Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
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DOI：
10.5194/tc-13-2001-2019
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发表时间：
2019-07
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影响因子：
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通讯作者：
A. West;M. Collins;E. Blockley;J. Ridley;A. Bodas‐Salcedo
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作者：
A. West;M. Collins;E. Blockley;J. Ridley;A. Bodas‐Salcedo
抽象。提出了一个新的框架，用于分析模型北极海冰偏差的近因，证明与CMIP 5模型HadGEM 2-ES（哈德利中心全球环境模型版本2 -地球系统）。在这个框架内，北极海冰体积被视为综合表面能量平衡的结果，通过体积平衡。一个简单的模型允许的局部依赖的表面通量的具体模型变量被描述为时间和空间的函数。当这些与参考数据集相结合时，可以估计每个变量中由模型偏差引起的表面通量偏差。该方法允许的作用，表面冰厚和冰厚增长反馈海冰体积平衡偏差被量化沿着与模型偏差的作用，变量不直接相关的海冰体积。它显示的HadGEM 2-ES海冰体积模拟中的偏差是由于春季表面融化开始日期的偏差，部分抵消了冬季下降流长波辐射的偏差。该框架原则上适用于任何模型，并有可能大大提高对模拟海冰状态下集合传播原因的理解。第二个发现是，观测的不确定性是最大的不确定性的原因，在诱导表面通量偏差计算。
Abstract. A new framework is presented for analysing the proximate causes of model Arctic sea ice biases, demonstrated with the CMIP5 model HadGEM2-ES (Hadley Centre Global Environment Model version 2 – Earth System). In this framework the Arctic sea ice volume is treated as a consequence of the integrated surface energy balance, via the volume balance. A simple model allows the local dependence of the surface flux on specific model variables to be described as a function of time and space. When these are combined with reference datasets, it is possible to estimate the surface flux bias induced by the model bias in each variable. The method allows the role of the surface albedo and ice thickness–growth feedbacks in sea ice volume balance biases to be quantified along with the roles of model bias in variables not directly related to the sea ice volume. It shows biases in the HadGEM2-ES sea ice volume simulation to be due to a bias in spring surface melt onset date, partly countered by a bias in winter downwelling longwave radiation. The framework is applicable in principle to any model and has the potential to greatly improve understanding of the reasons for ensemble spread in the modelled sea ice state. A secondary finding is that observational uncertainty is the largest cause of uncertainty in the induced surface flux bias calculation.