Department of Science, University of Roma Tre, Rome, Italy.
EnviX-Lab. Dipartimento di Bioscienze e Territorio, Universita' degli studi del Molise, Pesche-Isernia, Italy.
Int J Biometeorol. 2021 Jul;65(7):1085-1097. doi: 10.1007/s00484-021-02089-x. Epub 2021 Feb 15.
The present work analyses the main weather patterns over the period 1981-2010 in the Central Apennines (Italy), drawing upon data from 23 monitoring stations spanning a wide elevation range (260-1750 m asl). Cluster analysis was used to identify homogeneous units and to verify the effectiveness of the bioclimatic classification by crossing the results derived from the application of hierarchical and non-hierarchical classification techniques. The results reveal a diversified picture of five clusters that depends on several factors as elevation, the geographic position within or outside the mountainous range, and the regional morphological traits. Although Mediterranean and Temperate climatic features coexist, the Mediterranean pattern in the southern areas and internal valleys better expresses the overall mixed characteristics of Central Italy. The use of a mixed methodology of hierarchic and partitioning methods of cluster analysis improves the bioclimatic classification, especially to quantify the level of humidity and the mediterraneity degree.
本研究分析了 1981 年至 2010 年间意大利中央亚平宁山脉的主要天气模式,所使用的数据来自海拔范围广泛(260-1750 米)的 23 个监测站。聚类分析用于识别同质单元,并通过交叉应用层次和非层次分类技术的结果来验证生物气候分类的有效性。结果显示了五个聚类的多样化情况,这取决于几个因素,如海拔、山区内外的地理位置以及区域形态特征。尽管地中海和温带气候特征并存,但南部地区和内部山谷的地中海模式更好地体现了意大利中部的整体混合特征。层次聚类分析和分区聚类分析的混合方法的使用提高了生物气候分类的准确性,特别是量化了湿度水平和地中海程度。