从光利用效率法模拟初级生产力总值时气候引起的不确定性

IF 3.7 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Jiyan Wang, Yong Wang, Xinyao Xie, Wei Zhao, Changlin Wu, Xiaobin Guan, Tao Yang
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引用次数: 0

摘要

光利用效率(LUE)模型以及卫星植被图和气候再分析产品是估算大尺度总初级生产力(GPP)的有效工具。然而,人们对基于 LUE 的总初级生产力中由气候引起的不确定性仍然知之甚少,特别是忽略气候波动引起的时间比例不确定性。在此,采用了两种每 1 小时一次的再分析产品以及基于站点的观测数据,来驱动 194 个涡度协方差(EC)站点的双叶 LUE 模型。以平均绝对偏差(MAD)和纳什-苏特克利夫效率(NSE)为标准,对观测驱动和再分析驱动的 1 小时分辨率 GPP 与 EC GPP 进行了评估,以说明再分析产品的不确定性。此外,还通过比较分布式 GPP(以 1 小时分辨率气候驱动因素建模)和块状 GPP(以 6 小时分辨率气候驱动因素建模)来描述气候引起的时间比例不确定性。结果表明,在 1 小时分辨率下,再分析驱动的 GPP 与 EC GPP 的关系(MAD = 0.14 gC m-2h-1,NSE = 0.48)弱于观测驱动的 GPP(MAD = 0.12 gC m-2h-1,NSE = 0.60),证实了再分析产品不可忽略的气候诱导不确定性。此外,网格辐射引起的气候诱导不确定性明显大于温度和水汽压差(VPD)引起的气候诱导不确定性。在 6 小时分辨率下,观测驱动的和再分析驱动的块状 GPP 与 EC GPP 的关系(MAD = 0.63 gC m-26h-1,NSE = 0.54)均低于相应的分布式 GPP(MAD = 0.57 gC m-26h-1,NSE = 0.59),表明在 6 小时 GPP 估计中,气候诱导的时间比例不确定性非常明显。这项研究强调,必须改进再分析产品,以更精确地捕捉短期波动,并减少粗时间分辨率 GPP 估算值的比例不确定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Climate-Induced Uncertainty in Modeling Gross Primary Productivity From the Light Use Efficiency Approach

Light use efficiency (LUE) models, along with satellite-based vegetation maps and climatic reanalysis products as drivers, are effective tools for estimating large-scale gross primary productivity (GPP). However, the climate-induced uncertainty in LUE-based GPP remains poorly understood, particularly the temporal scaling uncertainty from ignored climatic fluctuations. Here, two 1-hourly reanalysis products, along with site-based observations, were employed to drive a two-leaf LUE model at 194 eddy-covariance (EC) sites. The observation-driven and reanalysis-driven GPP at the 1-hourly resolution were evaluated against EC GPP to illustrate the uncertainty from reanalysis products, with mean absolute deviation (MAD) and Nash-Sutcliffe efficiency (NSE) as criterion. Moreover, the climate-induced temporal scaling uncertainty was characterized by comparing distributed GPP (modeled with 1-hourly resolution climatic drivers) and lumped GPP (modeled with 6-hourly resolution climatic drivers). At the 1-hourly resolution, results demonstrated that the reanalysis-driven GPP showed a weaker relationship with EC GPP (MAD = 0.14 gC m−2h−1, NSE = 0.48) than the observation-driven GPP (MAD = 0.12 gC m−2h−1, NSE = 0.60), confirming the nonnegligible climate-induced uncertainty from reanalysis products. Additionally, the climate-induced uncertainty arising from gridded radiation was found to be significantly larger than that associated with temperature and vapor pressure deficit (VPD). At the 6-hourly resolution, both the observation-driven and reanalysis-driven lumped GPP exhibited a lower relationship with EC GPP (MAD = 0.63 gC m−26h−1, NSE = 0.54) than the corresponding distributed GPP (MAD = 0.57 gC m−26h−1, NSE = 0.59), demonstrating that the climate-induced temporal scaling uncertainty in 6-hourly GPP estimates was significantly apparent. This study emphasizes the imperative to refine reanalysis products for more precise capture of short-term fluctuations and to reduce scaling uncertainties in coarse temporal resolution GPP estimates.

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来源期刊
Journal of Geophysical Research: Biogeosciences
Journal of Geophysical Research: Biogeosciences Earth and Planetary Sciences-Paleontology
CiteScore
6.60
自引率
5.40%
发文量
242
期刊介绍: JGR-Biogeosciences focuses on biogeosciences of the Earth system in the past, present, and future and the extension of this research to planetary studies. The emerging field of biogeosciences spans the intellectual interface between biology and the geosciences and attempts to understand the functions of the Earth system across multiple spatial and temporal scales. Studies in biogeosciences may use multiple lines of evidence drawn from diverse fields to gain a holistic understanding of terrestrial, freshwater, and marine ecosystems and extreme environments. Specific topics within the scope of the section include process-based theoretical, experimental, and field studies of biogeochemistry, biogeophysics, atmosphere-, land-, and ocean-ecosystem interactions, biomineralization, life in extreme environments, astrobiology, microbial processes, geomicrobiology, and evolutionary geobiology
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