Very long timescale variations in the palaeomagnetic record and the evolution of the Earth's deep interior

地球的磁场是由地球熔融外核的地球发电机产生的，随着时间的推移变化很大，变得更强或更弱，偶尔会完全逆转其极性。该领域发挥着至关重要的作用，不仅为人类和其他物种提供导航手段，而且还保护地球表面和大气免受太阳风的影响。我们研究这些变化是很重要的，因为如果磁场在未来大幅减弱，人造卫星和发电站将更容易受到这种带电粒子流的破坏，人类患皮肤癌的几率也会增加。对磁场变化的研究还可以告诉我们地球深处的情况，那里是磁场产生的地方，但我们无法直接进入。为此，科学家们利用地磁观测站和卫星获得的数据研究磁场的短期变化。然而，我们也很幸运，许多岩石从它们形成的时候就“锁定”了磁场的方向和/或强度。对这些岩石的“古地磁”测量（加上对它们年龄的估计）使我们能够研究比卫星或天文台数据更长的时期内的磁场变化：数千年、数百万年，甚至数十亿年。该项目的主要研究者最近领导了一项研究，利用古地磁数据研究了大约25亿年前地球磁场的内在变化，并得出结论，平均而言，它与最近的磁场有很大的不同。具体来说，在低纬度地区观察到的磁场方向变化似乎相对于最近的时间有所减少，这可能表明磁场处于更稳定的状态，在这种状态下，它的极性逆转的频率较低。拟议的项目旨在找出它何时、如何以及为什么从一种状态转变为另一种状态。我们将通过对年龄小于25亿年的岩石的古地磁数据（包括方向和强度）进行新的分析，来限制这种转变的时间和性质。我们还将使用从地球发电机数学模型中获取的人工数据，试图理解这些变化发生的原因。最后，在一个相关的博士项目中，我们将对南非近35亿年前的岩石进行古地磁研究，以进一步扩展我们对地球磁场行为的了解。了解地球磁场在数十亿年间是如何变化的，有可能告诉我们很多关于地球深层内部演变的信息。在很长的时间尺度上，可能影响地球动力的变化包括底层固体内核的生长和上覆地幔的对流。最近的研究使用数值模型来试图了解这些变化是如何影响地球动力学的。我们建议将我们从古地磁记录中得到的观测结果与这些模型的结果联系起来，以便我们能够以最现实的方式解释它们。

The Earth's magnetic field is produced by the geodynamo in the molten outer core of the planet and varies dramatically in time, becoming stronger and weaker and occasionally reversing its polarity altogether. The field plays a crucial role, not only in providing a means of navigation for humans and other species, but also in protecting the Earth's surface and atmosphere from the solar wind. It is important that we study these variations because if the magnetic field were to weaken substantially in the future, artificial satellites and power stations would be more prone to being damaged by this stream of charged particles, and rates of skin cancer among humans could also increase. The study of variations of the magnetic field can also tell us about the deep interior of the planet, where the field is generated, but which we are not able to access directly. Scientists study short-term variations of the magnetic field for this purpose using data obtained by magnetic observatories and satellites. However, we are also fortunate that many rocks 'lock in' the direction and / or strength of the magnetic field from the time they form. 'Palaeomagnetic' measurements from these rocks (together with estimates of their age) allow us to study the variations of the field over much longer periods than do satellite or observatory data: thousands, millions, or even billions of years. A recent study led by the principle investigator of the proposed project used palaeomagnetic data to study the intrinsic variation of the Earth's magnetic field around two and a half billion years ago and concluded that it was significantly different, on average, from that of the more recent field. Specifically, the directional variability of the field as viewed at low latitudes appears to have been reduced relative to more recent times, possibly indicating that the field was in a more stable state in which it reversed its polarity less often. The proposed project aims to find out when, how, and why it changed from this one state to the other. We will constrain the timing and nature of the transition by undertaking new analyses of palaeomagnetic data (both directional and intensity) from rocks which are younger than 2.5 billion years. We will also use artificial data taken from mathematical models of the geodynamo to try and understand why these changes occurred. Finally, in a related PhD project, we will undertake a palaeomagnetic study of rocks from South Africa which are nearly 3.5 billion years old to extend our knowledge of the behaviour of the Earth's magnetic field back even further. Knowledge of how the Earth's magnetic field has varied over billions of years has the potential to tell us a great deal about the evolution of the planet's deep interior. Changes that might have affected the geodynamo over these very long timescales include the growth of the underlying solid inner core and the convection of the overlying mantle. Recent studies have used numerical models to try and understand how these changes might have affected the geodynamo. We propose to tie in the observations we make from the palaeomagnetic record with the results of these models so that we can interpret them in the most realistic way.