Evaluating the ability of numerical models to capture important shifts in environmental time series: A fuzzy change point approach

Evaluating the ability of numerical models to capture important shifts in environmental time series: A fuzzy change point approach
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评估数值模型捕获环境时间序列重要变化的能力:模糊变点方法

DOI:
10.1016/j.envsoft.2021.104993
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发表时间:
2021
影响因子:
4.9
通讯作者:
Hollaway M
Hollaway M
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Hollaway M

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数值模型是理解自然环境复杂性和动态性的重要工具。评估这些模型在多大程度上代表现实的能力对于它们的使用和未来的发展至关重要。本研究提出了一个变点分析和模糊逻辑相结合,以评估数值模型捕捉当地规模的时间观察事件的能力。基于模糊联合的变点位置的不确定性度量因子,用于计算观测记录中每个变点的数值模型与现实之间的个体相似性得分。该方法的应用是通过一个高分辨率的模型数据集,能够拿起格陵兰岛的温度记录中观察到的变化点,以不同程度的成功的案例研究。该案例研究使用DataLabs框架,这是一个基于云的协作平台,可以简化环境科学应用中复杂统计方法的访问。
Numerical models are essential tools for understanding the complex and dynamic nature of the natural environment. The ability to evaluate how well these models represent reality is critical in their use and future development. This study presents a combination of changepoint analysis and fuzzy logic to assess the ability of numerical models to capture local scale temporal events seen in observations. The fuzzy union based metric factors in uncertainty of the changepoint location to calculate individual similarity scores between the numerical model and reality for each changepoint in the observed record. The application of the method is demonstrated through a case study on a high resolution model dataset which was able to pick up observed changepoints in temperature records over Greenland to varying degrees of success. The case study is presented using the DataLabs framework, a cloud-based collaborative platform which simplifies access to complex statistical methods for environmental science applications.
格陵兰岛极端温度事件的观测和 MAR 区域气候模型
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发表时间: 2018
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