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Modelling and data-intensive science methods to understand substorm-driven energy deposition into the polar atmosphere

Modelling and data-intensive science methods to understand substorm-driven energy deposition into the polar atmosphere
建模和数据密集型科学方法来了解亚暴驱动的能量沉积到极地大气中
批准号:
2109171
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --

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中文摘要
翻译
空间天气描述了可能对地球产生影响的空间环境条件,严重的空间天气被列为英国政府国家风险登记册中最优先的自然灾害之一。在亚暴周期中,地球磁层的条件不断变化:太阳风和行星场之间相互作用产生的磁通量和能量的积累和爆炸性释放。在亚暴开始时,大部分能量流向极地地区,随着地球无线电辐射的变化而消散到高层大气中(强度和频率变化)以及极光发射的亮度和形态的变化与这种变化的能量沉积有关。从南安普顿的空间环境物理小组在北极高纬度地区操作的极光相机多年的数据中提取相关能量参数的复杂建模,㈡开发新的计算方法,使分析航天器几十年无线电发射观测结果的过程自动化,以选择表征能量沉积的特征,㈢模拟轨道航天器无线电和极光发射能见度的变化,以量化数据集对观测地点的敏感性。
英文摘要
Space Weather describes environmental conditions in space that can have an impact on Earth, and severe Space Weather is listed as one of the highest priority natural hazards in the UK Government's National Risk Register. Conditions in Earth's magnetosphere are constantly changing over the substorm cycle: a build-up and explosive release of magnetic flux and energy from the interaction between the solar wind and the planetary field. At substorm onset, much of this energy makes its way toward the polar regions, dissipating into the upper atmosphere as changes in Earth's radio emissions (intensifications and frequency changes) and changes in the brightness and morphology of auroral emissions are associated with this varying energy deposition.This project will use i) sophisticated modelling to extract relevant energy parameters from years of data from auroral cameras operated by Southampton's Space Environment Physics group in the high Arctic, ii) develop novel computing methods to automate the process of analysing decades of spacecraft observations of radio emissions, to select the features which characterize energy deposition, iii) simulate the changing visibility of radio and auroral emissions from orbiting spacecraft, to quantify the sensitivity of the datasets to the observation location.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
  • 批准号:
    72101261
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    孙韬
  • 依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: