Reexamining the Estimation of Tropical Cyclones Radius of Maximum Wind from Outer Size with an Extensive Synthetic Aperture Radar Dataset

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Arthur Avenas, Alexis Mouche, Pierre Tandeo, Jean-Francois Piolle, Dan Chavas, Ronan Fablet, John Knaff, Bertrand Chapron
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Abstract

The radius of maximum wind (Rmax), an important parameter in tropical cyclones (TCs) ocean surface wind structure, is currently resolved by only a few sensors, so that, in most cases, it is estimated subjectively or via crude statistical models. Recently, a semi-empirical model relying on an outer wind radius, intensity and latitude was fit to best-track data. In this study we revise this semi-empirical model and discuss its physical basis. While intensity and latitude are taken from best-track data, Rmax observations from high-resolution (3 km) spaceborne synthetic aperture radar (SAR) and wind radii from an inter-calibrated dataset of medium-resolution radiometers and scatterometers are considered to revise the model coefficients. The new version of the model is then applied to the period 2010-2020 and yields Rmax reanalyses and trends more accurate than best-track data. SAR measurements corroborate that fundamental conservation principles constrain the radial wind structure on average, endorsing the physical basis of the model. Observations highlight that departures from the average conservation situation are mainly explained by wind profile shape variations, confirming the model’s physical basis, which further shows that radial inflow, boundary layer depth and drag coefficient also play roles. Physical understanding will benefit from improved observations of the near-core region from accumulated SAR observations and future missions. In the meantime, the revised model offers an efficient tool to provide guidance on Rmax when a radiometer or scatterometer observation is available, for either operations or reanalysis purposes.
用大口径合成孔径雷达数据对热带气旋最大风半径估算的再检验
最大风半径(R max)是热带气旋(tc)海洋表面风结构的一个重要参数,目前只有少数传感器能够确定,因此在大多数情况下,它是通过主观或粗糙的统计模型来估计的。最近,一种依赖于外风半径、强度和纬度的半经验模型适合于最佳跟踪数据。本文对这一半经验模型进行了修正,并讨论了其物理基础。虽然强度和纬度来自最佳航迹数据,但考虑了来自高分辨率(3公里)星载合成孔径雷达(SAR)的最大R值观测和来自中分辨率辐射计和散射计的互校准数据集的风半径来修正模型系数。然后,将新版本的模型应用于2010-2020年期间,得到的R max再分析和趋势比最佳跟踪数据更准确。SAR测量证实,基本守恒原理平均约束径向风结构,支持模型的物理基础。观测结果表明,偏离平均守恒状态的主要原因是风廓线形状的变化,证实了模型的物理基础,进一步表明径向入流、边界层深度和阻力系数也起作用。物理认识将受益于积累的SAR观测和未来任务对近核心区域的改进观测。同时,修正后的模式提供了一个有效的工具,当有辐射计或散射计观测时,可以为操作或再分析提供最大R值的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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