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本文建立了一个Markov型相似模式,用于预报西北太平洋热带气旋的移动.在概率求解方法上部分吸取了美国大西洋飓风预报的HURRAN方法.本模式跟传统的相似求解方法与概念是有原则区别的,为了使相似的选择能不断逼近和适应新的资料,采用Markov过程来描写台风移动的概率预报问题.72小时预报分6步来作,每步预报起始资料和相似概率求解资料都在不断更新。 为试验模式性能,文中还移植了传统的相似法,建立了预报太平洋台风移动的相似模式(方案1),并将方案1与Markov型相似模式(方案2)做相同实例的平行对比预报.对1981和1982年共95次台风的独立资料,进行了72小时预报试验.结果表明,方案2预报误差明显减小。
In this paper, a Markov-type similarity model is established to forecast the tropical cyclone movement in the western North Pacific. The HURRAN method of hurricane forecast of the Atlantic Ocean in the United States is partly absorbed in the method of probability solution. This model is in principle different from the traditional similarity solution method and concept In order to make the similar choices keep approaching and adapt to the new data, the Markov process is used to describe the probability forecast problem of typhoon movement. The 72-hour forecast is made in 6 steps, and the data of each step forecast and the data of similar probability solution are constantly Updated. In order to test the performance of the model, the traditional similarity method is also transplanted, and a similar model for forecasting the movement of the Pacific typhoon is established (Scheme 1). The parallel contrast prediction of the same example with the Markov-type similarity model (Scheme 2) is made. A total of 95 typhoon data were conducted in 1981 and 1982, and a 72-hour forecast test was carried out. The results show that the forecast error of Scenario 2 is significantly reduced.