CEDAR: Data-driven Modeling of the Global Equatorial Electrojet Variability

CEDAR:全球赤道电喷射变率的数据驱动建模

基本信息

  • 批准号:
    2231409
  • 负责人:
  • 金额:
    $ 40.73万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-01 至 2026-08-31
  • 项目状态:
    未结题

项目摘要

The Earth's low- and mid-latitude ionosphere hosts a variety of complex phenomena resulting from the coupled dynamics of plasma and neutral species under the influence of Earth’s magnetic field. This region is furthermore exposed to constantly varying conditions of both terrestrial and space weather, giving rise to considerable day-to-day variability that is highly dependent on longitudes. This project will use a comprehensive data-driven modeling approach to close the gap in our understanding of the origins of the observed longitudinal and day-to-day variability of daytime large-scale low- to mid-latitude electrodynamics phenomena with a focus on equatorial electrojet (EEJ). The outcome of this project will likely help us to better characterize the plasma structure in the near-Earth space environment, which is key to the forecasting of plasma irregularity and radio wave scintillation that affect communication, navigation, and positioning systems. The project will serve to broaden the education and training experiences of one graduate student at CU-Boulder and three undergraduate students recruited through the Boulder Solar Alliance REU program.The development of the data-driven modeling approach will be guided by a four-dimensional ensemble variational formulation, which is a hybrid of the variational and ensemble approach being built for the NCAR Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM). The approach takes advantage of the capabilities of the 3-D Electrodynamo model which can specify ground and low-Earth-orbit (LEO) magnetic perturbations and 3D ionospheric currents driven by wind dynamo and high-latitude ionospheric convection electric fields. Specific science questions addressed include: • What are the causes of the observed day-to-day variability of EEJ?; To what extent is its longitudinal dependence controlled by the geometry and magnitude of geomagnetic fields, and by the atmospheric waves originating from longitudinal asymmetric sources on the Earth's surface?• What is the connection of the EEJ day-to-day variability to the variability of equatorial plasma drifts, equatorial ionization anomaly (EIA), as well as equatorial counter electrojet (CEJ) and solar quiet (Sq) currents? The primary observational data that will be assimilated includes magnetic fields from a network of ground-based magnetometers, LEO magnetic fields measured by Swarm and electron density and plasma drift measurements obtained from COSMIC-2 and ICON missions. Analysis results will be compared and verified against independent observations of plasma drifts, plasma densities and neutral winds from ground-based observational networks, including incoherent and coherent scatter radars, ionosondes, Fabry-Perot interferometers, and Global Navigation Satellite System receivers as well as neutral winds from ICON.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.
地球的低和中纬度电离层在地球磁场的影响下,由等离子体和中性物种的耦合动力学产生了各种复杂现象。该地区进一步暴露于陆地和太空天气的不断变化的条件,从而高度取决于纵向,从而导致相当大的日常变异性。该项目将使用一种全面的数据驱动建模方法来缩小我们对观察到的纵向和日常变化的起源的差距,这些纵向和日常变化的差异是大规模的低度电子现象,重点是备列式电子夹克(EEJ)。该项目的结果可能会帮助我们更好地表征近地太空环境中的等离子体结构,这是对影响通信,导航和定位系统的血浆不规则性和无线电波闪烁的预测的关键。项目将有助于扩大Cu-Boulder一名研究生的教育和培训经验以及通过Boulder太阳能联盟REU计划招募的三名本科生。数据驱动的建模方法的开发将以四维整体变化公式为指导,这是构建的循环型和循环的循环模型,用于各种循环系统,用于各种循环系统。 (tiegcm)。该方法利用了3-D Electrodynamo模型的功能,该模型可以指定地面和低地面 - 轨道(LEO)磁扰动以及由风力发电机和高纬度电离层连接电场驱动的3D电离层电流。解决的具体科学问题包括:•EEJ观察到的日常变异性的原因是什么?它的纵向依赖性在多大程度上由地磁场的几何形状和幅度控制,以及来自地球表面上纵向不对称来源的大气波,•EEJ日常日常变化与等价等级的差异,等值的求和式求和式Anome(eeje)以及等值的变化(EEJ)的连接是什么安静(平方)电流?将被吸收的主要观察数据包括来自地面磁力计网络的磁场,通过群体和电子密度和等离子钻测量的LEO磁场,从宇宙-2和图标任务中获得的磁场。将比较和验证分析结果,并与对地面观察网络的血浆钻,血浆密度和中性风的独立观察结果进行比较和验证基金会的智力优点和更广泛的影响评论标准。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

暂无数据

数据更新时间:2024-06-01

Tomoko Matsuo其他文献

Modeling impact of FORMOSAT‐7/COSMIC‐2 mission on ionospheric space weather monitoring
模拟 FORMOSAT-7/COSMIC-2 任务对电离层空间天气监测的影响
Annual and semiannual variations of thermospheric density: Observations and simulations
热层密度的年度和半年度变化:观测和模拟
Detection of Methicillin-resistant Staphylococcus aureus from Patients and Hospital Personnel in a Neurosurgery Ward
神经外科病房患者及医护人员耐甲氧西林金黄色葡萄球菌的检测
  • DOI:
  • 发表时间:
    1994
    1994
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Tomoko Matsuo;Keiko Oshima;Eiko Shigetomi;Michiyo Nojima;Noriyuki Murakami;K. Kono
    Tomoko Matsuo;Keiko Oshima;Eiko Shigetomi;Michiyo Nojima;Noriyuki Murakami;K. Kono
  • 通讯作者:
    K. Kono
    K. Kono
共 3 条
  • 1
前往

Tomoko Matsuo的其他基金

CAREER: Predictability of the Whole Atmosphere from Ground to Geospace
职业:从地面到地球空间的整个大气的可预测性
  • 批准号:
    1848544
    1848544
  • 财政年份:
    2019
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Continuing Grant
    Continuing Grant
EarthCube Data Capabilities: Collaborative Proposal: Assimilative Mapping of Geospace Observations
EarthCube 数据能力:协作提案:地理空间观测同化制图
  • 批准号:
    1928403
    1928403
  • 财政年份:
    2019
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Standard Grant
    Standard Grant
Collaborative Research: Multi-Scale Modeling of Non-Gaussian Random Fields
合作研究:非高斯随机场的多尺度建模
  • 批准号:
    1811279
    1811279
  • 财政年份:
    2018
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Standard Grant
    Standard Grant
Collaborative Research: CEDAR--Assimilative Analysis of Low- and Mid-latitude Ionospheric Electrodynamics
合作研究:CEDAR--低纬度和中纬度电离层电动力学同化分析
  • 批准号:
    1651469
    1651469
  • 财政年份:
    2017
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Continuing Grant
    Continuing Grant
Assimilative Mapping of Interhemispheric Polar Ionospheric Electrodynamics
半球间极地电离层电动力学同化制图
  • 批准号:
    1443703
    1443703
  • 财政年份:
    2015
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Continuing Grant
    Continuing Grant
EarthCube IA: Collaborative Proposal: Integrated GeoScience Observatory
EarthCube IA:协作提案:综合地球科学观测站
  • 批准号:
    1541010
    1541010
  • 财政年份:
    2015
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Standard Grant
    Standard Grant
NSWP: Next Generation AMIE: Assimilative Mapping of Space-based and Extremely Localized Observations of Ionospheric Electrodynamics
NSWP:下一代 AMIE:电离层电动力学天基和极局域观测的同化制图
  • 批准号:
    1025089
    1025089
  • 财政年份:
    2010
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Continuing Grant
    Continuing Grant

相似国自然基金

数据驱动的持续集成测试加速技术研究
  • 批准号:
    62372005
  • 批准年份:
    2023
  • 资助金额:
    50 万元
  • 项目类别:
    面上项目
机理模型与数据混合驱动的空间遥操作学习控制方法研究
  • 批准号:
    62373305
  • 批准年份:
    2023
  • 资助金额:
    50 万元
  • 项目类别:
    面上项目
时序数据驱动的预期因果推断经济网络动力学感知重构方法研究
  • 批准号:
    72371229
  • 批准年份:
    2023
  • 资助金额:
    39 万元
  • 项目类别:
    面上项目
数据与模型耦合驱动的自供能传感系统动力学理论与应用研究
  • 批准号:
    12302022
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
基于数据驱动策略的多元岩盐型陶瓷相图预测和微波介电性能优化设计
  • 批准号:
    52302135
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

Facilitating circular construction practices in the UK: A data driven online marketplace for waste building materials
促进英国的循环建筑实践:数据驱动的废弃建筑材料在线市场
  • 批准号:
    10113920
    10113920
  • 财政年份:
    2024
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    SME Support
    SME Support
N2Vision+: A robot-enabled, data-driven machine vision tool for nitrogen diagnosis of arable soils
N2Vision:一种由机器人驱动、数据驱动的机器视觉工具,用于耕地土壤的氮诊断
  • 批准号:
    10091423
    10091423
  • 财政年份:
    2024
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Collaborative R&D
    Collaborative R&D
Data Driven Discovery of New Catalysts for Asymmetric Synthesis
数据驱动的不对称合成新催化剂的发现
  • 批准号:
    DP240100102
    DP240100102
  • 财政年份:
    2024
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Discovery Projects
    Discovery Projects
PIDD-MSK: Physics-Informed Data-Driven Musculoskeletal Modelling
PIDD-MSK:物理信息数据驱动的肌肉骨骼建模
  • 批准号:
    EP/Y027930/1
    EP/Y027930/1
  • 财政年份:
    2024
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Fellowship
    Fellowship
CC* Networking Infrastructure: YinzerNet: A Multi-Site Data and AI Driven Research Network
CC* 网络基础设施:YinzerNet:多站点数据和人工智能驱动的研究网络
  • 批准号:
    2346707
    2346707
  • 财政年份:
    2024
  • 资助金额:
    $ 40.73万
    $ 40.73万
  • 项目类别:
    Standard Grant
    Standard Grant