An Open-Ocean Marine Fog Development and Forecast Model for Ocean Weather Station Papa.

Abstract

Marine fog forecasts during the summer period in the North Pacific are not made presently with any acceptable degree of accuracy. Objective fog development models exist and are used with some success for localized coastal regions of the western U.S.; scarcity of accurate data has hindered creation of a reliable open-ocean model. The Eulerian single-station approach, utilizing a segment of the complete accurate data of Ocean Weather Station Papa (50N, 145W) is applied in this study to an objective marine fog forecasting model. The time-series study of significant atmospheric variables at OWS Papa, when coupled with a chronological synoptic overview, delineates accurately fog/no fog sequences in the summer months of 1973 and 1977. Actual observed fog situations are evaluated by the general model and presented in relation to open-ocean fog indices, NOAA 5 satellite coverage and synoptic history. The open-ocean forecast model is tested on an independent data set for the month of July 1975 at OWS Papa, with favorable results. The research delineates four required indices that must all be positive to forecast fog. These indices, when plotted daily in the region of OWS Papa allow a single station to predict, with some confidence out to twenty-four hours, the occurrence of advection fog. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1981
Accession Number
ADA104595

Entities

People

  • Robert Louis Clark

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Coastal Regions
  • Data Sets
  • Meteorological Satellites
  • Meteorology
  • Oceanography
  • Oceans
  • Plastic Explosives
  • Regions
  • Schools
  • Sea Surface Temperature
  • Space Sciences
  • Stations
  • Surface Temperature
  • United States
  • United States Naval Academy
  • Weather Stations

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space