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青岛沿海,春末夏初逐日天气主要是晴与雾交替出现。两种天气的出现与不出现不仅与前期因子有关系,而且存在着相互转移的规律。这种相互转移过程可近似视为简单的马尔柯夫过程。因而,为建立预报模式提供更多的信息,以提高预报准确率,本文,在建立预报模式时既考虑了前期各因子的变化情况,又应用了逐日天气相互之间转移的规律,即计算各因子在出现某种状况下晴与雾之间的转移概率,然后采用平均法和回归法作出逐日海雾的概率预报,效果尚好。对海雾的短期预报有一定的参考意义。
Qingdao coast, early spring and early summer early daily weather is mainly cloudy and fog alternate appearance. The appearance and absence of two kinds of weather are not only related to the previous factors, but also exist the law of mutual transfer. This mutual transfer process can be approximated as a simple Markov process. Therefore, in order to provide more information to establish the forecasting model to improve the forecasting accuracy, this article not only considers the changes of the various factors in the forecasting model but also applies the laws of day-to-day weather transfer, that is, Factor in the emergence of a transition between sunny and fog probability, and then use the average method and regression method to make a daily sea fog probability forecast, the effect is good. The short-term forecast of the sea fog has a certain reference value.