Meixian Liu, Alexander Y Sun, Kairong Lin, Wei Luo, Xinjun Tu, Xiaohong Chen
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Comparing results over the globe and across 10 ET data sets (used as inputs), which are based on diverse mechanisms and algorithms, we find that the approach can capture canopy resistance well (mean correlation of 0.84 ± 0.04, mean relative Root Mean Squared Error of 4.4% ± 1.0%, and mean relative Mean Absolute Error of 5.8% ± 1.4%), and the estimated r cs are very close to those estimated using another method ( R 2 = 0.92), which is based on a quite different hypothesis that is only suitable for saturated regions. Based on these, we find that the r cs shows an overall increasing trend (0.43 ± 0.13 s m −1 year −1 ) over the globe (at 77.6% ± 3.9% of the land grid cells) during 1982–2014, and the air temperature dominates the variabilities of r cs in regions with decreasing r cs (mean relative contribution of 57.9% ± 11.4%), while air CO 2 concentration controls the changes in r cs in regions with increasing r cs (mean relative contribution of 47.3% ± 8.0%). Moreover, we also find that the traditional PET estimator explicitly overestimates the increasing trends in PET, and tends to overestimate (underestimate) the increasing (decreasing) trends in regions with increasing (decreasing) PET. 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引用次数: 0
摘要
非限水冠层阻力(rcs),又称体积气孔阻力或表面阻力,是估算潜在蒸散发(PET)的关键变量,在生态水文相关领域得到广泛应用。然而,量化碳排放是一项具有挑战性的工作。在这里,我们开发了一种估算全球r cs的方法。对比基于不同机制和算法的全球和10个ET数据集(作为输入)的结果,我们发现该方法可以很好地捕获冠层阻力(平均相关系数为0.84±0.04,平均相对均方根误差为4.4%±1.0%,平均相对平均绝对误差为5.8%±1.4%),估计的r cs与使用另一种方法估计的r cs非常接近(r2 = 0.92)。这是基于一个完全不同的假设,只适用于饱和区域。在此基础上,我们发现r cs显示了一个总体增加的趋势(0.43±0.13 s m 1年−−1)在世界各地(在77.6%±3.9%的土地网格细胞)在1982 - 2014年期间,和空气温度的主导着可变性r cs与减少区域r cs(平均57.9%±11.4%)的相对贡献,而空气CO 2浓度控制地区r cs的变化随着r cs(平均47.3%±8.0%)的相对贡献。此外,我们还发现传统的PET估计器明显高估了PET的增加趋势,并且倾向于高估(低估)PET增加(减少)区域的增加(减少)趋势。这些发现可以提高我们对水-植被-环境复杂相互作用的认识,并有助于开发更准确的模型来量化全球变化对水资源的影响。
Estimating dynamic non‐water‐limited canopy resistance over the globe: Changes, contributors and implications
Abstract Non‐water‐limited canopy resistance ( r cs , also known as the bulk stomatal resistance or surface resistance) is a critical variable in estimating potential evapotranspiration (PET), which is widely used in ecohydrology related fields. However, quantifying r cs is a challenging work. Here we develop an approach for estimating r cs over the globe. Comparing results over the globe and across 10 ET data sets (used as inputs), which are based on diverse mechanisms and algorithms, we find that the approach can capture canopy resistance well (mean correlation of 0.84 ± 0.04, mean relative Root Mean Squared Error of 4.4% ± 1.0%, and mean relative Mean Absolute Error of 5.8% ± 1.4%), and the estimated r cs are very close to those estimated using another method ( R 2 = 0.92), which is based on a quite different hypothesis that is only suitable for saturated regions. Based on these, we find that the r cs shows an overall increasing trend (0.43 ± 0.13 s m −1 year −1 ) over the globe (at 77.6% ± 3.9% of the land grid cells) during 1982–2014, and the air temperature dominates the variabilities of r cs in regions with decreasing r cs (mean relative contribution of 57.9% ± 11.4%), while air CO 2 concentration controls the changes in r cs in regions with increasing r cs (mean relative contribution of 47.3% ± 8.0%). Moreover, we also find that the traditional PET estimator explicitly overestimates the increasing trends in PET, and tends to overestimate (underestimate) the increasing (decreasing) trends in regions with increasing (decreasing) PET. These findings can improve our knowledge on the complex water‐vegetation‐environment interactions and would be helpful for developing more accurate models for quantifying the impacts of global change on water resources.
期刊介绍:
Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.