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CMIP5和CMIP6模式对1950~2014年中国陆地植被碳储量的模拟评估

Evaluation of China’s Terrestrial Vegetation Carbon Stocks Simulated by the CMIP5 and CMIP6 Models during 1950–2014

  • 摘要: 选取两套植被碳密度数据和首次至第九次(1950~2018年)中国森林资源清查数据、基于遥感的土地覆盖数据,对比评估CMIP5和CMIP6地球系统模式对中国陆地植被碳的时空分布及其变化趋势的模拟能力,并进一步探究CMIP5和CMIP6土地变化数据的异同对植被碳储量模拟结果的影响。1995~2004年多模式平均结果表明,CMIP5和CMIP6模式均高估了中国植被碳储量,分别为28.0±6.0 Pg(C),25.3±7.7 Pg(C),两套参考数据分别为18.1 Pg(C)和18.7 Pg(C)。CMIP6模式对植被碳空间分布的模拟优于CMIP5模式,其各项泰勒评分(TSS)指标均显著提高,模式间不确定性有所减小。1950~1990年,CMIP5和CMIP6模拟的中国区植被为碳源,分别为−89.4 Tg(C) a−1和−58.2 Tg(C) a−1,且于1980年代显著增强,分别为−256.6 Tg(C) a−1和−171.0 Tg(C) a−1。1990~2014年CMIP5模式中植被碳源减弱−48.1 Tg(C) a−1,而CMIP6模式中植被则转变为碳汇42.8 Tg(C) a−1P<0.05。CMIP5与CMIP6模式对中国植被碳源汇模拟的差异和模式的土地变化情况密切相关,相较于CMIP5模式,CMIP6模式的土地变化数据(LUH2)和中国森林资源清查结果更吻合,1980年代后模式森林覆盖度的变化趋势与清查结果更为接近。本研究显示目前用于CMIP模拟的LUH1、LUH2数据与中国森林和农田在过去65年的变化情况有较大差异,采用更准确的土地变化数据对提高下一代CMIP模式植被碳模拟效果具有重要作用。

     

    Abstract: The performances of the CMIP5 and CMIP6 earth system models in simulating China’s terrestrial vegetation biomass were assessed using two sets of observation-based biomass carbon density data, the first to ninth (1950–2018) China Forest Resource Inventory data and a set of remote sensing land cover data. Furthermore, the impacts of different land-use harmonization (LUH) datasets on the vegetation biomass simulations of the CMIP5 and CMIP6 models were explored. Our results show that these models overestimate China’s total vegetation carbon storage during 1995–2004 28.0±6.0 Pg(C) for CMIP5 and 25.3±7.7 Pg(C) for CMIP6 and 18.1 and 18.7 Pg(C) for the two sets of reference data. The spatial distributions of the vegetation carbon density simulated using the CMIP6 model are better than those by CMIP5, demonstrating improved Taylor skill score(hereinafter referred to as “TSS”) values and reduced model uncertainties. During 1950–1990, both CMIP5 and CMIP6 models display that China’s vegetation acts as carbon sources −89.4 Tg(C) a−1 for CMIP5 and −58.2 Tg(C) a−1 for CMIP6. These carbon sources substantially increase to −256.6 Tg(C) a−1 (CMIP5) and −171.0 Tg(C) a−1 (CMIP6) in the 1980s. However, from 1990 to 2014, the CMIP5 model shows that carbon sources reduce to −48.1 Tg(C) a−1, while the CMIP6 model indicates a shift from carbon sources to weak carbon sinks 42.8 Tg(C) a−1, P < 0.05. The differences in China’s vegetation carbon between CMIP5 and CMIP6 are closely related to their different land change conditions. Compared with LUH1 used in CMIP5, the forest coverage and changes depicted in LUH2 (used in CMIP6) are more consistent with the China Forest Inventory data and are closer to that since the 1980s. This study implies that LUH datasets used in CMIP exhibit a large bias for China’s forest and crop trajectories over the past 65 years. Therefore, more accurate land cover datasets are essential for improving the simulation of vegetation carbon in future CMIP models.

     

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