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<p>Under global warming, asymmetric changes between cold and warm extremes represent a critical dimension of mountain climate sensitivity. The upper Yangtze River, a pivotal component of the “Asian Water Tower,” features complex terrain with dramatic elevational contrasts, yet systematic quantification of how extreme temperature asymmetry varies with altitude and season remains lacking. Utilizing ERA5-Land reanalysis and SRTM data (1984–2023), this study analyzes elevational gradients and seasonal differences via a defined Asymmetry Index (AI = trend_TXx – trend_TXn). Key findings include: (1) Cold extremes (TXn) warmed markedly faster than warm extremes (TXx), with the mean TXn trend ~ 1.7 times greater. Spatially, rapid TXn warming concentrated in high-elevation zones (e.g., eastern Tibetan Plateau), whereas faster TXx warming dominated low-elevation areas (e.g., Sichuan Basin). (2) AI exhibited a significant negative correlation with elevation (<i>p</i> &lt; 0.001), decreasing by ~ 0.107&#xa0;°C/decade per 1000&#xa0;m ascent, signaling a systematic altitudinal shift from “faster warming of warm extremes” to “faster warming of cold extremes.” (3) Pronounced seasonal heterogeneity emerged: growing-season AI was predominantly positive, but non-growing-season AI displayed a striking dipole pattern (negative at high elevations, positive at low elevations). (4) The seasonal difference itself depended on elevation, peaking at 3000–5000&#xa0;m, indicating a fundamental change in governing processes across altitudes. This work provides a systematic, spatially explicit quantification of how extreme temperature asymmetry varies with both elevation and season over the Upper Yangtze River basin, a major monsoonal mountain system. Our analysis reveals a robust elevational gradient and a striking seasonal reversal in this asymmetry. The findings refine the understanding of elevation-dependent warming by revealing its asymmetric nature between temperature extremes, offering critical insights into the coupled roles of altitude and season in modulating climate responses within complex terrain.</p> Graphical abstract <p></p> <p>This visual summary depicts our investigation into the asymmetry of extreme temperature changes over the Upper Yangtze River. Utilizing ERA5-Land temperature data and SRTM elevation data (1984–2023), we analyzed trends in warm (TXx) and cold (TXn) extremes and defined an Asymmetry Index (AI = Trend_TXx - Trend_TXn). The core findings reveal two dominant patterns: (1) A clear elevational gradient, where AI decreases with altitude, indicating faster warming of cold extremes at higher elevations. (2) A pronounced seasonal reversal, with positive AI (faster warming of warm extremes) dominating the growing season, and a dipole pattern (negative AI at high elevations, positive at low elevations) characterizing the non-growing season. The study concludes that the asymmetry of extreme temperature changes is a three-dimensional phenomenon co-modulated by topography and seasonal processes, providing critical insights into mountain climate sensitivity.</p>

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Mountains Warm Differently: Altitudinal Switch and Seasonal Reversal of Extreme Temperature Asymmetry in the Upper Yangtze River

  • 期刊论文

  • 发表日期：

    2026年2月25日

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  • Zebin Li,
  • Zhijie Ta,
  • Qian Ren

摘要

Under global warming, asymmetric changes between cold and warm extremes represent a critical dimension of mountain climate sensitivity. The upper Yangtze River, a pivotal component of the “Asian Water Tower,” features complex terrain with dramatic elevational contrasts, yet systematic quantification of how extreme temperature asymmetry varies with altitude and season remains lacking. Utilizing ERA5-Land reanalysis and SRTM data (1984–2023), this study analyzes elevational gradients and seasonal differences via a defined Asymmetry Index (AI = trend_TXx – trend_TXn). Key findings include: (1) Cold extremes (TXn) warmed markedly faster than warm extremes (TXx), with the mean TXn trend ~ 1.7 times greater. Spatially, rapid TXn warming concentrated in high-elevation zones (e.g., eastern Tibetan Plateau), whereas faster TXx warming dominated low-elevation areas (e.g., Sichuan Basin). (2) AI exhibited a significant negative correlation with elevation (p < 0.001), decreasing by ~ 0.107 °C/decade per 1000 m ascent, signaling a systematic altitudinal shift from “faster warming of warm extremes” to “faster warming of cold extremes.” (3) Pronounced seasonal heterogeneity emerged: growing-season AI was predominantly positive, but non-growing-season AI displayed a striking dipole pattern (negative at high elevations, positive at low elevations). (4) The seasonal difference itself depended on elevation, peaking at 3000–5000 m, indicating a fundamental change in governing processes across altitudes. This work provides a systematic, spatially explicit quantification of how extreme temperature asymmetry varies with both elevation and season over the Upper Yangtze River basin, a major monsoonal mountain system. Our analysis reveals a robust elevational gradient and a striking seasonal reversal in this asymmetry. The findings refine the understanding of elevation-dependent warming by revealing its asymmetric nature between temperature extremes, offering critical insights into the coupled roles of altitude and season in modulating climate responses within complex terrain.

Graphical abstract

This visual summary depicts our investigation into the asymmetry of extreme temperature changes over the Upper Yangtze River. Utilizing ERA5-Land temperature data and SRTM elevation data (1984–2023), we analyzed trends in warm (TXx) and cold (TXn) extremes and defined an Asymmetry Index (AI = Trend_TXx - Trend_TXn). The core findings reveal two dominant patterns: (1) A clear elevational gradient, where AI decreases with altitude, indicating faster warming of cold extremes at higher elevations. (2) A pronounced seasonal reversal, with positive AI (faster warming of warm extremes) dominating the growing season, and a dipole pattern (negative AI at high elevations, positive at low elevations) characterizing the non-growing season. The study concludes that the asymmetry of extreme temperature changes is a three-dimensional phenomenon co-modulated by topography and seasonal processes, providing critical insights into mountain climate sensitivity.