平洋海盆进行过测试。分析表明,未经调整的模式风高估了海洋上空约 13%(中位数)和陆地上空约 73.9%(中位数)的 10 分钟观测到的地面风,本研究利用二级经验风减弱因子解决了这一问题。这些研究结果将为未来热带气旋风建模的多种应用提供支持,包括区域风险评估和沿海灾害研究。
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来源期刊
Monthly Weather Review
Monthly Weather Review 地学-气象与大气科学
CiteScore
6.40
自引率
12.50%
发文量
186
审稿时长
3-6 weeks
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.
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