World Library  

Add to Book Shelf
Flag as Inappropriate
Email this Book

Spatio-temporal Filling of Missing Points in Geophysical Data Sets : Volume 13, Issue 2 (24/05/2006)

By Kondrashov, D.

Click here to view

Book Id: WPLBN0004019750
Format Type: PDF Article :
File Size: Pages 9
Reproduction Date: 2015

Title: Spatio-temporal Filling of Missing Points in Geophysical Data Sets : Volume 13, Issue 2 (24/05/2006)  
Author: Kondrashov, D.
Volume: Vol. 13, Issue 2
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Ghil, M., & Kondrashov, D. (2006). Spatio-temporal Filling of Missing Points in Geophysical Data Sets : Volume 13, Issue 2 (24/05/2006). Retrieved from

Description: Department of Atmospheric and Oceanic Sciences and Institute of Geophysics and Planetary Physics, University of California, Los Angeles, USA. The majority of data sets in the geosciences are obtained from observations and measurements of natural systems, rather than in the laboratory. These data sets are often full of gaps, due to to the conditions under which the measurements are made. Missing data give rise to various problems, for example in spectral estimation or in specifying boundary conditions for numerical models. Here we use Singular Spectrum Analysis (SSA) to fill the gaps in several types of data sets. For a univariate record, our procedure uses only temporal correlations in the data to fill in the missing points. For a multivariate record, multi-channel SSA (M-SSA) takes advantage of both spatial and temporal correlations. We iteratively produce estimates of missing data points, which are then used to compute a self-consistent lag-covariance matrix; cross-validation allows us to optimize the window width and number of dominant SSA or M-SSA modes to fill the gaps. The optimal parameters of our procedure depend on the distribution in time (and space) of the missing data, as well as on the variance distribution between oscillatory modes and noise. The algorithm is demonstrated on synthetic examples, as well as on data sets from oceanography, hydrology, atmospheric sciences, and space physics: global sea-surface temperature, flood-water records of the Nile River, the Southern Oscillation Index (SOI), and satellite observations of relativistic electrons.

Spatio-temporal filling of missing points in geophysical data sets

Alvera-Azcárate, A., Barth, A., Rixen, M., and Beckers, J M.: Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: applications to the Adriatic Sea surface temperature, Ocean Modelling, 9, 325-346, 2005. %\bibitem[] Allen, M. R., and L. A. Smith (1996), Monte Carlo SSA: Detecting irregular oscillations in the presence of coloured noise. \textitJ. Clim., \textit9, 3373-3404.; Beckers, J. and Rixen, M.: EOF calculations and data filling from incomplete oceanographic data sets, J. Atmos. Ocean. Technol., 20, 1839-1856, 2003.; Broomhead, D. S. and King, G P.: Extracting qualitative dynamics from experimental data, Physica D, 20, 217-236, 1986.; Colebrook, J M.: Continuous plankton records: zooplankton and environment, North-East Atlantic and North Sea, 1948-1975, Oceanol. Acta, 1, 9-23, 1978. \bibitem [Dettinger (1995)]dett95 Dettinger, M D., Ghil, M., Strong, C M., Weibel, W., and Yiou, P.: Software expedites singular-spectrum analysis of noisy time series, Eos, Trans. American Geophysical Union, v 76(2), p 12, 14, 21, 1995. %\bibitem[] Deser, C., and M. L. Blackmon (1993), Surface climate variations %over the North Atlantic ocean during winter 1900-1989, \textitJ. %Clim., \textit6, 1743-1753.; Foster, G.: Wavelets for period analysis of unevenly sampled time series, Astronom. J., 112, 1709-1729, 1996.; Fraedrich, K.: Estimating the dimensions of weather and climate attractors, J. Atmos. Sci., 43, 419-432, 1986. %\bibitem [] Fraedrich, K., and Ch. Bantzer (1991), A note on fluctuations of the Nile River flood levels \it Theor. Appl. Climatol., \it 44, 167-171. %\bibitem[] Fraedrich, K., J. Jiang, F. W. Gerstengarbe, and P. C. Werner %(1997), Multiscale detection if abrupt climate changes: Application %to River Nile flood levels, \textitInt. J. Climatol., \textit17, 1301-1315.; Ghil, M. and Vautard, R.: Interdecadal oscillations and the warming trend in global temperature time series, Nature, 350, 324-327, 1991.; Ghil, M. and Jiang, N.: Recent forecast skill for the El Ni\~no/Southern Oscillation, Geophys. Res. Lett., 25, 171-174, 1998.; Ghil, M., Allen, R. M., Dettinger, M. D., Ide, K., Kondrashov, D., et al.: Advanced spectral methods for climatic time series, Rev. Geophys. 40(1), 3.1-3.41, doi:10.1029/2000RG000092, 2002.; Johns, C., Nychka, D., Kittel, T., and Daly, C.: Infilling sparse records of spatial fields, J. Amer. Stat. Assoc., 98(464), 796-806, 2003.; Kaplan, A., Kushnir, Y., Cane, M., and Blumenthal, M.: Reduced space optimal analysis for historic data sets: 136 years of Atlantic sea-surface temperatures, J. Geophys. Res., 102, 27 835-27 860, 1997.; Kondrashov, D., Feliks, Y., and Ghil, M.: Oscillatory modes of extended Nile River records (A.D. 622-1922), Geophys. Res. Lett., 32, L10702, doi:10.1029/2004GL022156, 2005a.; Kondrashov, D., Kravtsov, S., and Ghil, M.: A hierarchy of data-based ENSO models. J. Climate, 18, 4425-4444, 2005b.; MacDonald, G J.: Spectral analysis of time series generated by nonlinear processes, Rev. Geophys., 27, 449-469, 1989.; Mann, M E., Bradley, R S., and Hughes M K.: Global-scale temperature patterns and climate forcing over the past centuries, Nature, 392, 779-787, 1998.; Popper, W.: The Cairo Nilometer, 269 pp., University of California Press, Berkeley/Los Angeles, 1951. %; %Preisendorfer, R W.: Principal Component Analysis in Meteorology and %Oceanography. Elsevier, New York, 425 pp, 1998.; Ropelewski, C F. and P. D. Jones: An extension of the Tahiti-Darwin Southern Oscillation Index, Mon. Wea. Rev., 115, 2161-2165, 1987.; Mendelssohn, R., Schwing, F B., and Bograd S J.: Spatial structure of subsurface temperature variability in the California Current, 1950-1993, J. Geophys. Res., 108(C3), 3093, doi:10.1029/2002JC001568, 2003. %\bibitem[] Mann, M., J. Park, and R. S. Bradley (1995), Global interdecadal %and century-scale climate oscillations during the past five centuries, \textitNature, \textit378, %266-270. %\bibitem[] Mann, M., and J. M. Lees


Click To View

Additional Books

  • Magnetic Field Turbulence, Electron Heat... (by )
  • Inverse Modelling of Atmospheric Tracers... (by )
  • Lagrangian Characteristics of Continenta... (by )
  • Influence of Thresholding in Mass and En... (by )
  • Estimation of Permeability of a Sandston... (by )
  • Dynamics of Nonlinear Resonant Slow Mhd ... (by )
  • Stochastic Electron Motion Driven by Spa... (by )
  • Thin Layer Shearing of a Highly Plastic ... (by )
  • Toward Enhanced Understanding and Projec... (by )
  • Dynamics of Simple Earthquake Model with... (by )
  • A Study of the Phase Instability of Quas... (by )
  • Quasi-biennial Oscillations Extracted fr... (by )
Scroll Left
Scroll Right


Copyright © World Library Foundation. All rights reserved. eBooks from World eBook Fair are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.