CEDAR: Examining the vertical structures of ionosphere-atmosphere coupling using decadal observations and ionospheric models

CEDAR:使用十年观测和电离层模型检查电离层-大气耦合的垂直结构

基本信息

  • 批准号:
    2230265
  • 负责人:
  • 金额:
    $ 40.61万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-11-01 至 2025-10-31
  • 项目状态:
    未结题

项目摘要

The ionosphere protects life on Earth by shielding cosmic rays, energetic particles, X rays, and extreme UV from the Sun. The ionosphere also enables communication by reflecting radio high-frequency transmissions. However, disturbances due to natural variabilities on vastly different time scales, such as the solar cycles and the solar flares from above, or the tidal waves and the anthropogenic CO2 effects from below, may disrupt the stability of the ionosphere, and interfere with civilian activities, such as navigation, emergency services, precision farming, and artificial satellite systems. Thus, an accurate space weather prediction must be able to predict the impacts of the natural variabilities. This project studies the ionospheric variabilities in ground-based and satellite observations and uses state-of-the-art models to better understand the impacts of the solar electromagnetic changes and the climate forcings on the predictability of the ionospheric variabilities. An undergraduate research assistant will be hired to perform some of the data analyses using machine-learning tools. Annual field trips to a local national lab facility in Los Angeles for undergraduates will be taken to promote aeronomy sciences among under-represented groups in Southern California.The goal of this investigation is to advance our understanding of the influence of solar and lower atmospheric disturbances on the global ionosphere, with particular focus on interannual variabilities related to the solar cycles, the quasi-biennial oscillation (QBO), the El Niño-Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO). The team will study vertical structures of these variabilities using International Reference Ionosphere (IRI) reanalysis data and satellite observations from the last two decades, including NASA's GRACE, NSF-sponsored COSMIC/FORMOSAT-3 and COSMIC-2/FORMOSAT-7, and German Aerospace Center's CHAMP satellite instruments. They will derive the vertical structures of electron density related to the solar cycles, QBO, ENSO, and PDO using IRI reanalysis and satellite data and compare these observations with NCAR's TIME-GCM and WACCM-X standard simulations. The observed interannual variabilities will be diagnosed using tidal wave fluxes and machine-learning tools. The interannual variabilities in ionospheric electron density will be simulated using customized TIME-GCM and WACCM-X models to elucidate the chemo-dynamical connections of the ionosphere with solar electromagnetic changes and climate forcing. Thorough knowledge of the interannual impacts on the chemical and dynamical components can help to improve the space weather forecasts on monthly to decadal timescales.This project is co-funded through a collaboration between the Directorate for Geosciences and Office of Advanced Cyberinfrastructure to support AI/ML and open science activities in the geosciences.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.
电离层通过屏蔽来自太阳的宇宙射线、高能粒子、X射线和极端紫外线来保护地球上的生命。电离层还通过反射无线电高频传输来实现通信。然而,由于不同时间尺度上的自然变化而产生的干扰,例如来自上方的太阳周期和太阳耀斑,或来自下方的潮汐波和人为CO2效应,可能会破坏电离层的稳定性,并干扰民用活动,例如导航,紧急服务,精密农业和人造卫星系统。因此,准确的空间天气预报必须能够预测自然变率的影响。该项目研究地面和卫星观测中的电离层变异性,并利用最新模型更好地了解太阳电磁变化和气候强迫对电离层变异性可预测性的影响。 将聘请一名本科生研究助理使用机器学习工具进行一些数据分析。每年到洛杉矶的一个地方国家实验室进行实地考察,为本科生在南加州代表性不足的群体中推广高层大气科学。这项调查的目标是促进我们对太阳和低层大气扰动对全球电离层影响的理解,特别关注与太阳周期有关的年际变化,准两年振荡(QBO),厄尔尼诺-南方涛动(ENSO)和太平洋十年涛动(PDO)。该团队将利用国际参考电离层(IRI)再分析数据和过去20年的卫星观测,包括NASA的GRACE,NSF赞助的COSMIC/FORMOSAT-3和COSMIC-2/FORMOSAT-7,以及德国航空航天中心的CHAMP卫星仪器,研究这些变化的垂直结构。他们将使用IRI再分析和卫星数据导出与太阳周期,QBO,ENSO和PDO相关的电子密度垂直结构,并将这些观测结果与NCAR的TIME-GCM和WACCM-X标准模拟进行比较。观测到的年际变化将使用潮汐波通量和机器学习工具进行诊断。 将使用定制的TIME-GCM和WACCM-X模式模拟电离层电子密度的年际变化,以阐明电离层与太阳电磁变化和气候强迫的化学动力学联系。深入了解化学和动力学成分的年际影响有助于改进月至十年时间尺度的空间天气预报。地球科学中的ML和开放科学活动。该奖项反映了NSF的法定使命,并通过使用基金会的学术价值和更广泛的影响审查标准。

项目成果

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King-Fai Li其他文献

Characterizing fire and fire atmospheric states from space using collocated hyperspectral infrared sounding and narrow-band imagery
  • DOI:
    10.1016/j.rse.2024.114318
  • 发表时间:
    2024-10-01
  • 期刊:
  • 影响因子:
  • 作者:
    Xuyang Zhou;Qing Yue;King-Fai Li;Evan Fishbein;Xiuhong Chen;Lin Tan;Sally Newman;Eric Fetzer;Yuk L. Yung
  • 通讯作者:
    Yuk L. Yung

King-Fai Li的其他文献

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