Estimating marine fog probability using a model output statistics scheme

• Published in: Monthly weather review 1983-01, Vol.111 (12), p.2333-2340
• Main Authors: KOZIARA, M. C, RENARD, R. J, THOMPSON, W. J
• Format: Article
• Language: English
• Subjects: Earth, ocean, space; Exact sciences and technology; External geophysics; Meteorology; Water in the atmosphere (humidity, clouds, evaporation, precipitation)
• ISSN: 0027-0644; 1520-0493
• DOI: 10.1175/1520-0493(1983)111<2333:EMFPUA>2.0.CO;2

A model output statistics (MOS) scheme, with a stepwise-selection multiple linear regression approach is used to estimate marine fog probability at 24-hr intervals from 0 to 48 hr for the North Pacific Ocean (30-60 degrees N) summer season. The predictand is uniquely determined by present and past weather, visibility, and low-level cloud information in the primary synoptic report. Available predictors include 158 Fleet Numerical Oceanography Center model output parameters as well as monthly climatological fog frequencies. The regression equations, containing, at most, seven terms, are derived from 0000-hr GMT synoptic ship report data for the months of July 1976, 1977, and 1979. Evaporative heat flux and fog frequency are among the first four parameters selected for each equation. Reliability and sharpness diagrams are presented to identify specific biases in estimating fog probability. Categorical (percentage correct, threat, and Heidke skill) and probabilistic (Brier) scoring methods are used to establish the credibility level of the MOS scheme in relation to climatology and FNOC's advective-fog probability program. The MOS scheme outperforms its competitors, with score ranges for an independent Aug. 1979 data set as follows: Heidke skill, 0.47-0.40; threat; 0.45-0.42; Brier, 0.27-0.34; and percentage correct, 78-70%.