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A new prediction model of daily weather elements in Hainan province under the typhoon weather

机译:台风天气下海南省日常天气元素的新预测模型

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This paper proposes a new prediction model for severe natural disasters, especially typhoon using daily weather analysis. Hainan province in China is selected to be a typical application region, where natural disasters, especially typhoons take place frequently. These disasters have great impacts on the life and property safety of the residents, and therefore are in specific need of accurate prediction. A new prediction model of daily weather in Hainan province under the typhoon weather is proposed in this paper based on the best track datasets of typhoons and the corresponding daily weather data. This model utilizes the statistical methods and data mining technology in combination with the dynamic migration information of tropical cyclones and can provide the dynamic prediction of daily weather elements in any designated location. Three surface meteorological observation stations of Hainan province during the years 1951-1920 are used to test the model. Test results show that the prediction equations established for the vast majority of daily weather elements have passed the significant test. Besides, Typhoon Damrey is used as a case to illustrate the whole daily weather prediction model in detail and comparisons between the model and other official forecast (such as JTWC, UKMO and CMA) are performed thoroughly. It is worth noting that the model proposed in this paper is not limited to Hainan province and can be generalized to other areas in the world.
机译:本文提出了一种新的自然灾害预测模型,特别是使用日常天气分析的严重自然灾害,特别是台风。海南省在中国被选为典型的应用区域,自然灾害,特别是台风经常发生。这些灾难对居民的生命和财产安全产生了很大的影响,因此需要准确的预测。本文提出了在台风天气下的海南省日常天气预测模型,基于台风的最佳轨道数据集和相应的日常天气数据。该模型利用统计方法和数据挖掘技术与热带气旋的动态迁移信息相结合,可以在任何指定位置提供日常天气元素的动态预测。 1951年至1920年期间海南省的三个表面气象观测站用于测试模型。测试结果表明,为绝大多数日常天气元素建立的预测方程已通过显着的测试。此外,台风达雷被用作案例,以说明整个日常天气预报模型详细说明,模型与其他官方预测(如JTWC,UKMO和CMA)进行彻底进行。值得注意的是,本文提出的模型不仅限于海南省,可以推广到世界其他地区。

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    Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China;

    Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China;

    China Elect Power Res Inst Beijing 100192 Peoples R China;

    Hainan Power Grid Corp Haikou 570203 Hainan Peoples R China;

    Hainan Power Grid Corp Haikou 570203 Hainan Peoples R China;

    Hainan Power Grid Corp Haikou 570203 Hainan Peoples R China;

    Hainan Power Grid Corp Haikou 570203 Hainan Peoples R China;

    China South Power Grid Int Co Ltd Elect Power Res Inst Guangzhou 510080 Guangdong Peoples R China;

    China South Power Grid Int Co Ltd Elect Power Res Inst Guangzhou 510080 Guangdong Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大气科学(气象学);
  • 关键词

  • 入库时间 2022-08-20 03:59:47

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