Statistical diagnostic modeling of marine fog using model output parameters.
Van Orman, Brian Lee
Renard, Robert Joseph
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Diagnostic model output parameters, provided by the Fleet Numerical Weather Central, Monterey, California (FNWC) , and the marine fog frequency climatology developed at the Naval Postgraduate School, Monterey, California, are statistically processed in context with marine surface synoptic ship reports for the purpose of developing a linear regression scheme for modeling the distribution of marine fog. The study area encompasses a large section of the North Pacific Ocean (from 30-60N) . The time period involves 0000 GMT, 1-30 July 1976. The predictand is a fog parameter developed from a quantitative categorization of each of the 4481 synoptic observations according to reported present and past weather, low-cloud type, and visibility codes. The 38 model output and climatological predictor parameters are interpolated to each of the ship observation positions and the resultant data file is used for the derivation of the regression equations. The diagnostic capabilities of the regression equations, along with other existent approaches, are analyzed through the use of three verification scoring systems--Heidke Skill, Threat, and the Panofsky-Brier Probability scores. Improvement over climatology and FNWC's operational fog probability program (FTER, applied at analysis time) is demonstrated. Selective mappings of the regression equation outputs and categorized observations are intercompared with the sea-level pressure analysis; FTER; and the most significant predictor parameter in the regression equations, evaporative heat flux.
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