عنوان مقاله [English]
Considering the great application of Sea Surface Temperature (SST) in climatic and oceanic investigations, this research deals with the investigation of spatial autocorrelation pattern of SST data obtained from AVHRR sensor for Gulf of Oman from 2003 to 2015 (13 years). To achieve this aim, two important spatial statistics, i.e. global Moran and Anselin local Moran’s I were employed within monthly and annually timescales. The results obtained from global Moran in the monthly scale suggested the existence of a strong autocorrelation and cluster pattern for SST data across all months, where warm months had a stronger autocorrelation in comparison with cold months. Furthermore, global Moran index within annual scale indicated an ascending trend for autocorrelation and clustering of SST data within the 13 studied years. To represent the manner of clustering, local Moran index was employed. Based on the results of this index within monthly scale, it was found that in winter, especially during January and February, low-low clusters, which represent low SST values, have been formed in western parts, while high-high clusters, which represent high SST values, have been formed in the southeastern parts of Gulf of Oman. After this season, the mentioned pattern changed, and from May to October, low-low clusters have been developed in the southeastern parts, while high-high clusters have been developed in the western parts of Gulf of Oman. The map of clusters for the annual scale suggested the growth of high-high clusters and reduction of low-low clusters of SST overtime. Based on these findings, it could be concluded that warming of SST in Gulf of Oman within this time period has been statistically significant and positive.
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