teleconnection drivers of extreme precipitation over iran: a causal-network perspective (1980–2024)

This study provides a quantitative and process-oriented assessment of how large-scale ocean–atmosphere teleconnection patterns modulate extreme precipitation over iran during 1979–2024. using daily observations from 160 synoptic stations, precipitation extremes were characterized through etccdi indices (r10mm, r20mm, r95p, rx5day), seasonal totals, and spi-3, and subsequently aggregated into five quasi-homogeneous hydro-climatic clusters. a causal discovery framework based on the pcmci+ algorithm was employed to infer directed and lagged relationships between twelve major teleconnection indices and regional precipitation metrics. network diagnostics reveal a pronounced asymmetry between drivers and responses: teleconnection nodes exhibit higher total degree (≈19.3 ± 10.2) and betweenness centrality (≈0.07 ± 0.08) than precipitation nodes, confirming their dominant large-scale control. enso-related indices (niño-3.4, oni, mei, soi) jointly account for nearly 65% of the aggregated absolute causal strength over southern iran, followed by the indian ocean dipole (≈13%) and eawr (≈10%). short-duration intensity metrics (rx1day and rx5day) display the strongest cumulative teleconnection influence (exceeding 33% of the total signal), whereas moderate wet-day frequencies show weaker connectivity. seasonally, robust links are concentrated in son and mam, with dynamically consistent and statistically supported signals also emerging in djf, while jja remains comparatively weakly connected. composite analyses of upper-tropospheric wind at 250 hpa, mid-tropospheric geopotential height at 500 hpa (z500), and lower-tropospheric moisture transport at 850 hpa indicate that teleconnections primarily act through reorganization of the subtropical and mid-latitude jet streams, modulation of rossby wave-train structure, and alteration of mid-level baroclinicity and low-level moisture convergence. overall, the results demonstrate that extreme precipitation over iran is governed by a limited set of dynamically efficient teleconnections whose influence is seasonally modulated and regionally heterogeneous. these findings provide a quantitative basis for improving seasonal predictability and for evaluating process representation in climate-model simulations. this study provides a quantitative and process-oriented assessment of how large-scale ocean–atmosphere teleconnection patterns modulate extreme precipitation over iran during 1979–2024. using daily observations from 160 synoptic stations, precipitation extremes were characterized through etccdi indices (r10mm, r20mm, r95p, rx5day), seasonal totals, and spi-3, and subsequently aggregated into five quasi-homogeneous hydro-climatic clusters. a causal discovery framework based on the pcmci+ algorithm was employed to infer directed and lagged relationships between twelve major teleconnection indices and regional precipitation metrics. network diagnostics reveal a pronounced asymmetry between drivers and responses: teleconnection nodes exhibit higher total degree (≈19.3 ± 10.2) and betweenness centrality (≈0.07 ± 0.08) than precipitation nodes, confirming their dominant large-scale control. enso-related indices (niño-3.4, oni, mei, soi) jointly account for nearly 65% of the aggregated absolute causal strength over southern iran, followed by the indian ocean dipole (≈13%) and eawr (≈10%). short-duration intensity metrics (rx1day and rx5day) display the strongest cumulative teleconnection influence (exceeding 33% of the total signal), whereas moderate wet-day frequencies show weaker connectivity. seasonally, robust links are concentrated in son and mam, with dynamically consistent and statistically supported signals also emerging in djf, while jja remains comparatively weakly connected. composite analyses of upper-tropospheric wind at 250 hpa, mid-tropospheric geopotential height at 500 hpa (z500), and lower-tropospheric moisture transport at 850 hpa indicate that teleconnections primarily act through reorganization of the subtropical and mid-latitude jet streams, modulation of rossby wave-train structure, and alteration of mid-level baroclinicity and low-level moisture convergence. overall, the results demonstrate that extreme precipitation over iran is governed by a limited set of dynamically efficient teleconnections whose influence is seasonally modulated and regionally heterogeneous. these findings provide a quantitative basis for improving seasonal predictability and for evaluating process representation in climate-model simulations.