A representative modern calibration dataset is an essential prerequisite for a reliable quantitative reconstruction of paleoclimate. However, there has been a notable lack of systematic research on the optimal filtering of calibration sets. Four representative high-resolution pollen records were selected to repeatedly reconstruct paleoclimate using multiple approaches such as geographical distance, analogues and climate gradient. Comparisons of pollen-based reconstructions indicate that these varied approaches exhibit significant discrepancy in model performance and reconstruction accuracy under different geographical circumstances and time scales. Generally, in terms of calibration-set selection, the geographical distance method demonstrates greater efficiency for the plain region, but exhibit limitations in areas characterized by significant topographic changes. Analogue-calibration has been found to be more suitable for the edge of the database and also has been proven superior to other two methods for reconstructions exceed Holocene. Selecting calibration sets based only on climate gradients is inappropriate for independent applications, but may act as a limitation for other methods. This preliminary research can contribute to a more precise projection of potential future climate changes by providing essential data input or validating hindcasts for Earth system models.

中文翻译：

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各种现代花粉气候校准集建立方法对定量气候重建的影响

具有代表性的现代校准数据集是古气候可靠定量重建的重要先决条件。然而，对于校准集的优化过滤却明显缺乏系统的研究。选择四个具有代表性的高分辨率花粉记录，利用地理距离、类比和气候梯度等多种方法重复重建古气候。基于花粉的重建的比较表明，这些不同的方法在不同地理环境和时间尺度下的模型性能和重建精度方面表现出显着差异。一般来说，在校准集选择方面，地理距离法对于平原地区表现出较高的效率，但在地形变化较大的地区表现出局限性。人们发现模拟校准更适合数据库的边缘，并且也被证明优于其他两种超过全新世的重建方法。仅根据气候梯度选择校准集不适合独立应用，但可能会限制其他方法。这项初步研究可以通过提供必要的数据输入或验证地球系统模型的后报，有助于更精确地预测未来潜在的气候变化。