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<p>The Tibetan Plateau (TP) has experienced substantial surface warming in recent decades, driven by both external forcing and internal variability. In this study, we utilized 43 models from the CMIP6 abrupt-4xCO<sub>2</sub> experiment to examine both CO<sub>2</sub> radiative forcing and feedback mechanisms over the TP. Our analysis reveals that TP surface temperature increases by 7.3&#xa0;K in response to quadrupled CO<sub>2</sub>, significantly exceeding the global average warming of 5.3&#xa0;K. A quantitative assessment of the contributing processes identifies surface albedo feedback as the dominant driver, contributing 5.0&#xa0;K to the overall warming, followed by water vapor feedback at 2.2&#xa0;K. These feedback mechanisms are consistent across seasons, with surface albedo feedback remaining the dominant contributor, unlike in the Arctic where surface albedo feedback dominates in summer and lapse rate feedback dominates in winter. Surface albedo feedback is stronger in transitional seasons, especially in spring, than in winter and summer. As continental glaciers are prescribed in model simulations, the surface albedo feedback is largely attributed to snow cover reduction in this analysis. TP warming amplification is weaker than Arctic amplification, primarily due to the atmospheric heat transport (AHT) and temperature feedbacks, on an annual mean basis. Decomposed by season, in summer, the reduced warming is attributed to surface albedo feedback, which is more significant in the Arctic, while in winter, ocean heat uptake and lapse rate feedback favor stronger warming in Arctic. The dominant contributors, surface albedo feedback in summer and ocean heat uptake in winter, are balanced out in the annual mean results. The warming mechanisms are consistent across model groups with different resolutions, indicating they are not sensitive to model resolution. Additionally, we identify a strong negative correlation between moist and dry components of AHT, suggesting that moist AHT could be another important contributor to future TP warming. Covariance analysis of different warming contributions shows that atmospheric heat transport is negatively correlated with almost all other processes, suggesting TP surface warming is largely driven by local processes. Model variability in TP surface warming is substantial, with a standard deviation of 1.9&#xa0;K. Surface albedo feedback accounts for 76% of the spread. Our findings highlight the critical role of accurately simulating land processes to improve the reliability of future TP climate projections. Comparisons of warming mechanisms across the abrupt-4xCO<sub>2</sub>, historical, and SSP experiments confirm that the warming mechanisms driving TP surface warming are robust and will likely continue under future climate scenarios.</p>

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Amplified tibetan plateau surface warming in CO2-induced global warming simulations

  • 期刊论文

  • 发表日期：

    2025年7月25日

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  • Yuwei Wang,
  • Zhenghui Lu,
  • Ziqian Wang,
  • Fei Huang,
  • Jingchuan Zhao,
  • Han Huang,
  • Jing Feng,
  • Yi Huang

摘要

The Tibetan Plateau (TP) has experienced substantial surface warming in recent decades, driven by both external forcing and internal variability. In this study, we utilized 43 models from the CMIP6 abrupt-4xCO2 experiment to examine both CO2 radiative forcing and feedback mechanisms over the TP. Our analysis reveals that TP surface temperature increases by 7.3 K in response to quadrupled CO2, significantly exceeding the global average warming of 5.3 K. A quantitative assessment of the contributing processes identifies surface albedo feedback as the dominant driver, contributing 5.0 K to the overall warming, followed by water vapor feedback at 2.2 K. These feedback mechanisms are consistent across seasons, with surface albedo feedback remaining the dominant contributor, unlike in the Arctic where surface albedo feedback dominates in summer and lapse rate feedback dominates in winter. Surface albedo feedback is stronger in transitional seasons, especially in spring, than in winter and summer. As continental glaciers are prescribed in model simulations, the surface albedo feedback is largely attributed to snow cover reduction in this analysis. TP warming amplification is weaker than Arctic amplification, primarily due to the atmospheric heat transport (AHT) and temperature feedbacks, on an annual mean basis. Decomposed by season, in summer, the reduced warming is attributed to surface albedo feedback, which is more significant in the Arctic, while in winter, ocean heat uptake and lapse rate feedback favor stronger warming in Arctic. The dominant contributors, surface albedo feedback in summer and ocean heat uptake in winter, are balanced out in the annual mean results. The warming mechanisms are consistent across model groups with different resolutions, indicating they are not sensitive to model resolution. Additionally, we identify a strong negative correlation between moist and dry components of AHT, suggesting that moist AHT could be another important contributor to future TP warming. Covariance analysis of different warming contributions shows that atmospheric heat transport is negatively correlated with almost all other processes, suggesting TP surface warming is largely driven by local processes. Model variability in TP surface warming is substantial, with a standard deviation of 1.9 K. Surface albedo feedback accounts for 76% of the spread. Our findings highlight the critical role of accurately simulating land processes to improve the reliability of future TP climate projections. Comparisons of warming mechanisms across the abrupt-4xCO2, historical, and SSP experiments confirm that the warming mechanisms driving TP surface warming are robust and will likely continue under future climate scenarios.