Smarter Ensembles for solar wind forecasts

用于太阳风预报的智能集成系统

• 批准号: 2890054
• 金额: --
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2890054
• 关键词: Smarter; Ensembles; solar; wind; forecasts

The solar wind is a continuous outflow of charged particles and magnetic field from the Sun's upper atmosphere. Variability in the solar wind conditions leads to space weather, which can adversely affect technological infrastructures, such as power grids and telecommunications networks, as well as the health of humans in space and on high-altitude flights.Space-weather forecasting requires accurate prediction of the solar wind conditions in near-Earth space. The Met Office uses numerical solar wind models for this purpose. In order to assess forecast uncertainty, an "ensemble" of many model runs with slightly different initial conditions is used. This project will attempt to answer three important research questions: 1. How well do these ensembles capture forecast uncertainty?2. How can we better define the starting ensembles?3. What are the primary solar wind sources of forecast uncertainty?This will be achieved through comparison of the Met Office forecast model output with of data from NASA and ESA spacecraft, and through use of Reading's computationally efficient solar wind model.Training opportunities:The student will be given the opportunity to attend relevant summer schools, both in the UK and the US. The student will also visit the UK Met Office to work with their solar wind forecasting system.

太阳风是带电粒子和磁场从太阳上层大气持续流出。太阳风条件的多变性导致空间天气，而空间天气可能对电网和电信网络等技术基础设施以及空间和高空飞行人员的健康产生不利影响，空间天气预报需要准确预测近地空间的太阳风条件。英国气象局为此使用了数值太阳风模型。为了评估预报的不确定性，使用了许多初始条件略有不同的模式运行的“集合”。本研究试图回答三个重要的研究问题：1。这些集合如何捕捉预测的不确定性？2.我们如何更好地定义首发阵容？3.预测不确定性的主要太阳风来源是什么？这将通过比较英国气象局的预测模型输出与美国宇航局和欧空局航天器的数据，并通过使用阅读的计算效率高的太阳风模型来实现。培训机会：学生将有机会参加相关的暑期学校，无论是在英国和美国。学生还将访问英国气象局，与他们的太阳风预报系统。