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上个千年温度历史数据模型差异的可能原因。

Possible causes of data model discrepancy in the temperature history of the last Millennium.

机构信息

Oeschger Centre for Climate Change Research and Institute of Geography, University of Bern, Bern, Switzerland.

School of Geosciences, University of Edinburgh, Edinburgh, UK.

出版信息

Sci Rep. 2018 May 15;8(1):7572. doi: 10.1038/s41598-018-25862-2.

Abstract

Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role.

摘要

模型模拟和代理重建是量化仪器前气候变化的主要工具。对于一些指标,如北半球平均温度,模型和重建之间存在显著的一致性。对于其他诊断指标,如火山爆发对区域的响应或半球温差,已有报告称数据与模型之间存在实质性分歧。在这里,我们通过比较基于真实古气候代理的 1000 年半球温度重建与基于气候模型的伪代理来评估这些差异的潜在来源。这些伪代理实验(PPE)表明,代理记录中的固有噪声和代理数据的空间分布不均是解释数据-模型差异的关键因素。例如,PPE 可以完全解释重建中半球间相关性较低的原因。噪声和数据采样也部分解释了与模型相比,重建中对外部强迫的响应幅度减小的原因。对于其他指标,如半球间差异,虽然有所减少,但仍存在一些差异。我们的结果表明,提高代理数据质量和空间覆盖范围是提高未来气候重建质量的关键因素,而代理记录的总数和重建方法的作用较小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc1b/5953951/5cd05f2a253c/41598_2018_25862_Fig1_HTML.jpg

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