NSWP: Data-based Forecasting of the Geomagnetic Field with High Resolution in Space

磁场是控制磁层结构及其风暴-时间动力学的基本参数。实现及时、准确、可靠的预报是国家空间天气计划的主要目标之一。这对于发生磁暴和辐射带扰动的内部磁层尤其重要，而且目前第一原理模型的能力在那里是最有限的。特别是，磁场的动力学是控制辐射带径向输运和加速的关键因素。最近开发的一种基于可扩展的赤道电流场模型的技术使用了大量航天器数据，极大地提高了磁层磁场经验图像的空间分辨率。由于空间高分辨率所需的数据积累可能太长，并掩盖了重要的动力学效应，因此设计了一种新的非线性数据入库技术，其中通过将模型与数据的局部子集进行拟合来描述磁层每种状态的空间结构。它既包括针对给定状态获得的实际数据，也包括来自在全局参数、太阳风电场、地磁活动指数Sym-H及其时间导数的空间中与当前状态相邻的其他时间间隔(例如，其他磁暴的类似阶段)的数据。利用该模型得到的磁暴结构和动力学的初步结果与现场的地球同步观测数据、航天器图像观测数据以及从Iridium星座数据推断的场向电流图像相一致，表明该技术为从过去的事件中提取关于风暴时间电流和磁场的重要新信息提供了一种强有力的新方法。该项目的目标是通过使用星际介质数据作为唯一的模型输入，将目前的高分辨率模型转化为成熟的预测工具。目前模型通过Sym-H指数提供的关于磁层状态的缺失信息，将通过预测的Sym-H和更详细地描述太阳风和国际货币基金组织参数及其时间历史，在其预测版本中提供。该项目将分三步完成。首先，已从现有全球预测模型获得的预测Sym-H或DST指数将用作实际Sym-H指数的替代品。第二，将制定一个新的数据拟合程序，在该程序中，只使用太阳风和基金组织的数据及其时间历史。第三，新工具将使用现场数据和已有的基于全范围风暴的实际Sym-H指数的高分辨率模型进行验证和优化。这项拟议的研究使用了迄今为止为经验建模研究汇编的最大的现场空间磁场数据和行星际介质数据的集合数据库，这些数据基于GOES、IMP 8、Polar、GeoTail、星系团、ACE和Wind航天器11年的观测。一旦可用，来自新的THEMIS任务的数据也将被添加到数据集。这项研究的最终成果将是一套空间天气预报代码，其中规定了磁层磁场，其空间分辨率为几个地球半径，时间分辨率最高可达亚暴时间尺度。为了提供快速预测，新代码将被并行化，并在本地集群和超级计算机上进行测试。

The magnetic field is a fundamental parameter that governs the structure of the magnetosphere and its storm-time dynamics. Achieving its timely, accurate, and reliable forecasting is one of principal goals of the National Space Weather Program. It is especially important for the inner magnetosphere, where magnetic storms and radiation belt disturbances occur, and where the capabilities of the present-day first-principle models are most limited. In particular, the dynamics of the magnetic field is a key factor controlling the radial transport and acceleration of the radiation belts. A recently developed technique based on an extensible model for the field of equatorial currents that uses large sets of spacecraft data has been shown to dramatically improve the spatial resolution of the empirical picture of the magnetospheric magnetic field. Since the data accumulation, necessary for high resolution in space, may be too long and smear out important dynamical effects, a new nonlinear data-binning technique has been devised, where the spatial structure of each state of the magnetosphere is described by fitting the model to a local subset of data. It includes both the actual data obtained for the given state and data from other time intervals (e.g., similar phases of other magnetic storms), neighboring the present state in the space of global parameters, solar wind electric field, geomagnetic activity index Sym-H, and its time derivative. Initial results for magnetic storm structure and dynamics made with the model are consistent with in situ geosynchronous data, IMAGE spacecraft observations and the picture of field-aligned currents inferred from the Iridium constellation data, indicating that the technique offers a powerful new way to extract important new information on the storm-time currents and magnetic field from the past events. The goal of the project is to transform the present high-resolution model into a fully-fledged forecasting tool by using the interplanetary medium data as the only model input. Missing information on the state of the magnetosphere, available in the current model through the Sym-H index, will be provided in its forecasting version through a predicted Sym-H and through a more detailed description of the solar wind and IMF parameters and their time histories. The project will be done in three steps. First, the predicted Sym-H or Dst indices, already available from existing global forecasting models, will be used as a proxy of the actual Sym-H index. Second, a new data-fitting procedure will be elaborated, in which only solar wind and IMF data are used together with their time histories. Third, the new tool will be validated and optimized using in situ data and the already available high-resolution model based on the actual Sym-H index for the full range of storms. The proposed study uses the largest assembled database of in-situ space magnetic field data and concurrent interplanetary medium data ever compiled for empirical modeling studies, based on 11 years of GOES, IMP 8, Polar, Geotail, Cluster, ACE, and Wind spacecraft observations. When available, data from the new THEMIS mission will also be added to the data set. The final product of the study will be a set of space weather forecasting codes specifying the magnetospheric magnetic field with the resolution in space of a few Earth radii and the temporal resolution up to substorm time scales. To provide fast predictions the new codes will be parallelized and tested on local clusters and supercomputers.