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Markov Chain: First Step towards Heat Wave Analysis in Malaysia

机译:马尔可夫链:马来西亚热浪分析的第一步

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Extreme temperature has been carried out around the world to provide awareness and proper opportunity for the societies to prepare necessary arrangements. In this present paper, the first order Markov chain model was applied to estimate the probability of extreme temperature based on the heat wave scales provided by the Malaysian Meteorological Department. In this study, the 24-year period (1994-2017) daily maximum temperature data for 17 meteorological stations in Malaysia was assigned to the four heat wave scales which are monitoring, alert level, heat wave and emergency. The analysis result indicated that most of the stations had three categories of heat wave scales. Only Chuping station had four categories while Bayan Lepas, Kuala Terengganu, Kota Bharu and Kota Kinabalu stations had two categories. The limiting probabilities obtained at each station showed a similar trend which the highest proportion of daily maximum temperature occurred in the scale of monitoring and followed by the alert level. This trend is apparent when the daily maximum temperature data revealed that Malaysia is experiencing two consecutive days of temperature below 35°C.
机译:极端温度已经在世界各地进行,为社会提供准备的必要安排,为社会提供意识和适当的机会。在本文中,基于马来西亚气象部门提供的热波尺度来施加第一阶马尔可夫链模型来估计极端温度的概率。在本研究中,24年期间(1994-2017)马来西亚17个气象站的每日最高温度数据被分配到监测,警报水平,热波和紧急情况的四个热波尺度。分析结果表明,大多数车站有三类热波尺度。只有Chuping Station才有四类,而Bayan Lepas,Kuala Terengganu,Kota Bharu和Kota Kinabalu站有两类。在每个站中获得的限制概率显示出类似的趋势,其每日最高温度比例的最高比例在监测的规模中发生,然后是警报级别发生。当日常的最高温度数据显示马来西亚在35°C以下连续两天经历连续的温度时,这种趋势很明显。

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