Infrared visibility prediction by statistical methods
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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 wordsStatistical methods for visibility prediction Atmospheric visibility
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