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An operational marine fog prediction model
  • Published Date:
    1990
Filetype[PDF - 770.17 KB]


Details:
  • Corporate Authors:
    National Meteorological Center (U.S.)
  • Series:
    Office note (National Centers for Environmental Prediction (U.S.)) ; 371
  • Document Type:
  • Description:
    A major concern to the National Weather Service marine operations is the problem of forecasting advection fogs at sea. Currently fog forecasts are issued using statistical methods only over the open ocean domain but no such system is available for coastal and offshore areas. We propose to use a partially diagnostic model, designed specifically for this problem, which relies on output fields from the global operational Medium Range Forecast (MRF) model. The boundary and initial conditions of moisture and temperature, as well as the MRF's horizontal wind predictions are interpolated to the fog model grid over an arbitrarily selected coastal and offshore ocean region. The moisture fields are used to prescribe a droplet size distribution and compute liquid water content, neither of which is accounted for in the global model. Fog development is governed by the droplet size distribution and advection and exchange of heat and moisture. A simple parameterization is used to describe the coefficients of evaporation and sensible heat exchange at the surface. Depletion of the fog is based on droplet fallout of the three categories of assumed droplet size. Comparison of three months of model results over the Atlantic seaboard with ship data show realistic forecasts of fogbound areas. The MRF initial conditions are used to update the fog model boundaries, thus supplying "perfect forecasts" for the fog model boundary conditions. Liquid water droplet concentrations are used to infer the relative intensity of fog and compare well with visibility reports from ship locations. It should be noted, however, that the verification of fog at sea is hampered by the limited amount of routinely available ship observations. The model also successfully predicted situations in which no fog was present when similarly verified with ship data. These results show that diagnostic models can be developed for specific regional applications based on numerical weather forecasts made with large scale global models.

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