The shape and extent of the Greenland Ice Sheet (GIS) during the Last Interglacial (LIG) is a matter of controversy, with different studies proposing a wide range of reconstructions. Here, for the first time, we combine stable water isotopic information from ice cores with isotope‐enabled climate model outputs to investigate the problem. Exploring the space of possible ice sheet geometries by simulation is prohibitively expensive. We address this problem by using a Gaussian process emulator as a statistical surrogate of the full climate model. The emulator is calibrated using the results of a small number of carefully chosen simulations and then permits fast, probabilistic predictions of the simulator outputs at untried inputs. The inputs are GIS morphologies, parameterized through a dimension‐reduction technique adapted to the spherical geometry of the setting. Based on the emulator predictions, the characteristics of morphologies compatible with the available ice core measurements are explored, leading to a reduction in uncertainty on the LIG GIS morphology. Moreover, a scenario‐based approach allows to assess the gains in uncertainty reduction which would result from the availability of better dated LIG measurements in Greenland ice cores.

中文翻译：

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使用冰芯和高斯过程模拟来恢复格陵兰冰盖在最后一次冰期之间的变化

上一次冰间期（LIG）期间格陵兰冰原（GIS）的形状和范围是一个有争议的问题，不同的研究提出了广泛的重建方案。在这里，我们首次将来自冰芯的稳定水同位素信息与启用同位素的气候模型输出相结合，以研究该问题。通过模拟来探索可能的冰盖几何形状的空间是非常昂贵的。我们通过使用高斯过程仿真器作为整个气候模型的统计替代来解决此问题。使用少量精心选择的仿真结果对仿真器进行校准，然后允许在未尝试输入时对仿真器输出进行快速，概率性的预测。输入是GIS形态，通过适用于设置球形几何形状的降维技术进行参数化。基于仿真器的预测，探索了与可用冰芯测量值兼容的形态特征，从而降低了LIG GIS形态的不确定性。此外，基于场景的方法允许评估不确定性降低的收益，这是由于格陵兰冰芯中提供了更及时的LIG测量结果而导致的。