The large influence of climate model bias on terrestrial carbon cycle simulations
The large influence of climate model bias on terrestrial carbon cycle simulations
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DOI：
10.1088/1748-9326/12/1/014004
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发表时间：
2017-01-01
影响因子：
6.7
通讯作者：
Smith, Benjamin
中科院分区：
文献类型：
--
作者：
Ahlstrom, Anders;Schurgers, Guy;Smith, Benjamin
全球植被模型和陆地碳循环模型广泛用于预测陆地生态系统的碳平衡。此类模型的集合显示碳平衡预测存在很大差异，从陆地生物圈大量吸收碳到释放碳，这对全球气候变化下大气二氧化碳浓度的相关反馈构成了很大的不确定性。可能导致这种不确定性的误差和偏差包括生态系统模型结构、参数以及大气环流模型 (GCM) 或地球系统模型 (ESM) 大气组成部分的气候输出的强迫，例如准备用于 IPCC 气候变化评估。这些影响因素对碳循环预测总体不确定性的相对重要性尚未得到很好的描述。在这里，我们通过强制使用单一的全球生态系统碳循环模型来研究气候模型衍生偏差的作用，其中原始气候输出来自 CMIP5 集合的 15 个 ESM 和 GCM。我们表明，当前和未来碳循环模拟的结果集合之间的变化是由于温度、降水和传入短波辐射的年度平均值的偏差而传播的。碳库的未来变化以及土地碳汇趋势也受到气候偏差的影响，尽管影响程度小于碳库的绝对规模。我们的结果表明，气候偏差可能是陆地碳通量和库的 ESM 模拟中很大一部分不确定性的原因，约占 ESM 报告范围的 40%。我们的结论是，必须减少气候偏差引起的不确定性，才能做出准确的大气-碳循环耦合预测。
Global vegetation models and terrestrial carbon cycle models are widely used for projecting the carbon balance of terrestrial ecosystems. Ensembles of such models show a large spread in carbon balance predictions, ranging from a large uptake to a release of carbon by the terrestrial biosphere, constituting a large uncertainty in the associated feedback to atmospheric CO2 concentrations under global climate change. Errors and biases that may contribute to such uncertainty include ecosystem model structure, parameters and forcing by climate output from general circulation models (GCMs) or the atmospheric components of Earth system models (ESMs), e.g. as prepared for use in IPCC climate change assessments. The relative importance of these contributing factors to the overall uncertainty in carbon cycle projections is not well characterised. Here we investigate the role of climate model-derived biases by forcing a single global ecosystem-carbon cycle model, with original climate outputs from 15 ESMs and GCMs from the CMIP5 ensemble. We show that variation among the resulting ensemble of present and future carbon cycle simulations propagates from biases in annual means of temperature, precipitation and incoming shortwave radiation. Future changes in carbon pools, and thus land carbon sink trends, are also affected by climate biases, although to a smaller extent than the absolute size of carbon pools. Our results suggest that climate biases could be responsible for a considerable fraction of the large uncertainties in ESM simulations of land carbon fluxes and pools, amounting to about 40% of the range reported for ESMs. We conclude that climate bias-induced uncertainties must be decreased to make accurate coupled atmosphere-carbon cycle projections.