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arXiv 1609.06338physics.ao-ph
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用贝叶斯校准评估简单南极冰盖模式中退缩机制的影响

Assessing the Impact of Retreat Mechanisms in a Simple Antarctic Ice Sheet Model Using Bayesian Calibration

Kelsey L. Ruckert, Gary Shaffer, David Pollard, Yawen Guan, Tony E. Wong, Chris E. Forest, Klaus Keller

摘要:

南极冰盖(AIS)对气候强迫变化的响应是海平面变化的重要驱动因素。人为的气候变化可能会推动相当大的AIS临界点响应,随后增加沿海洪水的风险。许多分析洪水风险的研究使用简单的模型来预测AIS的未来响应及其对海平面的影响。这些分析提供了重要的新见解,但它们通常对海洋冰盖不稳定性(MISI)或海洋冰崖不稳定性(MICI)等潜在重要过程的影响保持沉默。这些近似可以很好地证明,并导致更简约和透明的模型结构。这就提出了一个问题,即这种近似如何影响后报和预测。在这里,我们校准一个以前发表的和相对简单的AIS模型,它忽略了MICI和区域特征的影响,使用组合的观测约束和贝叶斯反演方法。具体来说,我们近似的影响,失踪的MICI比较我们的结果与专家评估更现实的模型和量化的偏差在末次间冰期时,MICI可能已经触发。我们的研究结果表明,该模型可以近似MISI的过程中,并重现预测的中位数融化从以前的一些专家评估在2100年。然而,我们的平均后报大约是末次间冰期观测数据的3/4,我们的平均预测大约是2100年MICI模型平均值的1/6和1/10。这些结果表明,缺少MICI和/或区域特征可能会导致在变暖期间AIS融化的低偏差,因此在预测的海平面和洪水风险中存在潜在的低偏差。

英文摘要:

The response of the Antarctic ice sheet (AIS) to changing climate forcings is an important driver of sea-level changes. Anthropogenic climate change may drive a sizeable AIS tipping point response with subsequent increases in coastal flooding risks. Many studies analyzing flood risks use simple models to project the future responses of AIS and its sea-level contributions. These analyses have provided important new insights, but they are often silent on the effects of potentially important processes such as Marine Ice Sheet Instability (MISI) or Marine Ice Cliff Instability (MICI). These approximations can be well justified and result in more parsimonious and transparent model structures. This raises the question of how this approximation impacts hindcasts and projections. Here, we calibrate a previously published and relatively simple AIS model, which neglects the effects of MICI and regional characteristics, using a combination of observational constraints and a Bayesian inversion method. Specifically, we approximate the effects of missing MICI by comparing our results to those from expert assessments with more realistic models and quantify the bias during the last interglacial when MICI may have been triggered. Our results suggest that the model can approximate the process of MISI and reproduce the projected median melt from some previous expert assessments in the year 2100. Yet, our mean hindcast is roughly 3/4 of the observed data during the last interglacial period and our mean projection is roughly 1/6 and 1/10 of the mean from a model accounting for MICI in the year 2100. These results suggest that missing MICI and/or regional characteristics can lead to a low-bias during warming period AIS melting and hence a potential low-bias in projected sea levels and flood risks.

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