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The land-atmosphere water flux in the tropics

机译:热带的陆地-大气水通量

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Tropical vegetation is a major source of global land surface evapotranspiration, and can thus play a major role in global hydrological cycles and global atmospheric circulation. Accurate prediction of tropical evapotranspiration is critical to our understanding of these processes under changing climate. We examined the controls on evapotranspiration in tropical vegetation at 21 pan-tropical eddy covariance sites, conducted a comprehensive and systematic evaluation of 13 evapotranspiration models at these sites, and assessed the ability to scale up model estimates of evapotranspiration for the test region of Amazonia. Net radiation was the strongest determinant of evapotranspiration (mean evaporative fraction was 0.72) and explained 87% of the variance in monthly evapotranspiration across the sites. Vapor pressure deficit was the strongest residual predictor (14%), followed by normalized difference vegetation index (9%), precipitation (6%) and wind speed (4%). The radiation-based evapotranspiration models performed best overall for three reasons: (1) the vegetation was largely decoupled from atmospheric turbulent transfer (calculated from b decoupling factor), especially at the wetter sites; (2) the resistance-based models were hindered by difficulty in consistently characterizing canopy (and stomatal) resistance in the highly diverse vegetation; (3) the temperature-based models inadequately captured the variability in tropical evapotranspiration. We evaluated the potential to predict regional evapotranspiration for one test region: Amazonia. We estimated an Amazonia-wide evapotranspiration of 1370 mm yrp#, but this value is dependent on assumptions about energy balance closure for the tropical eddy covariance sites; a lower value (1096 mm yrp#) is considered in discussion on the use of flux data to validate and interpolate models.
机译:热带植被是全球陆地蒸散的主要来源,因此可以在全球水文循环和全球大气环流中发挥重要作用。准确预测热带蒸散量对我们了解气候变化下的这些过程至关重要。我们检查了21个泛热带涡度协方差点热带植被蒸散量的控制,对这些部位的13个蒸散量模型进行了全面而系统的评估,并评估了对亚马逊河试验区的蒸散量模型估算进行放大的能力。净辐射量是蒸散量的最强决定因素(平均蒸发分数为0.72),可以解释整个站点每月蒸散量变化的87%。蒸气压亏空是最强的残差预测因子(14%),其次是归一化差异植被指数(9%),降水(6%)和风速(4%)。基于辐射的蒸散模型总体上表现最佳,原因有以下三个:(1)植被与大气湍流转移(根据b解耦因子计算)很大程度上脱钩,尤其是在较湿润的地方; (2)由于难以一致地描述高度多样性植被中的冠层(和气孔)抗性,因此阻碍了基于抗性的模型的建立; (3)基于温度的模型不足以捕捉热带蒸散量的变化。我们评估了预测一个测试区域:亚马逊地区的区域蒸散的潜力。我们估计整个亚马逊地区的蒸散量为1370毫米yrp#,但该值取决于有关热带涡度协方差站点能量平衡关闭的假设。在讨论使用通量数据验证和内插模型时,应考虑使用较低的值(yrp#1096 mm)。

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