Space Weather: Dynamics of Regional and Local High-Latitude Geomagnetic Disturbances

该项目将进一步发展一个最初由国家科学基金会早期支助资助的模型，以建立一个关于地面磁场波动的空间天气模型。目前的模型是一个线性动力学模型，根据芬兰磁强计阵列、IMAGE、地磁PC指数和最近的太阳风输入历史进行了训练。这些元素代表了地磁活动和全球磁层的状态，以及通过昼侧磁场重联可获得的能量的量度。该模型产生在纬度55 - 90度的水平（2D）场的估计。场的动态近似为振荡和增长/衰减，并且它们由PC指数和太阳风输入驱动。所提出的模型将被训练以预测完整的3D地面磁场。一个类似的模型将单独开发，以预测磁场的时间导数方面的场波动。时间导数是特别重要的，因为地磁感应电流，这可能会影响电力配电网，是由磁场的突然变化。这些模型将是非线性的，这意味着它们的系数将由地磁活动水平参数化。从线性到非线性动态的过渡将提高预测精度。太阳风和行星际磁场（IMF）的输入对预测精度的影响将被检查。太阳风-磁层耦合过程不仅与纬度有关，还与当地时间有关。模型的每个位置可以由不同的太阳风/IMF输入函数驱动。所提出的模型可以动态地适应不断变化的太阳风条件，但重要的是，它定期校正的正确的地磁条件的当前状态。数据同化将用于接收实时地磁测量结果。由于该模型可以被写为局部场（或其波动）的滤波器，因此它将被扩展为包括卡尔曼滤波器。卡尔曼组件将调整模型的状态，使其快速收敛于测量点的实际条件。地面磁场的动态模型有几个重要的应用。首先，了解地磁响应及其对太阳风输入和磁层结构的依赖性是磁层等离子体物理学中的一个重要问题。该模型可以用来作为一种工具来量化这种复杂的耦合作为行星际条件和磁层状态的函数。此外，该模型的某些方面可用作磁层和电离层等离子体物理学学生培训的一部分。

This project will further develop a model originally funded with earlier NSF support to a space weather model for the fluctuations of ground magnetic field. The current model is a linear dynamical model trained on historic measurements taken by the Finnish magnetometer array, IMAGE, the geomagnetic PC index, and the recent history of the solar wind inputs. These elements represent the state of geomagnetic activity and of the global magnetosphere, and a measure of the energy available through dayside magnetic reconnection. The model produces an estimate of the horizontal (2D) field at latitudes 55-90 degrees. The dynamics of the field are approximated as oscillation and growth/decay and they are driven by the PC index and solar wind inputs. The proposed model will be trained to predict the full 3D ground magnetic field. A similar model will be separately developed to predict the field fluctuations in terms of the time derivatives of the magnetic field. Time derivatives are of particular importance because geomagnetically induced currents, which can effect the electric power distribution grid, are driven by sudden changes in the magnetic field. The models will be nonlinear, meaning that their coefficients will be parameterized by the geomagnetic activity level. The transition from linear to nonlinear dynamics will increase the prediction accuracy. The effects of the solar wind and interplanetary magnetic field (IMF) inputs on prediction accuracy will be examined. The solar wind-magnetosphere coupling process depends on local time as well as on latitude. Each location of the model can be driven by a distinct solar wind/IMF input function. The proposed model can dynamically adapt to changing solar wind conditions, but it is important that it be regularly corrected by the correct present state of geomagnetic conditions. Data assimilation will be used to ingest real-time geomagnetic measurements. Because the model can be written as a filter for the local field (or its fluctuations), it will be extended to include a Kalman filter. The Kalman component will adjust the state of the model so that it rapidly converges on realistic conditions at the points of measurement. A dynamic model for the ground magnetic field has several important applications. First, understanding the geomagnetic response and its dependence on solar wind input and the magnetospheric configuration is an important question in magnetospheric plasma physics. The model can be used as a tool to quantify this complex coupling as a function of interplanetary conditions and the magnetospheric state. In addition, some aspects of the model can be used as part of student training on magnetospheric and ionospheric plasma physics.