A candidate secular variation model for IGRF-12 based on Swarm data and inverse geodynamo modelling

被引:25
作者
Fournier, Alexandre [1 ]
Aubert, Julien [1 ]
Thebault, Erwan [1 ,2 ]
机构
[1] Univ Paris Diderot, UMR CNRS 7154, Sorbonne Paris Cite, Inst Phys Globe Paris, F-75005 Paris, France
[2] Univ Nantes, Lab Planetol & Geodynam Nantes, UMR CNRS 6112, F-44322 Nantes 3, France
来源
EARTH PLANETS AND SPACE | 2015年 / 67卷
关键词
Magnetic field; Satellite magnetics; Dynamo: theories and simulations; Inverse theory; GEOMAGNETIC REFERENCE FIELD; EARTHS MAGNETIC-FIELD; CORE; CONSTELLATION; ASSIMILATION; GENERATION; DYNAMICS; FLOW;
D O I
10.1186/s40623-015-0245-8
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
In the context of the 12th release of the international geomagnetic reference field (IGRF), we present the methodology we followed to design a candidate secular variation model for years 2015-2020. An initial geomagnetic field model centered around 2014.3 is first constructed, based on Swarm magnetic measurements, for both the main field and its instantaneous secular variation. This initial model is next fed to an inverse geodynamo modelling framework in order to specify, for epoch 2014.3, the initial condition for the integration of a three-dimensional numerical dynamo model. The initialization phase combines the information contained in the initial model with that coming from the numerical dynamo model, in the form of three-dimensional multivariate statistics built from a numerical dynamo run unconstrained by data. We study the performance of this novel approach over two recent 5-year long intervals, 2005-2010 and 2009-2014. For a forecast horizon of 5 years, shorter than the large-scale secular acceleration time scale (similar to 10 years), we find that it is safer to neglect the flow acceleration and to assume that the flow determined by the initialization is steady. This steady flow is used to advance the three-dimensional induction equation forward in time, with the benefit of estimating the effects of magnetic diffusion. The result of this deterministic integration between 2015.0 and 2020.0 yields our candidate average secular variation model for that time frame, which is thus centered on 2017.5.
引用
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页数:17
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