Influence of leading teleconnection indices on key climate variables—precipitation and Tmin/Tmax—at Saveh Synoptic Station, Iran.

Document Type : Research Paper

Author

Department of Irrigation and reclamation-Faculty of Agriculture and Nature Resources -Tehran University-Karaj-Iran

10.22059/ijswr.2025.400345.669995

Abstract

This study interrogates the influence of fifteen atmospheric–oceanic teleconnections (AMM, AMO, AO, EAWR, EP–NP, MEI, NAO, ONI, PDO, PNA, QBO30Z, SCAND, SOI, TNA, TSA) on precipitation and temperature at the Saveh synoptic station over 1993–2024. Monthly indices were retrieved from NOAA/NCEI, while precipitation and temperature were obtained from the Iranian Meteorological Organization. Direct associations were quantified using the Spearman rank correlation to avoid distributional assumptions. To extract dominant structures, we employed Rock‑PCA—an extension of EOF/PCA. Findings reveal EP–NP as the most influential controller of temperature on monthly and seasonal scales; Pacific signals (e.g., MEI/ONI) also manifest more robustly in temperature than in annual precipitation. For precipitation, Atlantic metrics—especially AMM and AO—are pivotal: negative AMM is linked to rainfall reduction (notably in autumn), whereas negative AO is associated with modest wet anomalies in October–December across the central Iranian Plateau, including Saveh; positive AO generally suppresses rainfall. Composite and co‑occurrence analyses, together with 1–3‑month lag responses, substantially improve predictability. Operationally, we recommend monitoring EP–NP for temperature outlooks and combining EP–NP with Atlantic indices (TNA/TSA/AMO/AMM) for seasonal precipitation guidance. The contrast between annual and seasonal/extreme scales explains the weak annual rainfall correlations versus stronger seasonal signals.

Keywords

Main Subjects

Introduction

Teleconnections orchestrate energy–mass exchanges across basins and modulate hydro‑climate variability from the synoptic to decadal scales. In West Asia and Iran, compound interactions among Pacific and Atlantic modes shape rainfall intermittency, temperature extremes, and dust activity. Motivated by heightened vulnerability of water and agriculture in the central Iranian Plateau, this study examines fifteen indices and their lagged/co‑occurring impacts on Saveh hydro‑climate over 1993–2024.

Methodology

We quantify monotonic associations via the Spearman rank correlation. To uncover dominant, potentially nonlinear structures, we use Rock‑PCA, which generalizes complex EOF/PCA by (i) encoding phase/lag through the Hilbert analytic signal, (ii) mapping to an RKHS with linear or nonlinear kernels, and (iii) applying Varimax/ProMax rotation for interpretability. Composite analyses link teleconnection phases to geopotential‑height and low‑level temperature anomalies (500/850 hPa, 2‑m temperature), clarifying dynamical pathways.

Sampling Procedures

Monthly teleconnection indices (AMM, AMO, AO, EAWR, EP–NP, MEI, NAO, ONI, PDO, PNA, QBO30Z, SCAND, SOI, TNA, TSA) were obtained from NOAA/NCEI. Co‑located monthly precipitation and temperature for the Saveh synoptic station were retrieved from the Iranian Meteorological Organization. The analysis period spans January 1993–December 2024. Lags up to three months were evaluated to capture delayed hydro‑climate responses.

Results

EP–NP emerges as the primary controller of temperature on monthly/seasonal scales; Pacific signals (MEI/ONI) show clearer links to temperature than to annual rainfall. For precipitation, Atlantic modes dominate: negative AMM aligns with rainfall reduction—especially in autumn—while negative AO corresponds to modest wet anomalies during October–December; positive AO tends to suppress rainfall. Composite maps corroborate these findings via changes in mid‑tropospheric waveguides and subtropical jet displacement. The seasonal scale exhibits markedly stronger, more interpretable signals than annual aggregates, consistent with extreme‑event sensitivity.

Conclusion

Operationally, monitoring EP–NP is crucial for temperature outlooks, whereas seasonal precipitation guidance benefits from combining EP–NP with Atlantic indices (AMM/AMO/TNA/TSA), while accounting for 1–3‑month lags and co‑occurrence patterns. These insights motivate hybrid statistical–ML prediction systems that assimilate teleconnections to enhance early warning and water‑resources planning in central Iran.

Authors’ contributions

 Mr. SaadatMoghaddasi: Gathering the experimental data, Data curation, Software; Methodology; Investigation, Conceptualization, Methodology, Writing-Reviewing and Editing, Formal analysis, Analyzing the experimental data.

Data Availability Statement

Data available on request from the author.

Ethical considerations

The author avoided data fabrication, falsification, plagiarism, and misconduct.

Conflict of interest

All authors declare that they have no conflict of interest.

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Iranian Journal of Soil and Water Research
Volume 56, Issue 11
January 2026
Pages 3217-3235

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