SWQU: Forecasting Small-Scale Plasma Structures in Earth's Ionosphere-Thermosphere System

SWQU：预测地球电离层-热层系统中的小规模等离子体结构

• 批准号: 2028032
• 负责人: Eric Sutton
• 金额: $ 239.86万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028032&HistoricalAwards=false
• 关键词: SWQU; Forecasting; Small; Scale; Plasma

Space weather caused by structures and irregularities in Earth’s ionosphere can disrupt transmission of Global Navigation Satellite System signals critical for precise positioning, navigation and timing, and can influence propagation of trans-ionospheric radio waves used in land-satellite communication. Despite decades of work, forecasting this space weather phenomenon remains a challenge. This project advances fundamental research underpinning such forecasts by establishing integrated models of ionosphere-thermosphere conditions that lead to ionospheric plasma irregularities. Novel data-assimilation techniques and uncertainty quantification methods are applied to estimate uncertainties in model predictions. Spatial and temporal variations of simulated ionosphere-thermosphere parameters are validated with ground- and satellite-based observations. The project team includes both senior and early-career scientists with expertise in space physics as well as software engineers and a graduate student. Collaborations with the UK, Japan, and Taiwan expand the availability and dissemination of the models and code. The improved models will be adopted into the operational version at NOAA Space Weather Prediction Center. This project directly addresses objectives in the National Space Weather Strategy and Action Plan and the National Strategic Computing Initiative Update.The project improves the coupled whole atmosphere model and ionosphere-plasmasphere electrodynamics model (WAM-IPE) with high resolution capability (10s of km) using the Cornell ionospheric dynamics model. The data assimilation scheme address uncertainty in external forcing especially solar EUV irradiance and high-latitude heating associated with geomagnetic activity, and constrain the large-scale ionosphere-thermosphere dynamics while preserving small-scale perturbations generated by WAM-IPE without requiring unrealistic local adjustments. Highly scalable uncertainty quantification strategies based on low rank approximations are adopted and extended to estimate the model prediction uncertainties in the presence of high-dimensional input uncertainty. Key science questions investigated here include: can the high-resolution global model generate the range of scales driving plasma irregularities at low- and mid-latitudes; which parts of the spectrum of waves and background ionosphere-thermosphere conditions lead to the formation of plasma irregularities; and what are the key drivers controlling model parameters and their uncertainty? This award is made as a part of the joint NSF-NASA pilot program on Next Generation Software for Data-driven Models of Space Weather with Quantified Uncertainties (SWQU). All software developed as a result of this award will be made available by the awardee free of charge for non-commercial use; the software license will permit modification and redistribution of the software free of charge for non-commercial use.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

地球电离层的结构和不规则现象造成的空间天气可能干扰对精确定位、导航和定时至关重要的全球导航卫星系统信号的传输，并可能影响陆地卫星通信中使用的跨电离层无线电波的传播。尽管经过几十年的努力，预测这种空间天气现象仍然是一个挑战。该项目通过建立导致电离层等离子体不规则性的电离层-热层条件的综合模型，推进支持这种预测的基础研究。新的数据同化技术和不确定性量化方法被用来估计模式预测中的不确定性。模拟的电离层-热层参数的空间和时间变化与地面和卫星观测进行了验证。该项目小组包括具有空间物理专业知识的资深和早期职业科学家以及软件工程师和一名研究生。与英国、日本和台湾的合作扩大了模型和代码的可用性和传播。改进后的模式将被NOAA空间天气预报中心的业务版本所采用。该项目直接涉及国家空间气象战略和行动计划以及国家战略计算举措更新中的目标，该项目使用康奈尔电离层动力学模型改进了具有高分辨率能力（10千米）的耦合全大气模型和电离层-等离子体电磁动力学模型。数据同化方案解决了外部强迫的不确定性，特别是与地磁活动有关的太阳极紫外线辐照度和高纬度加热，并限制了大尺度电离层-热层动态，同时保留了WAM-IPE产生的小尺度扰动，而不需要不切实际的局部调整。采用基于低秩近似的高度可扩展的不确定性量化策略，并将其扩展到高维输入不确定性情况下的模型预测不确定性估计。这里研究的关键科学问题包括：高分辨率全球模型能否产生在低纬度和中纬度驱动等离子体不规则性的尺度范围;波的频谱和背景电离层-热层条件的哪些部分导致等离子体不规则性的形成;以及控制模型参数及其不确定性的关键驱动因素是什么？该奖项是NSF-NASA联合试点计划的一部分，该计划旨在开发下一代空间天气数据驱动模型软件（SWQU）。 所有因该奖项而开发的软件将由获奖者免费提供用于非商业用途;软件许可证将允许免费修改和重新分发软件用于非商业用途。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Automatic Spread‐F Detection Using Deep Learning

• DOI: 10.1029/2021rs007419
• 发表时间: 2021-12
• 期刊: Radio Science
• 影响因子: 1.6
• 作者: Christopher Luwanga;T. Fang;A. Chandran;Yu-Ju Lee

Daily Dynamo Electric Fields Derived by Using Equatorial Ionization Anomaly Crests of the Total Electron Content

• DOI: 10.1029/2022sw003073
• 发表时间: 2022-11
• 期刊: Space Weather
• 作者: Ching Cheng;Jann‐Yenq Liu;C. Lin;Yin‐Chen Cheng

Bi-fidelity reduced polynomial chaos expansion for uncertainty quantification

用于不确定性量化的双保真减少多项式混沌展开

• DOI: 10.1007/s00466-021-02096-0
• 发表时间: 2022
• 期刊: Computational Mechanics
• 影响因子: 4.1
• 作者: Newberry, Felix;Hampton, Jerrad;Jansen, Kenneth;Doostan, Alireza
• 通讯作者: Doostan, Alireza