Vegetation greening is observed over the Arctic, and its feedback to Arctic amplification has attracted increasing attention. Previous studies have primarily focused on the temperature effect of a single environmental variable (e.g., albedo), while the separate contributions of land surface albedo, evapotranspiration (ET) and water vapor remain underexamined. In this study, we develop knowledge-based data-driven models (i.e., path analysis and machine learning) to estimate the temperature effect of vegetation greening and quantify the separate contributions of albedo, ET and water vapor in July and August from 1982 to 2015. The results show a wide range of temperature sensitivity to the NDVI (Normalized Difference Vegetation Index), and vegetation greening has led to Arctic warming of 0.76 °C, 0.68 °C, 0.83 °C in July and August and the average of the two months, respectively. Path analysis suggested that vegetation greening affects Arctic air temperature mainly by regulating albedo and water vapor. In July, changes in water vapor contributed the most to the temperature effect of vegetation greening with a contribution of 0.25 ± 0.08 °C, while in August, changes in albedo and water vapor had similar effects with a contribution of 0.21 ± 0.08 °C. In contrast, changes in ET have generated a negligible cooling effect due to small changes in ET. Further analysis shows similar positive contributions of albedo and water vapor in barren, graminoid tundra, prostrate-shrub tundra and erect-shrub, with contributions ranging from 0.18 ± 0.05°C to 0.30 ± 0.11°C, while changes in water vapor dominate vegetation’s temperature effect in wetlands, with contributions ranging from 0.26 ± 0.11°C to 0.32 ± 0.16°C. This study emphasizes the importance of considering multiple driving factors to assess the temperature effect of vegetation greening in a consistent framework and highlights the critical role of water vapor change in addition to the widely examined albedo in explaining Arctic warming.

中文翻译：

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解开水蒸气、反照率和蒸散变化对北极植被绿化温度影响的影响


在北极地区观察到植被绿化，其对北极放大的反馈引起了越来越多的关注。以前的研究主要集中在单个环境变量（例如反照率）的温度效应上，而地表反照率、蒸散 （ET） 和水蒸气的单独贡献仍然没有得到充分研究。在这项研究中，我们开发了基于知识的数据驱动模型（即路径分析和机器学习）来估计植被绿化的温度效应，并量化 1982 年至 2015 年 7 月和 8 月反照率、ET 和水蒸气的单独贡献。结果表明，北极对 NDVI （Normalized Difference Vegetation Index，归一化差值植被指数） 的温度敏感性范围很广，植被绿化导致北极在 7 月和 8 月以及两个月的平均气温分别升高了 0.76 °C、0.68 °C、0.83 °C。路径分析表明，植被绿化主要通过调节反照率和水汽来影响北极气温。7 月，水汽变化对植被绿化温度效应的贡献最大，贡献率为 0.25 ± 0.08 °C，而 8 月反照率和水汽变化的影响相似，贡献率为 0.21 ± 0.08 °C。 相比之下，由于 ET 的微小变化，ET 的变化产生的冷却效应可以忽略不计。进一步分析表明，反照率和水蒸气对贫瘠、禾本科苔原、匍匐灌木苔原和直立灌木也有类似的正贡献，贡献范围为 0.18 ± 0.05°C 至 0.30 ± 0.11°C，而水蒸气的变化在湿地植被的温度效应中占主导地位，贡献范围为 0.26 ± 0.11°C 至 0.32 ± 0.16°C。 本研究强调了在一致的框架中考虑多种驱动因素以评估植被绿化的温度影响的重要性，并强调了水蒸气变化以及广泛研究的反照率在解释北极变暖方面的关键作用。