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Space-Time ARMA Models for Satellite Ozone Data

In: Computing Science and Statistics

Author

Listed:
  • Xufeng Niu

    (University of Chicago, Department of Statistics)

  • Michael Stein

    (University of Chicago, Department of Statistics)

Abstract

In this paper, we develop some space-time autoregressive moving-average (ARMA) models for satellite ozone data, in which both the geographic neighbor effects and time-lag effects are considered. For the global TOMS ozone data over the 11-year period from January 1979 to December 1989, we divide the whole world into 10° latitude by 10° longitude blocks and calculate the monthly averages of total ozone for each geographic block. The space-time ARMA models then are applied to the monthly average series to assess the long-term changes in ozone concentrations. The long-term trend estimates over the world are all negative with the most negative trends occurring in the south polar latitudes, which is a reflection of the springtime Antarctic ozone hole that developed over the last several decades.

Suggested Citation

  • Xufeng Niu & Michael Stein, 1992. "Space-Time ARMA Models for Satellite Ozone Data," Springer Books, in: Connie Page & Raoul LePage (ed.), Computing Science and Statistics, pages 225-234, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2856-1_29
    DOI: 10.1007/978-1-4612-2856-1_29
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