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基于4年“蜂群”卫星观测数据确定的地球磁场综合模型。

A Comprehensive Model of Earth's Magnetic Field Determined From 4 Years of Swarm Satellite Observations.

作者信息

Sabaka Terence J, Tøffner-Clausen Lars, Olsen Nils, Finlay Christopher C

机构信息

Geodesy and Geophysics Laboratory, NASA Goddard Space Flight Center, Greenbelt/MD, U.S.A.

Division of Geomagnetism, DTU Space, Technical University of Denmark, Diplomvej DK-2800 Kongens Lyngby, Denmark.

出版信息

Earth Planets Space. 2018;70(1). doi: 10.1186/s40623-018-0896-3. Epub 2018 Aug 10.

DOI:10.1186/s40623-018-0896-3
PMID:30906198
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6425495/
Abstract

The European Space Agency's three-satellite constellation , launched in November 2013, has provided unprecedented monitoring of Earth's magnetic field via a unique set of gradiometric and multi-satellite measurements from low Earth orbit. In order to exploit these measurements, an advanced "Comprehensive Inversion" (CI) algorithm has been developed to optimally separate the various major magnetic field sources in the near-Earth regime. The CI algorithm is used to determine Level-2 (L2) magnetic field data products that include the core, lithospheric, ionospheric, magnetospheric, and associated induced sources. In addition, it has become apparent that the CI is capable of extracting the magnetic signal associated with the oceanic principal lunar semi-diurnal tidal constituent to such an extent that it has been added to the L2 data product line. This paper presents the parent model of the L2 CI products derived with measurements from the first four years of the mission and from ground observatories, denoted as "CIY4", including the new product describing the magnetic signal of the oceanic tide.

摘要

欧洲航天局的三星卫星星座于2013年11月发射,通过从近地轨道进行的一组独特的梯度测量和多卫星测量,对地球磁场进行了前所未有的监测。为了利用这些测量数据,已经开发了一种先进的“综合反演”(CI)算法,以最佳方式分离近地区域中的各种主要磁场源。CI算法用于确定二级(L2)磁场数据产品,其中包括地核、岩石圈、电离层、磁层以及相关的感应源。此外,很明显CI能够提取与海洋主要月球半日潮汐成分相关的磁信号,以至于该信号已被添加到L2数据产品线中。本文介绍了利用该任务前四年的测量数据和地面观测站数据得出的L2 CI产品的母模型,称为“CIY4”,包括描述海洋潮汐磁信号的新产品。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/3e2cd77c571c/40623_2018_896_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/361a3228ff6c/40623_2018_896_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/2150816698f1/40623_2018_896_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/be7898df3bcc/40623_2018_896_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/bb2855ad211a/40623_2018_896_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/bcf563c19341/40623_2018_896_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/0fdbc807731c/40623_2018_896_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/085673bd5a9e/40623_2018_896_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/2cb843261c19/40623_2018_896_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/1c60fbc2803f/40623_2018_896_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/3e2cd77c571c/40623_2018_896_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/361a3228ff6c/40623_2018_896_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/2150816698f1/40623_2018_896_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/be7898df3bcc/40623_2018_896_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/bb2855ad211a/40623_2018_896_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/bcf563c19341/40623_2018_896_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/0fdbc807731c/40623_2018_896_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/085673bd5a9e/40623_2018_896_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/2cb843261c19/40623_2018_896_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/1c60fbc2803f/40623_2018_896_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c24f/6428233/3e2cd77c571c/40623_2018_896_Fig11_HTML.jpg

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本文引用的文献

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Surv Geophys. 2022;43(1):5-39. doi: 10.1007/s10712-021-09656-2. Epub 2021 Sep 30.
4
Estimating global ocean heat content from tidal magnetic satellite observations.通过潮汐磁卫星观测估算全球海洋热含量。
Sci Rep. 2019 May 27;9(1):7893. doi: 10.1038/s41598-019-44397-8.