Piao Shilong, Tan Jianguang, Chen Anping, Fu Yongshuo H, Ciais Philippe, Liu Qiang, Janssens Ivan A, Vicca Sara, Zeng Zhenzhong, Jeong Su-Jong, Li Yue, Myneni Ranga B, Peng Shushi, Shen Miaogen, Peñuelas Josep
1] Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing 100085, China [2] CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100085, China [3] Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
Nat Commun. 2015 Apr 23;6:6911. doi: 10.1038/ncomms7911.
Recent warming significantly advanced leaf onset in the northern hemisphere. This signal cannot be accurately reproduced by current models parameterized by daily mean temperature (T(mean)). Here using in situ observations of leaf unfolding dates (LUDs) in Europe and the United States, we show that the interannual anomalies of LUD during 1982-2011 are triggered by daytime (Tmax) more than by nighttime temperature (T(min)). Furthermore, an increase of 1 °C in Tmax would advance LUD by 4.7 days in Europe and 4.3 days in the United States, more than the conventional temperature sensitivity estimated from T(mean). The triggering role of Tmax, rather than the T(min) or T(mean) variable, is also supported by analysis of the large-scale patterns of satellite-derived vegetation green-up in spring in the northern hemisphere (>30 °N). Our results suggest a new conceptual framework of leaf onset using daytime temperature to improve the performance of phenology modules in current Earth system models.
近期的气候变暖显著提前了北半球的叶子萌动期。当前基于日平均温度（T(mean)）参数化的模型无法准确再现这一信号。在此，利用欧洲和美国叶子展开日期（LUDs）的实地观测数据，我们发现1982 - 2011年期间LUD的年际异常更多是由白天温度（Tmax）而非夜间温度（T(min)）触发的。此外，Tmax每升高1°C，欧洲的LUD会提前4.7天，美国会提前4.3天，这比根据T(mean)估算的传统温度敏感性更高。对北半球春季（>30°N）卫星遥感植被返青的大规模模式分析也支持了Tmax而非T(min)或T(mean)变量的触发作用。我们的研究结果提出了一个利用白天温度来改进当前地球系统模型中物候模块性能的叶子萌动新概念框架。
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