SHINE: Prediction of Solar Activity Using Non-linear Dynamo Models and Data Assimilation Approach

这个为期3年的SIRE项目旨在开发数据同化技术，用于在太阳周期尺度上对太阳活动进行基于物理的预测。该项目有望提高我们预测太阳周期的建模能力，并促进我们对太阳能发电机和太阳周期性质的了解。应用于复杂发电机模型的数据同化技术将使广大太阳物理学界受益。该项目的科学成果将对日光层、地球上层大气以及可能的长期气候研究具有重要意义，并将有益于当前和未来的空间飞行任务和社会。这项为期3年的SISH项目的研究计划包括以下任务：(I)研究动力系统公式中各种数据同化方法和各种简化发电机模式的模型预测对观测数据中不确定性的敏感性；(Ii)开发估计模型参数、系统状态及其不确定性的程序；通过将它们应用于模拟数据和以前的太阳周期观测来验证和检验数据同化程序；(Iii)利用当前的观测数据，计算第25周太阳黑子数和极向和环向磁场总分量的预测，并提供不确定性和可信区间；以及(4)利用来自太阳动力学观测站和地面天气网络(如GONG和SOLIS)的2D发电机模式、天气磁图和经向流测量，为太阳活动的长期天气预报制定一个数据同化程序。该项目与NSF的SIRE计划直接相关，因为它将提供有关全球太阳活动的重要知识，这是太阳、日球层和行星际环境中高能扰动的主要来源。这些知识对于准确模拟和预测从太阳表面到地球乃至更远的空间天气状况至关重要。该项目的研究和EPO议程支持AGS部门在发现、学习、多样性和跨学科研究方面的战略目标。

This 3-year SHINE project is aimed at developing data assimilation techniques for physics-based predictions of the solar activity on the scale of the solar cycle. The project is expected to improve our modeling capabilities to predict the solar cycle, and to advance our knowledge about the solar dynamo and the nature of the solar cycle. The data assimilation techniques applied to the sophisticated dynamo models would benefit the broad solar physics community. The scientific outcome of this project would be important for the studies in the heliosphere, the Earth's upper atmosphere, and possibly climate in the long-term, and it would be beneficial for current and future space missions and society. The research plan of this 3-year SHINE project includes the following tasks: (i) investigate the sensitivity of model predictions to uncertainties in observational data for various data assimilation methods and various reduced dynamo models in a dynamical system formulation; (ii) develop procedures to estimate the model parameters, system state, and their uncertainties; verify and test data assimilation procedures by applying them to simulated data and previous solar cycle observations; (iii) using current observational data, calculate predictions of the sunspot number and total poloidal and toroidal magnetic field components for Cycle 25, and provide uncertainties and confidence intervals; and (iv) develop a data assimilation procedure for long-term synoptic forecasts of solar activity by using 2D dynamo models, synoptic magnetograms, and meridional flow measurements from the Solar Dynamics Observatory and ground-based synoptic networks such as GONG and SOLIS. The project is directly relevant to the NSF's SHINE program, because it will provide important knowledge about the global solar activity, which is the major source of high-energy disturbances in the solar, heliospheric, and interplanetary environment. Such knowledge is critical for accurate modeling and prediction of space weather conditions from the solar surface to the Earth and beyond. The research and EPO agenda of this project supports the Strategic Goals of the AGS Division in discovery, learning, diversity, and interdisciplinary research.