Examining spatiotemporal trends of drought in the conterminous United States using self-organizing maps
Examining spatiotemporal trends of drought in the conterminous United States using self-organizing maps
复制标题
DOI：
10.1080/02723646.2022.2035891
复制
发表时间：
2022-02
影响因子：
1.6
通讯作者：
M. Moreno;M. Sugg;Camila Moreno;Dr. Johnathan Sugg;Dr. Baker L. Perry;J. Runkle;R. Leeper
中科院分区：
文献类型：
--
作者：
M. Moreno;M. Sugg;Camila Moreno;Dr. Johnathan Sugg;Dr. Baker L. Perry;J. Runkle;R. Leeper
摘要干旱是一种自然的、周期性的极端气候现象，会对自然生态系统和社会经济部门造成长期的破坏。与其他自然灾害不同，干旱的发生是隐蔽的，往往在较长的时间范围内影响较大的空间范围。在美国，干旱的演变及其影响通常是区域性的，降水量的变化加剧可能会掩盖干旱的表现。在这项研究中，我们研究了干旱的时空趋势，使用自组织映射（SOM），人工神经网络（ANN）的竞争性学习子集，需要无监督的输入训练。我们将每月帕尔默干旱严重度指数（PDSI）值引入SOM，以确定1895年至2016年的湿润和干燥模式的现有集群。经过培训，我们创建了SOM输出的地图可视化，并进行了随后的时间序列分析，以与干旱的地理模式联系起来。在过去的40年里，东北部、中西部和大平原北部的降水在几个节点上加强。在大多数的SOM模式，我们确定没有显着变化的干燥或湿润模式在过去的世纪的大部分CONUS。
ABSTRACT Droughts are a natural, recurrent climate extreme that can inflict long-lasting devastation on natural ecosystems and socio-economic sectors. Unlike other natural hazards, drought onset is insidious and often affects a greater spatial extent over a prolonged temporal scale. In the United States the evolution of drought and its impacts are typically region-specific and intensified precipitation variability may obscure how drought may manifest. In this study, we examine the spatiotemporal trends of drought using self-organizing maps (SOM), competitive learning subset of artificial neural networks (ANN), requiring unsupervised training of inputs. We introduced monthly Palmer Drought Severity Index (PDSI) values to the SOM to identify existing clusters of wetting and drying patterns from 1895 to 2016. After training, we created cartographic visualizations of the SOM output and conducted a subsequent time-series analysis to link with the geographic patterns of drought. Over the last 40 years, precipitation intensified in the Northeast, Midwest, and upper Great Plains across several nodes. Across the majority of SOM patterns, we identified no significant changes of drying or wetting patterns over the last century for the greater part of the CONUS.