Assessing Hurricane Rainfall Mechanisms Using a Physics-Based Model: Hurricanes Isabel (2003) and Irene (2011)
Assessing Hurricane Rainfall Mechanisms Using a Physics-Based Model: Hurricanes Isabel (2003) and Irene (2011)
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DOI：
10.1175/jas-d-17-0264.1
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发表时间：
2018-07-01
影响因子：
3.1
通讯作者：
Smith, James
中科院分区：
文献类型：
--
作者：
Lu, Ping;Lin, Ning;Smith, James
本文以2003年的飓风伊莎贝尔（Isabel）和2011年的飓风艾琳（Irene）为研究对象，分析了一个基于物理学的热带气旋降水模式（TCR），并应用该模式对影响热带气旋降水强度和空间分布的机制进行了研究。我们使用天气和研究预报（WRF）模型模拟评估TCR模型。TCR产生的降雨场的两个风暴比较以及与WRF估计的方位角平均和空间分布。当与水文模型相结合时，TCR为艾琳生成的特拉华州流域的洪峰与WRF一样准确。TCR占四个主要的降雨机制：表面摩擦辐合，涡拉伸，风暴与地形的相互作用，以及风暴与大尺度斜压性的相互作用。我们发现，这些降雨机制影响的降雨模式不同的伊莎贝尔和艾琳。理论趋同是主导因素，但其他机制也很重要。摩擦收敛取决于边界层公式，这在TCR中相对简单，并且可能需要校准边界层参数。此外，我们发现，TC降水分布强烈依赖于TC风场的时空变化，介导的物理机制由TCR代表。当与各种分析风模型结合使用时，TCR通常可以捕捉到降雨分布，其中荷兰风模型表现最好。鉴于其高计算效率，TCR可以与分析风模型，水文模型和TC气候模型相结合，以生成大量的合成事件，以评估与TC降雨和内陆洪水相关的风险。
We examine a recently developed physics-based tropical cyclone rainfall (TCR) model and apply it to assess the mechanisms that dominate the magnitude and spatial distribution of TC rainfall, with Hurricanes Isabel (2003) and Irene (2011) as study cases. We evaluate the TCR model using Weather and Research Forecasting (WRF) Model simulations. TCR-generated rainfall fields for the two storms compare well with WRF estimates in terms of both azimuthal mean and spatial distributions. When coupled with a hydrologic model, TCR generates flood peaks over the Delaware River basin for Irene as accurately as WRF. TCR accounts for four major rainfall mechanisms: surface frictional convergence, vortex stretching, interaction of the storm with topography, and interaction of the storm with large-scale baroclinity. We show that these rainfall mechanisms affected the rainfall pattern differently for Isabel and Irene. Frictional convergence is the dominant factor, while other mechanisms are also significant. The frictional convergence depends on the boundary layer formulation, which is relatively simple in TCR and may require calibration of boundary layer parameters. Furthermore, we find that the TC rainfall distribution is strongly dependent on the temporal and spatial variation of the TC wind field, mediated by the physical mechanisms represented by TCR. When coupled with various analytical wind models, TCR generally captures the rainfall distribution, with the Holland wind model performing the best. Given its high computational efficiency, TCR can be coupled with an analytical wind model, a hydrological model, and a TC climatology model to generate large numbers of synthetic events to assess the risk associated with TC rainfall and inland flooding.