摘要:生态系统模型是模拟全球陆地生态系统碳循环的重要工具，但是其在全球不同区域的模拟存在很大的不确定性。如何评估陆地生态系统模型的不确定性是一项重要的研究。以北美地区为例，利用8个高塔观测站点同步获取的大气CO₂和羰基硫（OCS）浓度数据，结合WRF-STILT大气粒子扩散模型，评估了CASA-GFED3、SiB3和SiBCASA三种陆地生态系统模型模拟总初级生产力（GPP）和净生态系统CO₂交换（NEE）通量的不确定性。结果表明，SiB3模型能很好地模拟北美陆地生态系统GPP和NEE的季节变化时相和幅度，在3种模型中具有最佳的模拟能力；CASA-GFED3模型模拟的NEE季节变化较为理想、但对生长季GPP的模拟存在较大的误差，SiBCASA模型在模拟冬季晚期和春季早期的NEE和GPP时表现较不理想。研究证明了大气CO₂和OCS在评估陆地生态系统模型碳通量模拟的不确定性中的作用，为利用大气CO₂和OCS观测数据优化计算陆地生态系统光合和呼吸碳通量提供了理论支撑。



Abstract:Terrestrial Biosphere Models (TBMs) are important tools to simulate the carbon cycle of global terrestrial ecosystem, but there are still large uncertainties in their simulation in different regions over the globe. How to evaluate the uncertainty of TBMs is a critical research issue. In this study, taking North America as study area, the uncertainty of gross primary production (GPP) and net ecosystem exchange of CO₂ (NEE) fluxes simulated by CASA-GFED3, SiB3 and SiBCASA was evaluated by using atmospheric concentration data of CO₂ and carbonyl sulfide (OCS) simultaneously obtained from 8 high tower observational stations and WRF-STILT atmospheric particle diffusion model. The results show that the SiB3 model can well simulate the seasonal changes of GPP and NEE in terrestrial ecosystem, and has the best simulation ability among the three models; the CASA-GFED3 model can simulate the seasonal changes of NEE, but there is a large error in the simulation of GPP in growing season; and the SiBCASA model is not able to reasonably simulate NEE and GPP in late winter and early spring. This study proved the role of atmospheric CO₂ and OCS in evaluating the uncertainty of carbon fluxes simulated by TBMs, and provided theoretical support for optimizing the estimation of photosynthetic and respiratory carbon flux of terrestrial ecosystem by using the observation data of atmospheric CO₂ and OCS.





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