Refinement of a Statistical Diagnostic Model of Marine Fog using FNWC Model Output Parameters.

Abstract

They study represents a continuation of the development of a model output statistics scheme to specify marine fog over the open ocean and in coastal waters. Thirty-seven direct and derived Fleet Numerical Weather Central model output parameters, monthly climatological fog frequencies, combinations of the aforementioned parameters (i.e. interactive parameters) and a persistence parameter are used as predictors in a stepwise multiple linear regression approach to estimate a predictand defined as marine fog probability. The predictand is categorized in two ways, in one case (FOGCAT 1) as smoothed probabilities for 0 to 100% as a function of present weather, past weather, visibility and low cloud type; and, in another case (FOGCAT 2) as a limited number of discrete probabilities (to include 0 and 100%) derived form presetn weather, past weather and visibility only. This study derives diagnostic regression equations only using as a dependent data sample over 24,000 surface synoptic ship observations at 0000 GMT for June through August 1976 and 1977. The predictor parameters contributing most significantly to the variance are sensible and evaporative heat fluxes, monthly climatologial fog frequencies, and meridional wind speed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1979
Accession Number
ADA073959

Entities

People

  • Steve O'neal Ouzts

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Space

DTIC Thesaurus Topics

  • Air Force
  • California
  • Computer Programs
  • Equations
  • Frequency
  • Geography
  • Heat Flux
  • Meteorological Phenomena
  • Meteorology
  • North Pacific Ocean
  • Numerical Analysis
  • Observation
  • Oceans
  • Pacific Ocean
  • Regression Analysis
  • Statistics
  • United States

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Atmospheric Science/Meteorology
  • Regression Analysis.