Tropical Cyclone Intensity Evolution Modeled as a Dependent Hidden Markov Process
Tropical Cyclone Intensity Evolution Modeled as a Dependent Hidden Markov Process
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DOI：
10.1175/jcli-d-19-0027.1
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发表时间：
2019-11-01
影响因子：
4.9
通讯作者：
Lin, Ning
中科院分区：
文献类型：
--
作者：
Jing, Renzhi;Lin, Ning
建立了一个隐马尔可夫模式，用于模拟热带气旋强度随周围大尺度环境的演变。该模型考虑了三个未观测到的（隐藏的）离散状态的风暴强度变化，并将每个状态与强度变化的概率分布相关联。风暴从一个状态到另一个状态的转变被描述为马尔可夫链。模式的强度变化和状态转换分量都依赖于环境变量，包括潜在强度、垂直风切变、相对湿度和海洋反馈。这个马尔可夫环境依赖飓风强度模型（MeHiM）用于模拟风暴强度沿海洋沿着风暴路径的演变，并增加了一个简单的衰减模型来估计风暴在陆地上移动时的强度变化。1979年至2014年（555场风暴）的北大西洋（NA）盆地数据用于模型开发和评估。6小时和24小时强度变化的概率分布，寿命最大强度，登陆强度的模型模拟和观测比较好。虽然MeHiM在充分描述快速强化方面仍然有限，但它显示出比以前的统计模型（例如，线性、非线性和有限混合模型）。
A hidden Markov model is developed to simulate tropical cyclone intensity evolution dependent on the surrounding large-scale environment. The model considers three unobserved (hidden) discrete states of storm intensity change and associates each state with a probability distribution of intensity change. The storm's transit from one state to another is described as a Markov chain. Both the intensity change and state transit components of the model are dependent on environmental variables including potential intensity, vertical wind shear, relative humidity, and ocean feedback. This Markov Environment-Dependent Hurricane Intensity Model (MeHiM) is used to simulate the evolution of storm intensity along the storm track over the ocean, and a simple decay model is added to estimate the intensity change when the storm moves over land. Data for the North Atlantic (NA) basin from 1979 to 2014 (555 storms) are used for model development and evaluation. Probability distributions of 6- and 24-h intensity change, lifetime maximum intensity, and landfall intensity based on model simulations and observations compare well. Although the MeHiM is still limited in fully describing rapid intensification, it shows a significant improvement over previous statistical models (e.g., linear, nonlinear, and finite mixture models).