Dynamical Data-based Modeling of the Magnetospheric Magnetic Field

许多关于地球磁层的研究课题都依赖于磁场模型。现有的经验模型是全球性的空间，时间和磁场变化的幅度，他们适合使用一组有限的定制的基础功能，代表每个磁层电流系统的观测。虽然目前的模型已证明对空间科学界非常有用，但它们有一些局限性。特别地，它们不具有期望的空间分辨率，并且它们不考虑变化的时间历史。本项目将把过去使用的经验建模技术与空间数据插值和非线性时间序列分析的现代方法联合收割机结合起来。这将改进地磁场模型，有系统地提高其空间分辨率，并考虑到在磁暴和亚磁暴所涉及的时间尺度上太阳风驱动的变化。首先，该项目将探索主要磁层场源对太阳风密度、速度、冲压压力和行星际磁场变化的反应的时间尺度。响应函数将使用简单的加载-卸载方程相对于太阳风输入进行参数化。第二，将实施有限元技术，其中各个电流系统的领域被扩展成一系列的基函数，考虑到几何约束，施加在一个给定的电流系统通过其特定的边界条件。结合航天器数据库的逐步扩展，这一方法将提高空间分辨率，最大限度地利用从观测中获得的信息，并最大限度地减少关于磁层结构的先验假设。研究的第三条线将探索用局部时间和幅度拟合代替全局时间和幅度拟合的可能性，使用动力系统方法和相空间中数据的局部拟合的现代技术。该技术将基于时间延迟嵌入、最近邻和条件概率的概念。一个重要的技术改进将是现有和新开发代码的并行化，使用超级计算机提供更快的模型更新。拟议的研究将以现有的最大数量的航天器数据为基础，包括大量的行星际和磁层观测数据。该数据集包括50多个主要磁暴的覆盖范围。新一代的经验地磁场模型将能够对磁场进行空间气象预报，并将促进我们对太阳风和磁层之间在与地球空间扰动有关的时间尺度上的耦合的理解和预测。新的地磁场模型和数据库将向其他研究人员开放。

Many research topics concerning the Earth's magnetosphere depend on models of the magnetic field. The existing empirical models are global in space, time, and in the amplitude of field variations, and they are fitted to observations using a limited set of custom-tailored basis functions representing each magnetospheric current system. Although the current models have proven to be very useful to the space science community they have a number of limitations. In particular, they do not have the spatial resolution that would be desired and they do not take into account the time history of the variations. This project will combine the empirical modeling techniques that have been used in the past with modern methods of spatial data interpolation and nonlinear time-series analysis. This will advance the models of the geomagnetic field and make it possible to systematically increase their spatial resolution and to take into account the variable solar wind driving on the timescales involved in magnetic storms and substorms.The research will pursue three complementary lines. First, the project will explore the timescales of the response of the main magnetospheric field sources to solar wind density, speed, ram pressure and the interplanetary magnetic field (IMF) variations. The response functions will be parameterized using simple loading-unloading equations with respect to the solar-wind input. Second, a finite element technique will be implemented, in which the fields of individual current systems are expanded into a series of basis functions, taking into account geometrical constraints, imposed on a given current system via its specific boundary conditions. Combined with a progressive extension of the spacecraft database, this approach will improve the spatial resolution, maximize the information derived from observations, and minimize the number of a priori assumptions on the structure of the magnetosphere. The third line of the research will explore the possibility of replacing the global time and amplitude fitting with the local ones, using the dynamical system approach and modern techniques of the local fitting of data in phase space. This technique will be based on the concepts of time delay embedding, nearest neighbors, and conditional probability. An important technical improvement will be the parallelization of the existing and newly developed codes, providing a much faster update of the model using supercomputers. The proposed study will be based on the largest available amount of spacecraft data, including a significantly extended set of interplanetary and magnetospheric observations. The data set includes coverage of more than 50 major magnetic storms. The new generation of empirical geomagnetic field models, will enable space weather forecasting of the magnetic field and will promote our understanding and prediction of the coupling between the solar wind and the magnetosphere on timescales relevant to geospace disturbances. The new geomagnetic field models and the database will be made openly available to other researchers.