Data derived continuous time model for the Dst dynamics

Geophysical Research Letters

Volumn 33, Issue 4, 2006, Pages

  Zhu, D ^a   Billings, S A ^a   Balikhin, M ^a   Wing, S ^b   Coca, D ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b JOHNS HOPKINS UNIVERSITY APPLIED PHYSICS LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC ELECTRICITY; MAGNETOSPHERE; MATHEMATICAL MODELS; STORMS; TRANSFER FUNCTIONS; WEATHER FORECASTING;

GEOMAGNETIC STORMS; MAGNETOSPHERIC DYNAMICS; SOLAR WIND;

GEOMAGNETISM;

FORECASTING METHOD; GEOMAGNETIC STORM;

EID: 33645646709     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2005GL025022     Document Type: Article

References (17)

1. Balikhin, M. A., O. M. Boaghe, S. A. Billings, and H. S. K. Alleyne (2001), Terrestrial magnetosphere as a nonlinear resonator, Geophys. Res. Lett., 28, 1123-1126.
2. Billings, S. A., and K. M. Tsang (1989), Spectral analysis for nonlinear systems, part I: Parametric non-linear spectral analysis, Mech. Syst. Signal Proc., 3, 319-339.
3. Billings, S. A., and Q. M. Zhu (1989), Nonlinear model validation using correlation tests, Int. Control, J., 62, 749-766.
4. Boaghe, O., M. Balikhin, S. A. Billings, and H. Alleyne (2001), Identification of nonlinear processes in the magnetospheric dynamics and forecasting of Dst index, J. Geophys. Res., 106, 30,047-30,066.
5. Burton, R. K., R. L. McPherron, and C. T. Russell (1975), An empirical relationship between interplanetary conditions and Dst, J. Geophys. Res., 80, 4204-4214.
6. Chen, S., and S. A. Billings (1989), Representation of nonlinear systems: The NARMAX model, Int. Control. J., 49, 1013-1032.
7. Chen, S., S. A. Billings, and W. Luo (1989), Orthogonal least-squares methods and their application to non-linear system-identification, Int. Control, J., 50, 1873-1896.
8. Dasso, S., D. Gmez, and C. H. Mandrini (2002), Ring current decay rates of magnetic storms: A statistical study from 1957 to 1998, J. Geophys. Res., 107(A5), 1059, doi:10.1029/2000JA000430.
9. Johnson, J. R., and S. Wing (2005), A solar cycle dependence of nonlinearity in magnetospheric activity, J. Geophys. Res., 110, A04211, doi:10.1029/2004JA010638.
10. Klimas, A. J., D. Vassiliadis, D. N. Baker, and D. A. Roberts (1996), The organized nonlinear dynamics of the magnetosphere, J. Geophys. Res., 101, 13,089-13,114.
11. Li, L. M., and S. A. Billings (2001), Continuous time non-linear system identification in the frequency domain, Int. J. Control., 74, 1052-1061.
12. O'Brien, T. P., and R. L. McPherron (2000), An empirical phase space analysis of ring current dynamics: Solar wind control of injection and decay, J. Geophys. Res., 105, 7707-7720.
13. Petyon Jones, J. C., and S. A. Billings (1989), Recursive algorithm for computing the frequency response of a class of non-linear difference equation models, Int. J. Control., 50, 1925-1940.
14. Wang, C. B., J. K. Chao, and C.-H. Lin (2003), Influence of the solar wind dynamic pressure on the decay and injection of the ring current, J. Geophys. Res., 108(A9), 1341, doi:10.1029/2003JA009851.
15. Wing, S., J. R. Johnson, J. Jen, C.-I. Meng, D. G. Sibeck, K. Bechtold, J. Freeman, K. Costello, M. Balikhin, and K. Takahashi (2005), Kp forecast models, J. Geophys. Res., 110, A04203, doi:10.1029/2004JA010500.
16. Wu, J. G., and H. Lundstedt (1997a), Geomagnetic storm predictions from solar wind data with the use of dynamic neural networks, J. Geophys. Res., 102, 14,255-14,268.
17. Wu, J. G., and H. Lundstedt (1997b), Neural network modeling of solar wind-magnetosphere interaction, J. Geophys. Res., 102, 14,457-14,466.