Time Series Analysis of SOLSTICE Measurements

Details Time Series Analysis of SOLSTICE Measurements Time Series Analysis of SOLSTICE Measurements

Dec 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003agufmsh12a1154w&link_type=abstract

American Geophysical Union, Fall Meeting 2003, abstract #SH12A-1154

Physics

1600 Global Change (New Category), 1650 Solar Variability, 7537 Solar And Stellar Variability, 7538 Solar Irradiance

Scientific paper

Solar radiation is the major energy source for the Earth's biosphere and atmospheric and ocean circulations. Variations of solar irradiance have been a major concern of scientists both in solar physics and atmospheric sciences. A number of missions have been carried out to monitor changes in total solar irradiance (TSI) [see Fröhlich and Lean, 1998 for review] and spectral solar irradiance (SSI) [e.g., SOLSTICE on UARS and VIRGO on SOHO]. Observations over a long time period reveal the connection between variations in solar irradiance and surface magnetic fields of the Sun [Lean1997]. This connection provides a guide to scientists in modeling solar irradiances [e.g., Fontenla et al., 1999; Krivova et al., 2003].
Solar spectral observations have now been made over a relatively long time period, allowing statistical analysis. This paper focuses on predictability of solar spectral irradiance using observed SSI from SOLSTICE . Analysis of predictability is based on nonlinear dynamics using an artificial neural network in a reconstructed phase space [Abarbanel et al., 1993]. In the analysis, we first examine the average mutual information of the observed time series and a delayed time series. The time delay that gives local minimum of mutual information is chosen as the time-delay for phase space reconstruction [Fraser and Swinney, 1986]. The embedding dimension of the reconstructed phase space is determined using the false neighbors and false strands method [Kennel and Abarbanel, 2002]. Subsequently, we use a multi-layer feed-forward network with back propagation scheme [e.g., Haykin, 1994] to model the time series. The predictability of solar irradiance as a function of wavelength is considered.
References
Abarbanel, H. D. I., R. Brown, J. J. Sidorowich, and L. Sh. Tsimring, Rev. Mod. Phys. 65, 1331, 1993.
Fraser, A. M. and H. L. Swinney, Phys. Rev. 33A, 1134, 1986.
Fontenla, J., O. R. White, P. Fox, E. H. Avrett and R. L. Kurucz, The Astrophysical Journal, 518, 480-499, 1999.
Fröhlich, C. and J. Lean, IAU Symposium 185: New Eyes to See Inside the Sun and Stars, edited by F. L. Deubner, 82-102, Kluwer Academic Publ., Dordrecht, The Netherland, 1998.
Haykin, S., 696 pp, Macmillan, New York, 1994.
Kennel, M. B. and H. D. I. Abarbanel, Phys. Rev. E 66, 026209, 2002.
Krivova, N. A., S. K. Solanki, M. Fligge, and Y. C. Unruh, 399, L1-L4, 2003.
Lean, J., Annu. Rev. Astron. Astrophys., 35, 33-67, 1997.

Affiliated with

Also associated with

No associations

Rating

Time Series Analysis of SOLSTICE Measurements does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Time Series Analysis of SOLSTICE Measurements, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Time Series Analysis of SOLSTICE Measurements will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1643401