论文标题
HUXT-用Python编写的开源，计算有效的降低物理太阳风模型
HUXt -- An open source, computationally efficient reduced-physics solar wind model, written in Python
论文作者
论文摘要
Huxt是用Python编写的太阳风的开源数值模型。它基于1D Inviscid汉堡方程的解决方案。这种降低的物理方法产生了太阳风流模拟，这些模拟在一小部分计算费用的一小部分中密切模仿了由3-D磁水动力太阳风模型产生的流动。虽然不打算替代3-D MHD，但HUXT的简单性和计算效率提供了几种关键优势，可以实现实验和使用否则将是成本较高的技术。例如，大型合奏可以通过适度的计算资源轻松运行，这对于探索和量化太空天气预测的不确定性以及某些数据同化方法的应用很有用。 我们介绍了最新版本的Huxt，v4.0，并讨论了我们为模型的未来发展和应用的计划。 v4.0中的三个关键发展是：对模型求解器的重组，以实现完全依赖时间的边界条件，以便可以用任何直升机监测器机器人的原位观察来初始化Huxt；通过Huxt Flow解决方案追踪条纹线的新功能，可用于跟踪诸如Heliosperric Current板之类的特征；引入小型测试套件，以便我们可以更好地确保HUXT模拟对未来版本的所有用户的可靠性和可重复性。本文讨论了其他更小的发展。 讨论了HUXT的未来应用，包括用于吸收遥感和原位等离子体测量的开发数据同化方案。作为英国政府游泳计划的一部分，我们讨论了将HUXT转变为英国Met Office太空天气中心的运营模型的进展。
HUXt is an open source numerical model of the solar wind written in Python. It is based on the solution of the 1D inviscid Burger's equation. This reduced-physics approach produces solar wind flow simulations that closely emulate the flow produced by 3-D magnetohydrodynamic solar wind models at a small fraction of the computational expense. While not intended as a replacement for 3-D MHD, the simplicity and computational efficiency of HUXt offers several key advantages that enable experiments and the use of techniques that would otherwise be cost prohibitive. For example, large ensembles can easily be run with modest computing resources, which are useful for exploring and quantifying the uncertainty in space weather predictions, as well as for the application of some data assimilation methods. We present the developments in the latest version of HUXt, v4.0, and discuss our plans for future developments and applications of the model. The three key developments in v4.0 are: a restructuring of the models solver to enable fully time-dependent boundary conditions, such that HUXt can in principle be initialised with in-situ observations from any of the fleet of heliospheric monitors; new functionality to trace streaklines through the HUXt flow solutions, which can be used to track features such as the Heliospheric Current Sheet; introduction of a small test-suite so that we can better ensure the reliability and reproducibility of HUXt simulations for all users across future versions. Other more minor developments are discussed in the article. Future applications of HUXt are discussed, including the development data assimilation schemes for assimilation of both remote sensing and in-situ plasma measures. We discuss the progress of transitioning HUXt into an operational model at the UK's Met Office Space Weather Operations Center as part of the UK governments SWIMMR programme.
