标题： 一种用于Nor'easters中不对称压力和边界层风模拟的混合分析框架 显示英文标题

标题： A Hybrid Analytical Framework for Asymmetric Pressure and Boundary Layer Wind Simulation in Nor'easters

摘要： 东北风暴经常影响北美东海岸，带来危险的降水、风和沿海洪水。 准确模拟其气压和风场对于预测、风险评估和基础设施规划至关重要，但由于其复杂且不对称的结构，仍具有挑战性。 本研究介绍了一种新型的混合解析-数据驱动模型，旨在高效模拟东北风暴的气压和边界层风场。 气压场采用改进的Holland型公式进行建模，通过克里金代理模型估计方位角变化的参数，这些模型由再分析数据的敏感性分析提供信息。 然后通过将风流分解为梯度和摩擦分量，从动量方程中解析地推导出风场。 模型性能通过与ERA-Interim再分析数据以及历史事件的地表风观测进行对比评估。 结果表明，所提出的气压模型能够准确再现椭圆形等压线和关键的不对称模式，而风模型则能够捕捉边界层流动的基本结构和强度，包括超梯度风的存在。 由于其物理基础、计算效率以及能够表示关键风暴不对称性的能力，该模型为极端东北风暴的风险评估和情景分析提供了一个有价值的替代方案，相较于计算成本高昂的数值模拟。 显示英文摘要

摘要： Nor'easters frequently impact the North American East Coast, bringing hazardous precipitation, winds, and coastal flooding. Accurate simulation of their pressure and wind fields is essential for forecasting, risk assessment, and infrastructure planning, yet remains challenging due to their complex, asymmetric structure. This study introduces a novel hybrid analytical-data-driven model designed to efficiently simulate Nor'easter pressure and boundary layer wind fields. The pressure field is modeled using an adapted Holland-type formulation, with azimuthally varying parameters estimated through Kriging surrogate models informed by sensitivity analysis of reanalysis data. The wind field is then derived analytically from the momentum equations by decomposing the wind flow into gradient and frictional components. Model performance is assessed against ERA-Interim reanalysis data and surface wind observations from a historical event. Results show that the proposed pressure model accurately reproduces elliptical isobars and key asymmetrical patterns, while the wind model captures the fundamental structure and intensity of the boundary layer flow, including the presence of supergradient winds. Owing to its physical basis, computational efficiency, and ability to represent critical storm asymmetries, the model offers a valuable alternative to computationally expensive numerical simulations for hazard assessment and scenario analysis of extreme Nor'easters.