| Abstrakt: |
Climate change is a fact that we face year after year. Although is a common syntagma its manifestation is different for various region of the planet producing not just global, but local anomalies and changes. In order to track these changes, we propose a network model with preferential attachment, vertices representing successive time periods. The test location for our research was Miercurea Ciuc, one of the coldest locations of Romania. We have developed a similarity index including different meteorological parameters such as air temperature, ground temperature, precipitation amount, snow depth and sunshine hours. Using this similarity index for preferential attachment and considering the appearance order of nodes representing periods on time scale we have created a network model which shows the similarities between these periods as they appear in time. Clustering the obtained graph model, we could observe that the created network model at monthly scale clearly shows up some of experienced characteristic at the study location. [ABSTRACT FROM AUTHOR] |
