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Exploring Teleconnection–Drought Relationship in Iran Through Dynamic Conditional Correlation and Cluster Analysis.

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Title: Exploring Teleconnection–Drought Relationship in Iran Through Dynamic Conditional Correlation and Cluster Analysis.
Authors: Fathian, Farshad1 (AUTHOR) f.fathian@vru.ac.ir, Dehghan, Zohreh2 (AUTHOR), Vaheddoost, Babak3 (AUTHOR), Ongoma, Victor4 (AUTHOR)
Source: International Journal of Climatology. Dec2025, Vol. 45 Issue 15, p1-18. 18p.
Subject Terms: *Droughts, *Meteorological precipitation, *Climate change, Southern oscillation, Cluster analysis (Statistics), North Atlantic oscillation, Statistics
Geographic Terms: Iran
Company/Entity: DCC PLC
Abstract: An increase in drought frequency and intensity in most parts of the world is a threat to lives and property. Understanding the underlying climatic drivers of drought occurrence and variability is therefore vital for developing effective early warning systems. Large‐scale climate variability patterns, commonly referred to as teleconnections, exert significant influence on regional precipitation and drought dynamics. This study explores the relationship between major teleconnections: Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), and Multivariate El Niño–Southern Oscillation Index (MEI), and drought in Iran by applying the dynamical conditional correlation (DCC) approach together with cluster analysis to capture regional differences. Monthly precipitation data from 1993 to 2016, sourced from 106 meteorological stations, are used to calculate the standardised precipitation index (SPI) with 1‐, 3‐, 6‐, 9‐, and 12‐month moving averages. The DCC between SPIs and three teleconnections is then analysed and clustered using the Ward's method. Results demonstrate that the MEI and SOI exhibit a strong correlation with the SPIs, while NAO shows an insignificant association with drought patterns in the region. The influence of teleconnections on SPIs exhibited correlations reaching up to ±0.6, reflecting the coherence and density of SPI patterns and the distinct spatial clustering of meteorological stations, with this range varying notably based on terrain complexity and elevation. The strength of teleconnection–SPI relationships appears to be modulated by topographic features, time lag, and shocks, which likely play a crucial role in shaping precipitation dynamics and the spatial distribution of droughts in Iran. The findings underscore the importance of incorporating terrain and elevation when analysing large‐scale climatic patterns and their influence on regional climate variability for improved accuracy of weather forecasts of extreme events. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Climatology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Exploring Teleconnection–Drought Relationship in Iran Through Dynamic Conditional Correlation and Cluster Analysis.
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  Data: <searchLink fieldCode="AR" term="%22Fathian%2C+Farshad%22">Fathian, Farshad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> f.fathian@vru.ac.ir</i><br /><searchLink fieldCode="AR" term="%22Dehghan%2C+Zohreh%22">Dehghan, Zohreh</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vaheddoost%2C+Babak%22">Vaheddoost, Babak</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ongoma%2C+Victor%22">Ongoma, Victor</searchLink><relatesTo>4</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Climatology%22">International Journal of Climatology</searchLink>. Dec2025, Vol. 45 Issue 15, p1-18. 18p.
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  Data: *<searchLink fieldCode="DE" term="%22Droughts%22">Droughts</searchLink><br />*<searchLink fieldCode="DE" term="%22Meteorological+precipitation%22">Meteorological precipitation</searchLink><br />*<searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Southern+oscillation%22">Southern oscillation</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+%28Statistics%29%22">Cluster analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22North+Atlantic+oscillation%22">North Atlantic oscillation</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
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  Data: <searchLink fieldCode="DE" term="%22Iran%22">Iran</searchLink>
– Name: SubjectCompany
  Label: Company/Entity
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  Data: <searchLink fieldCode="DE" term="%22DCC+PLC%22">DCC PLC</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: An increase in drought frequency and intensity in most parts of the world is a threat to lives and property. Understanding the underlying climatic drivers of drought occurrence and variability is therefore vital for developing effective early warning systems. Large‐scale climate variability patterns, commonly referred to as teleconnections, exert significant influence on regional precipitation and drought dynamics. This study explores the relationship between major teleconnections: Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), and Multivariate El Niño–Southern Oscillation Index (MEI), and drought in Iran by applying the dynamical conditional correlation (DCC) approach together with cluster analysis to capture regional differences. Monthly precipitation data from 1993 to 2016, sourced from 106 meteorological stations, are used to calculate the standardised precipitation index (SPI) with 1‐, 3‐, 6‐, 9‐, and 12‐month moving averages. The DCC between SPIs and three teleconnections is then analysed and clustered using the Ward's method. Results demonstrate that the MEI and SOI exhibit a strong correlation with the SPIs, while NAO shows an insignificant association with drought patterns in the region. The influence of teleconnections on SPIs exhibited correlations reaching up to ±0.6, reflecting the coherence and density of SPI patterns and the distinct spatial clustering of meteorological stations, with this range varying notably based on terrain complexity and elevation. The strength of teleconnection–SPI relationships appears to be modulated by topographic features, time lag, and shocks, which likely play a crucial role in shaping precipitation dynamics and the spatial distribution of droughts in Iran. The findings underscore the importance of incorporating terrain and elevation when analysing large‐scale climatic patterns and their influence on regional climate variability for improved accuracy of weather forecasts of extreme events. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Climatology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1002/joc.70131
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 1
    Subjects:
      – SubjectFull: Droughts
        Type: general
      – SubjectFull: Meteorological precipitation
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Southern oscillation
        Type: general
      – SubjectFull: Cluster analysis (Statistics)
        Type: general
      – SubjectFull: North Atlantic oscillation
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Iran
        Type: general
      – SubjectFull: DCC PLC
        Type: general
    Titles:
      – TitleFull: Exploring Teleconnection–Drought Relationship in Iran Through Dynamic Conditional Correlation and Cluster Analysis.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Fathian, Farshad
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            NameFull: Dehghan, Zohreh
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            NameFull: Vaheddoost, Babak
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            NameFull: Ongoma, Victor
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          Dates:
            – D: 15
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 08998418
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              Value: 45
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              Value: 15
          Titles:
            – TitleFull: International Journal of Climatology
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