Waves produced by tropical cyclones (TCs) can be estimated using non-stationary wave models forced with time-varying wind fields. However, dynamical simulations are time and computationally demanding at regional-scale domains since high temporal and spatial resolutions are required to correctly simulate TC-induced wave propagation processes. Applications such as early warning systems, coastal risk assessments and future climate projections benefit from fast and accurate estimates of wave fields induced by close-to-real storm tracks geometry. The proposed SHyTCWaves methodology constitutes a novel tool capable of estimating the spatio-temporal variability of directional wave spectra produced by TCs in deep waters, using a hybrid approach and statistical techniques to reduce CPU time effort. This work demonstrates that TC-induced waves can be reconstructed using a stop-motion approach based on the addition of successive 6 h periods of time-varying storm conditions. The developed hybrid model reduces a TC track to a number of segments that are parameterized in terms of 10 representative TC features, and generates a library of cases dynamically pre-computed which allow to ensemble consecutive 6 h analog segments representing the original TC track. The metamodel has been compared and corrected with available satellite data, and its applicability is exemplified for TC Ofa in the South Pacific.

中文翻译：

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SHyTCWaves：预测热带气旋诱发波的定格运动混合模型

热带气旋 (TC) 产生的波浪可以使用时变风场强制的非平稳波浪模型进行估计。然而，由于需要高时间和空间分辨率才能正确模拟TC引起的波传播过程，因此区域尺度域的动态模拟对时间和计算要求很高。早期预警系统、沿海风险评估和未来气候预测等应用受益于对接近真实风暴路径几何形状引起的波场的快速准确估计。所提出的 SHyTCWaves 方法构成了一种新颖的工具，能够估计深水中 TC 产生的定向波谱的时空变化，使用混合方法和统计技术来减少 CPU 时间工作。这项工作表明，可以使用基于添加连续 6 小时周期的时变风暴条件的定格运动方法来重建 TC 引起的波。开发的混合模型将 TC 轨迹简化为多个分段，这些分段根据 10 个代表性 TC 特征进行参数化，并生成动态预计算的案例库，允许集成代表原始 TC 轨迹的​​连续 6 小时模拟分段。该元模型已与现有卫星数据进行了比较和修正，其适用性以南太平洋的 TC Ofa 为例。