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Codominant water control on global interannual variability and trends in land surface phenology and greenness

机译:关于全球年际变化以及土地表面物候和绿色趋势的共水控制

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Identifying the relative importance of climatic and other environmental controls on the interannual variability and trends in global land surface phenology and greenness is challenging. Firstly, quantifications of land surface phenology and greenness dynamics are impaired by differences between satellite data sets and phenology detection methods. Secondly, dynamic global vegetation models (DGVMs) that can be used to diagnose controls still reveal structural limitations and contrasting sensitivities to environmental drivers. Thus, we assessed the performance of a new developed phenology module within the LPJmL (Lund-Potsdam-Jena managed Lands) DGVM with a comprehensive ensemble of three satellite data sets of vegetation greenness and ten phenology detection methods, thereby thoroughly accounting for observational uncertainties. The improved and tested model allows us quantifying the relative importance of environmental controls on interannual variability and trends of land surface phenology and greenness at regional and global scales. We found that start of growing season interannual variability and trends are in addition to cold temperature mainly controlled by incoming radiation and water availability in temperate and boreal forests. Warming-induced prolongations of the growing season in high latitudes are dampened by a limited availability of light. For peak greenness, interannual variability and trends are dominantly controlled by water availability and land-use and land-cover change (LULCC) in all regions. Stronger greening trends in boreal forests of Siberia than in North America are associated with a stronger increase in water availability from melting permafrost soils. Our findings emphasize that in addition to cold temperatures, water availability is a codominant control for start of growing season and peak greenness trends at the global scale.
机译:查明气候和其他环境控制措施对全球陆地表面物候和绿色度的年际变化和趋势的相对重要性具有挑战性。首先,由于卫星数据集和物候检测方法之间的差异,土地表面物候和绿色动态的定量化受到损害。其次,可用于诊断控制的动态全球植被模型(DGVM)仍然显示出结构局限性和对环境驱动因素的敏感性对比。因此,我们评估了LPJmL(隆德-波茨坦-耶那管理土地)DGVM中一个新开发的物候模块的性能,该系统综合了三个植被绿度卫星数据集和十种物候检测方法,从而全面解释了观测的不确定性。经过改进和测试的模型使我们能够量化区域和全球范围内环境控制对年际变化和土地表面物候和绿色趋势的相对重要性。我们发现,生长季节开始时的年际变化和趋势除了主要受温带和北方森林的辐射和水的可利用性控制的寒冷温度外。高纬度地区气候变暖导致的生长期延长受到光的有限利用的抑制。为了达到最高的绿色度,在所有区域中,年际变化和趋势主要受水的可利用性,土地利用和土地覆盖变化(LULCC)的控制。与北美洲相比,西伯利亚的北方森林的绿化趋势更强,这与永久冻土融化而使水的可利用性增加有关。我们的发现强调,除了低温以外,水的可利用性还可以控制生长季节的开始以及全球范围内绿色峰值的趋势。

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