古地磁记录中地磁偶极的探测

2023-08-17 19:30:23 来源：今日科学小 中

德国慕尼黑大学Lhuillier, Florian研究组报道了在古地磁记录中探测地磁场的偶极。相关论文于2023年6月12日发表在《美国科学院院刊》杂志上。

为了更好地限制古地磁记录的预测能力，研究人员提出了一种基于分析地磁场强度和倾斜(水平线与磁力线所成的角度)之间的相关性分析的方法。基于统计场模型的结果，研究表明这两个量应该与大范围的类地磁场相关，即使有增强的长期变化、持续的非区域成分和和严重的噪音污染。研究数据显示，着眼于古地磁的记录，这种相关性对于 Brunhes 极性年代并不显著，研究人员将其归因于不充分的时空采样。相比之下，这种相关性在 1到130 Ma 的时间间隔中比较有意义，而在130 Ma 之前，对古强度和古方向都进行严格的过滤时，只存在略微的相关性。

(资料图片仅供参考)

在1到130Ma的时间间隔内，研究人员无法检测到相关性强度的显著变化，因此得出结论：白垩纪正常超时可能与地球发电机的偶极增强无关。当应用严格的过滤器时，在130 Ma 之前获得的强相关性表明，平均来讲，古磁场可能与现今磁场没有如此大的不同。目前，如果长期波动仍然存在，探测前寒武纪期间的潜在地球动力学机制，受到高质量数据的稀疏性的阻碍，这些数据在古强度和古方向上都通过了严格的过滤。

研究人员表示，恢复过去的地磁场强度是理解深部地球动力学和探测地球历史上潜在的地球动力学机制的关键。

附：英文原文

Title: Detecting dipolarity of the geomagnetic field in the paleomagnetic record

Author: Lhuillier, Florian, Shcherbakov, Valeriy P., Sycheva, Natalia K.

Issue&Volume: 2023-6-12

Abstract: Recovering the geomagnetic field strength in the past is key to understanding deep Earth dynamics and detecting potential geodynamo regimes throughout the history of Earth. To better constrain the predictive power of the paleomagnetic record, we propose an approach based on the analysis of the dependency between geomagnetic field strength and inclination (angle made by the horizontal with the field lines). Based on the outcomes of statistical field models, we show that these two quantities should correlate for a wide range of Earth-like magnetic fields, even with enhanced secular variation, persistent nonzonal components, and severe noise contamination. Focusing on the paleomagnetic record, we show that the correlation is not significant for the Brunhes polarity chron, what we ascribe to inadequate spatiotemporal sampling. In contrast, the correlation is significant for the 1 to 130 Ma interval, whereas it only marginally succeeds prior to 130 Ma when strict filters on both paleointensities and paleodirections are applied. As we cannot detect significant variations in the strength of the correlation over the 1 to ng potential geodynamo regimes during the Precambrian is currently impeded by the sparsity of high-quality data passing strict filters in both paleointensities and paleodirections.

DOI: 10.1073/pnas.2220887120

Source: https://www.pnas.org/doi/10.1073/pnas.2220887120

来源：科学网小柯机器人

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