Clustering of Iranian synoptic stations based on meteorological and geographical parameters

Clustering is an instrument that divides existing data into different groups. Generally, the number of clusters is determined based on the least changes within the group and the most changes outside the group. The study area is country of Iran. Coordinates of longitude, latitude, altitude, average temperature, relative humidity and total monthly rainfall of 420 synoptic stations from its establishment until 2018 have been used in this study. After reviewing, screening and repairing the data, only 375 stations remained to continue the research. Due to the length of the statistical period is an important factor influencing clustering, the stations are statistically divided into three periods: less than 5 years with 42 stations; 1-6 years with 33 stations and more than 10 years with 300 stations, were classified. Seven methods of hierarchical clustering (3 subsets), separation (2 subsets) and ward (2 subsets) have been used in this study. Cophenetic correlation coefficient, Silhouette width test are two indicators of clustering and selection. The coding was performed in R statistical software. Based on the Cophenetic and Silhouette coefficient indices, the best number and method of clustering for 1-5-year data are 4 clusters with the middle axis separation method, for the data of 6-10 years are 5 clusters with the mean-centered hierarchical method and for stations with a statistical period of more than 10 years are 4 clusters with the separation average axis method. The zoning of the clusters is plotted on the geographical map of Iran using ARCGIS software for all three categories. Keywords: Clustering, Geographical coordinates, Synoptic, Iran.Clustering is an instrument that divides existing data into different groups. Generally, the number of clusters is determined based on the least changes within the group and the most changes outside the group. The study area is country of Iran. Coordinates of longitude, latitude, altitude, average temperature, relative humidity and total monthly rainfall of 420 synoptic stations from its establishment until 2018 have been used in this study. After reviewing, screening and repairing the data, only 375 stations remained to continue the research. Due to the length of the statistical period is an important factor influencing clustering, the stations are statistically divided into three periods: less than 5 years with 42 stations; 1-6 years with 33 stations and more than 10 years with 300 stations, were classified. Seven methods of hierarchical clustering (3 subsets), separation (2 subsets) and ward (2 subsets) have been used in this study. Cophenetic correlation coefficient, Silhouette width test are two indicators of clustering and selection. The coding was performed in R statistical software. Based on the Cophenetic and Silhouette coefficient indices, the best number and method of clustering for 1-5-year data are 4 clusters with the middle axis separation method, for the data of 6-10 years are 5 clusters with the mean-centered hierarchical method and for stations with a statistical period of more than 10 years are 4 clusters with the separation average axis method. The zoning of the clusters is plotted on the geographical map of Iran using ARCGIS software for all three categories. Keywords: Clustering, Geographical coordinates, Synoptic, Iran.Clustering is an instrument that divides existing data into different groups. Generally, the number of clusters is determined based on the least changes within the group and the most changes outside the group. The study area is country of Iran. Coordinates of longitude, latitude, altitude, average temperature, relative humidity and total monthly rainfall of 420 synoptic stations from its establishment until 2018 have been used in this study. After reviewing, screening and repairing the data, only 375 stations remained to continue the research. Due to the length of the statistical period is an important factor influencing clustering, the stations are statistically divided into three periods: less than 5 years with 42 stations; 1-6 years with 33 stations and more than 10 years with 300 stations, were classified. Seven methods of hierarchical clustering (3 subsets), separation (2 subsets) and ward (2 subsets) have been used in this study. Cophenetic correlation coefficient, Silhouette width test are two indicators of clustering and selection. The coding was performed in R statistical software. Based on the Cophenetic and Silhouette coefficient indices, the best number and method of clustering for 1-5-year data are 4 clusters with the middle axis separation method, for the data of 6-10 years are 5 clusters with the mean-centered hierarchical method and for stations with a statistical period of more than 10 years are 4 clusters with the separation average axis method. The zoning of the clusters is plotted on the geographical map of Iran using ARCGIS software for all three categories. Keywords: Clustering, Geographical coordinates, Synoptic, Iran.