Analysis of the Relationship between Temperature Changes on the Southern Coasts of Iran and Teleconnections Indices

Document Type : Original Article

Authors

1 Professor, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

2 PhD Student of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.

3 Postdoctoral Researcher in Climatology, Department of Physical Geography, University of Mohaghegh Ardabili, Ardabil, Iran.

10.22124/gscaj.2025.26243.1280

Abstract

In this study, the relationship between monthly temperature changes of stations located on the southern coast of Iran and the teleconnection patterns was investigated. The minimum and maximum monthly temperature data of 11 synoptic stations and 14 teleconnection patterns of the Atlantic and tropical Pacific Oceans over 1985-2024 were used. The possible relationship between the two temperature components in the studied stations and these teleconnection patterns was calculated using Pearson correlation analysis, analysis of variance, and regression analysis, and the spatial distribution of the correlation was plotted. The results showed that the highest percentage of correlation between the Pacific Ocean patterns and the minimum and maximum air temperatures of the coasts was with the AMO patterns (0.56), NTA (0.46), AMO (0.76), and ONI (-0.63) patterns, respectively. About 16-56 percent of the minimum temperature changes and 6-31 percent of the maximum temperature changes of the stations were explained by the teleconnection patterns. The NINO3, ONI (Tropical Pacific) and AMO (Atlas) models are more effective in explaining the minimum temperatures of the stations and the NINO3, AMO and AMM models are more effective in explaining the maximum temperatures of the stations. The highest frequency of significant correlations between the minimum temperatures of the stations was observed in January with TNA, in February with AMO and TNA, in March with NAO, in Orville with TSA, in June with WHWP, in July with TSA, in August with TNA, in September with WHWP and AMO, and in May, October, November and December with AMO.

Highlights

  • The highest percentage of correlation between the Pacific Ocean patterns with the minimum and maximum coastal air temperatures was calculated with the AMO (0.76) and ONI (-0.63) patterns, and the AMO (0.56) and NTA (0.46) patterns, respectively.
  • Multivariate regression models showed that tropical patterns are the most effective patterns in explaining temperature changes in at least two-thirds of the studied stations.
  • The NINO3, ONI and AMO (tropical Pacific) patterns are effective in explaining the minimum temperature, and the NINO3 (tropical calm) and AMO (South Atlantic Tropical Index) and AMM patterns are effective in explaining the maximum temperature of these stations.
  • The highest frequency of significant correlations between the minimum temperatures of the stations in the months of February, May, September, October, November and December is related to the AMO pattern.

Keywords

Main Subjects

References

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