Abstract Frost, particularly during the spring, is one of the most damaging weather phenomena for vineyards, causing significant economic losses to vineyards around the world each year. The risk of tardive frost damage in vineyards due to changing climate is considered as an important threat to the sustainable production of grapes. Therefore, the cold monitoring strategies is one of the criteria with significant impacts on the yields and prosperity of horticulture and raisin factories. Frost events can be characterized by duration and severity. This paper investigates the risk and impacts of frost phenomenon in the vineyards by modeling the joint distribution of duration and severity factors and analyzing the influential parameter’s dependency structure using capabilities of copula functions. A novel mathematical framework is developed within this study to understand the risk and uncertainties associate with frost events and the impacts on yields of vineyards by analyzing the non-linear dependency structure using copula functions as an efficient tool. The developed model was successfully validated for the case study of vineyard in Malayer city of Iran. The copula model developed in this study was shown to be a robust tool for predicting the return period of the frost events.

中文翻译：

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基于 Copula 的寒冷事件强度和持续时间的概率评估：马来亚葡萄园地区的案例研究

摘要 霜冻，尤其是在春季，是对葡萄园最具破坏性的天气现象之一，每年给世界各地的葡萄园造成重大经济损失。由于气候变化导致葡萄园迟发霜冻的风险被认为是对葡萄可持续生产的重要威胁。因此，冷监测策略是对园艺和葡萄干工厂的产量和繁荣有重大影响的标准之一。霜冻事件可以用持续时间和严重程度来表征。本文通过对持续时间和严重程度因素的联合分布进行建模，并利用 copula 函数的能力分析影响参数的依赖结构，研究了葡萄园霜冻现象的风险和影响。本研究开发了一个新的数学框架，通过使用 copula 函数作为有效工具分析非线性依赖结构，了解与霜冻事件相关的风险和不确定性以及对葡萄园产量的影响。开发的模型在伊朗马来亚市葡萄园的案例研究中得到了成功验证。本研究中开发的 copula 模型被证明是预测霜冻事件重现期的强大工具。