Gap Filling of Solar Wind Data

Solar wind and interplanetary magnetic field (IMF) data have large gaps before the launch of the WIND spacecraft in 1994. Singular spectrum analysis (SSA) can reconstruct missing data by using an iterative algorithm which infers coherent spatio-temporal  “signal” modes, while  discarding the “noise” (Kondrashov and Ghil, 2006). Here the gaps of the solar driver (such as solar wind parameters and IMF) are filled-in by smooth modes of co-variability with the continuous response (geomagnetic indices such as AE,Kp and Dst), as captured by the multivariate-SSA (Kondrashov et al. 2010). 


SSA gap-filling algorithm has been applied to existing gaps in 1972-Oct. 2013 solar wind data data with hourly resolution: IMF components By, Bz, proton density Np, Alpha/proton ratio Na/Np, solar wind speed Vsw, and dynamic pressure P (see OMNI data set convention). Optimal SSA parameters that are obtained after testing on synthetic gaps. Both reconstruction datasets and results of testing with synthetic gaps are available by following the link below as  zipped archives (6-20Mb). 


This data is also available online in SI of Kondrashov et al. 2014 GRL paper.


Kondrashov, D., R. Denton, Y. Y. Shprits, and H. J. Singer, 2014: Reconstruction of gaps in the past history of solar wind parameters, Geophys. Res. Lett., 41, 2702–270, doi:10.1002/2014GL059741

Kondrashov, D., Y. Shprits, M. Ghil, 2010:  Gap Filling of Solar Wind Data by Singular Spectrum Analysis, Geophys. Res. Lett, 37, L15101, doi:10.1029/2010GL044138.

Kondrashov, D. and M. Ghil, 2006: Spatio-temporal filling of missing points in geophysical data sets, Nonlin. Processes Geophys., 13, 151-159, doi:10.5194/npg-13-151-2006


 Data source: OMNIWEB

Reconstruction for Radiation Belts and Wave Modeling Group

This research has been funded by National Science Foundation Award AGS-1102009