Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling

CORC > 生态环境研究中心 > 中国科学院生态环境研究中心 > 城市与区域生态国家重点实验室

	Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling
	Pan, Shufen; Pan, Naiqing; Tian, Hanqin; Friedlingstein, Pierre; Sitch, Stephen; Shi, Hao; Arora, Vivek K.; Haverd, Vanessa; Jain, Atul K.; Kato, Etsushi
刊名	HYDROLOGY AND EARTH SYSTEM SCIENCES
	2020-03-31
卷号	24 期号:3 页码:1485-1509
ISSN号	1027-5606
英文摘要	Evapotranspiration (ET) is critical in linking global water, carbon and energy cycles. However, direct measurement of global terrestrial ET is not feasible. Here, we first reviewed the basic theory and state-of-the-art approaches for estimating global terrestrial ET, including remote-sensing-based physical models, machine-learning algorithms and land surface models (LSMs). We then utilized 4 remote-sensing-based physical models, 2 machine-learning algorithms and 14 LSMs to analyze the spatial and temporal variations in global terrestrial ET. The results showed that the ensemble means of annual global terrestrial ET estimated by these three categories of approaches agreed well, with values ranging from 589.6 mm yr(-1) (6.56 x 10(4) km(3) yr(-1)) to 617.1 mm yr(-1) (6.87 x 10(4) km(3) yr(-1)). For the period from 1982 to 2011, both the ensembles of remote-sensing-based physical models and machine-learning algorithms suggested increasing trends in global terrestrial ET (0.62 mm yr(-2) with a significance level of p < 0.05 and 0.38 mm yr(-2) with a significance level of p < 0.05, respectively). In contrast, the ensemble mean of the LSMs showed no statistically significant change (0.23 mm yr(-2), p > 0.05), although many of the individual LSMs reproduced an increasing trend. Nevertheless, all 20 models used in this study showed that anthropogenic Earth greening had a positive role in increasing terrestrial ET. The concurrent small interannual variability, i.e., relative stability, found in all estimates of global terrestrial ET, suggests that a potential planetary boundary exists in regulating global terrestrial ET, with the value of this boundary being around 600mm yr(-1). Uncertainties among approaches were identified in specific regions, particularly in the Amazon Basin and arid/semiarid regions. Improvements in parameterizing water stress and canopy dynamics, the utilization of new available satellite retrievals and deep-learning methods, and model-data fusion will advance our predictive understanding of global terrestrial ET.
内容类型	期刊论文
源URL	[http://ir.rcees.ac.cn/handle/311016/44308]
专题	生态环境研究中心_城市与区域生态国家重点实验室
推荐引用方式 GB/T 7714	Pan, Shufen,Pan, Naiqing,Tian, Hanqin,et al. Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling[J]. HYDROLOGY AND EARTH SYSTEM SCIENCES,2020,24(3):1485-1509.
APA	Pan, Shufen.,Pan, Naiqing.,Tian, Hanqin.,Friedlingstein, Pierre.,Sitch, Stephen.,...&Running, Steven W..(2020).Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling.HYDROLOGY AND EARTH SYSTEM SCIENCES,24(3),1485-1509.
MLA	Pan, Shufen,et al."Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling".HYDROLOGY AND EARTH SYSTEM SCIENCES 24.3(2020):1485-1509.