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pure and applied geophysics

, Volume 120, Issue 2, pp 203–210 | Cite as

Infrared visibility prediction by statistical methods

  • Arnold Court
  • Gong-Yuh Lin
  • Stephen Zetsche
Article
  • 29 Downloads

Abstract

This study attempts to find statistical methods of predicting infrared visibility (IRV), as calculated from hourly meteorological observations from a North Atlantic weather ship. Simple and multiple regressions expressing IRV as a function of its component weather variables, and exponential data transformations, for time lags of 1 to 24 hours, gaveR2 values from 0.68 (1-hour lag) to 0.09 (24-hour lag). These have limited predictive power for lags up to 6 hours, almost none for longer lags. Two-category discriminant analysis, using class breaks at 2 km or 10 km is of little use, due to uneven data distribution.

Possibly more promising would be an application of Machine Output Statistics (‘MOS’), used routinely for temperature forecasts, to this problem.

Key words

Statistical methods for visibility prediction Atmospheric visibility 

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References

  1. Johnston, R. J.,Multivariate Statistical Analysis in Geography (Longman, New York 1978), p. 243.Google Scholar
  2. Katz, B. S., Hepfer, K., andMac Meekin, N.,Electro-Optical Meterological Sensitivity Study (Naval Surface Weapons Center (White Oak, MD 1979), PR 79-67.Google Scholar
  3. Tatsuoka, M. M.,Multivariate Analysis (Wiley, New York 1971).Google Scholar

Copyright information

© Birkhäuser Verlag 1982

Authors and Affiliations

  • Arnold Court
  • Gong-Yuh Lin
  • Stephen Zetsche
    • 1
  1. 1.California State UniversityNorthridgeUSA

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