Global climate change has, in recent years, increased the frequency and intensity of meteorological disasters. In particular, damage to greenhouses caused by heavy snowfall continues to occur on farms in South Korea. Because heavy snowfall occurs over a relatively long time compared to other sudden meteorological disasters, if an appropriate warning system for heavy snowfall events is in place then damage to greenhouses can be prevented. However, the existing snowfall warning system in South Korea consists only of a simple alert that is unable to anticipate future risks to an area caused by heavy snowfall. In this study, the aim was to develop a stochastic alarm model to minimise the damage to greenhouses caused by heavy snowfall events. A Markov chain was designed to construct the alarm model using snowfall data from nationwide weather stations as well as from greenhouse standards with various safety criteria. The snow depth data were divided into several sections using a cluster analysis, and the failure probabilities of the greenhouses were derived for specific time interval according to current snow depth. This method considers the weather characteristics of each region as well as various greenhouse standards because the risks of heavy snowfall vary depending on location and type of the installation. Using the alarm model developed in this study, it is possible to predict and therefore manage the negative impacts of heavy snowfall events on greenhouses.

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基于马尔可夫链的大雪大降雪预警模型对温室防灾的开发

近年来，全球气候变化增加了气象灾害的频率和强度。特别是，韩国农场持续发生大雪对温室造成的破坏。由于与其他突发性气象灾害相比，大雪发生的时间相对较长，如果有适当的大雪事件预警系统，则可以防止对温室的破坏。然而，韩国现有的降雪预警系统仅包含一个简单的警报，无法预测大雪给该地区带来的未来风险。在这项研究中，目的是开发一个随机警报模型，以尽量减少大雪事件对温室造成的损害。马尔可夫链旨在使用来自全国气象站的降雪数据以及具有各种安全标准的温室标准来构建警报模型。使用聚类分析将积雪深度数据划分为多个部分，并根据当前积雪深度推导出特定时间间隔内温室的故障概率。这种方法考虑了每个地区的天气特征以及各种温室标准，因为大雪的风险因安装位置和类型而异。使用本研究中开发的警报模型，可以预测并因此管理大雪事件对温室的负面影响。使用聚类分析将积雪深度数据划分为多个部分，并根据当前积雪深度推导出特定时间间隔内温室的故障概率。这种方法考虑了每个地区的天气特征以及各种温室标准，因为大雪的风险因安装位置和类型而异。使用本研究中开发的警报模型，可以预测并管理大雪事件对温室的负面影响。使用聚类分析将积雪深度数据划分为多个部分，并根据当前积雪深度推导出特定时间间隔内温室的故障概率。这种方法考虑了每个地区的天气特征以及各种温室标准，因为大雪的风险因安装位置和类型而异。使用本研究中开发的警报模型，可以预测并管理大雪事件对温室的负面影响。这种方法考虑了每个地区的天气特征以及各种温室标准，因为大雪的风险因安装位置和类型而异。使用本研究中开发的警报模型，可以预测并管理大雪事件对温室的负面影响。这种方法考虑了每个地区的天气特征以及各种温室标准，因为大雪的风险因安装位置和类型而异。使用本研究中开发的警报模型，可以预测并管理大雪事件对温室的负面影响。