Simulating terrestrial carbon fluxes using the new biosphere model “biosphere model integrating eco‐physiological and mechanistic approaches using satellite data” (BEAMS)
Simulating terrestrial carbon fluxes using the new biosphere model “biosphere model integrating eco‐physiological and mechanistic approaches using satellite data” (BEAMS)
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DOI：
10.1029/2005jg000045
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发表时间：
2005-12
影响因子：
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通讯作者：
T. Sasai;K. Ichii;Y. Yamaguchi;R. Nemani
中科院分区：
文献类型：
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作者：
T. Sasai;K. Ichii;Y. Yamaguchi;R. Nemani
[1]在这项研究中，我们提出了一种新的生物圈模型，称为生物圈模型，它结合了利用卫星数据(BEMS)的生态生理和力学方法。BEMS为计算影响植物生长的环境应力(应力)提供了一种新的方法。胁迫是使用光合作用模型和气孔导度公式进行生态生理计算的，提供了比以前的模型更接近实际的结果。应力值被用来通过光利用效率的概念来估计总初级生产(GPP)。我们使用BEAM，包括我们的新的压力方法，来研究全球净初级生产力(NPP)和净生态系统生产力(NEP)的时空格局。BEMS使用全球范围的卫星和气候数据在1982-2000年间运行。模型结果与通量站点的观测结果比较表明，BEAM预报的GPP值与GPP实测值基本一致。将得到的应力值与MOD17和CASA的应力值进行比较；这三种方法产生了对比的空间图案。通过比较预测和观测的NPP，可以充分估计每种植物功能类型的NPP模式。在趋势分析方面，大多数区域的净生产总值在1982-2000年间有所增加。在欧洲、俄罗斯和加拿大东北部观察到的NPP趋势与Nemani等人提出的不同。(2003)；我们将这些差异归因于与气候有关的过程。模拟的全球NEP年际变化与反模拟结果相似。对NEP的敏感性研究表明，NEP的年际变化强烈地受气温、降水、CO2和吸收的光合作用有效辐射的影响。
[1] In this study we present a new biosphere model called the Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data (BEAMS). BEAMS provides a new method of calculating the environmental stress affecting plant growth (Stress). Stress is calculated eco-physiologically using a photosynthesis model and stomatal conductance formulation, providing a more realistic result than previous models. Stress values are used to estimate Gross Primary Production (GPP) estimates via the light use efficiency concept. We used BEAMS, including our new Stress approach, to investigate global spatial and temporal patterns of net primary production (NPP) and net ecosystem production (NEP). BEAMS was run for the years 1982–2000 using global scale satellite and climate data. Comparison of model results with observational measurements at flux sites reveals that GPP values predicted by BEAMS agree with measured GPP. Obtained Stress values were compared with those of MOD17 and CASA; the three methods produce contrasting spatial patterns. Upon comparing predicted and observed NPP, the pattern of NPP for each plant functional type can be adequately estimated. In terms of trend analysis, NPP increased for the years 1982–2000 in most regions. Different NPP trends were observed in Europe, Russia, and northeast Canada than those proposed by Nemani et al. (2003); we attribute these differences to climate-related processes. Simulated interannual variations in global NEP are similar to results from inverse modeling. A sensitivity study of obtained NEP shows that the interannual variability in NEP is strongly controlled by air temperature, precipitation, CO2, and the fraction of absorbed photosynthetically active radiation.