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Reconstruction of late Glacial and Early Holocene near surface temperature anomalies in Europe and their statistical interpretation

机译:欧洲晚冰川和早全新世近地表温度异常的重建及其统计解释

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摘要

This paper presents the results of a variational analysis study based on the recently developed method by Gebhardt et al. to reconstruct paleo temperature fields on the typical scale of climate model output, providing the necessary basis for quantitative comparison of reconstructions and model results. Additionally, an extension of the approach takes into account the full statistics of the analysis error of the variational analysis to study the inherent uncertainties of the proxy data representing the imperfect paleo climate information and their impact on the field reconstruction. The method is applied to reconstruct realizations of monthly mean temperature anomaly fields in Europe for January and July in Europe as averages for several time slices in the Late Glacial and Holocene. Single realizations can differ substantially from the field of expectation values in terms of spatial patterns due to the inherent correlation of the spatial uncertainties of the paleo proxy data. Additionally, the fields of expectation values generally are much smoother than the realizations. This indicates that it is misleading to only consider expectation values. Further, the ensembles of realization are used to calculate robust error measures for area mean values, which is valuable for the quantitative comparison of the results of different time slices.
机译:本文介绍了基于Gebhardt等人最近开发的方法进行的变异分析研究的结果。在典型气候模型产出规模上重建古温度场,为定量比较重建结果和模型结果提供必要的基础。此外,该方法的扩展考虑了变分分析的分析误差的完整统计信息,以研究代表不完善的古气候信息的代理数据的固有不确定性及其对田间重建的影响。该方法用于重构欧洲在1月和7月在欧洲的月平均温度异常场的实现,作为晚冰川和全新世几个时间片的平均值。由于古代理数据的空间不确定性的内在相关性,单个实现在空间模式方面可能与期望值的领域大不相同。此外,期望值的字段通常比实现要平滑得多。这表明仅考虑期望值会产生误导。此外,实现的集成用于计算面积平均值的鲁棒误差度量,这对于不同时间片的结果的定量比较很有用。

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  • 来源
    《Quaternary International》 |2012年第1期|p.233-250|共18页
  • 作者单位

    Meteorological Institute, University of Bonn, Auf dem Huegel 20, D-53121 Bonn, Germany, WetterOnline GmbH, Am Rheindorfer Ufer 2, 53117 Bonn, Germany;

    Meteorological Institute, University of Bonn, Auf dem Huegel 20, D-53121 Bonn, Germany;

    Steinmann Institute of Geology, Mineralogy and Palaeontology, University of Bonn, Nussallee 8, 53115 Bonn, Germany;

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