Marine Fog: A Review on Microphysics and Visibility Prediction

  • Ismail GultepeEmail author
  • Jason A. Milbrandt
  • Binbin Zhou
Part of the Springer Atmospheric Sciences book series (SPRINGERATMO)


Marine fog occurs commonly over the world due to the various physical, chemical, dynamical, and radiative processes active at various time and space scales. These processes are affected by local topographical conditions such as surface height and irregularities, slope, and ocean-land boundaries and sea surface conditions as well as atmospheric physical conditions such as pollution as a source of cloud condensation nuclei, cooling rates, and moisture and heat fluxes. Marine fog is usually the result of the advection of warm air masses over cold surfaces or vice versa. Marine fog impacts transportation and shipping, aviation, and the Earth ecosystem because of reduced visibilities and increased moisture availability. Recent studies suggest that the occurrence of fog is decreasing in many part of the world over the lands but not over the ocean. Its prediction using numerical weather prediction (NWP) models includes large uncertainties on small space scales over the short time periods. In this review, first, fog observations are summarized, and second microphysics of fog and visibility were described. Fog prediction issues related to NWP model uncertainties and observational issues are then provided. In the end, future challenges related to marine fog observations and NWP model based prediction, as well as fog and climate change issues are summarized.


Numerical Weather Prediction Liquid Water Content Numerical Weather Prediction Model Cloud Condensation Nucleus Polar Warming Amplification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Regression constant in Eq. (7.19)


Cross sectional area


Aviation Digital Data Service


3.6 s h−1 L g−1; unit conversion factor


Cloud condensation nuclei


Community Climate System Model 4


Condensation Nuclei


Contiguous United Sates


Carbon dioxide


A constant for airmasses for droplet activation; 1000 cm−3 for airmasses over land


A constant in mass-size relationships (page 368), depending on particle shape


Droplet diameter


Droplet diameter in bin i


Droplet Measurement Technologies


Federal Aviation Administration


Fog droplet settling




Kinematic viscosity


Ground Cloud Imaging Probe


Global Environmental Multi-scale model


Initial conditions for a model


Ice nuclei


Ice forming nuclei


Infrared shortwave part in ch2 of GOES data


Dielectric constant for ice crystals


Dielectric constant for water droplets


Size parameters


A constant for airmasses for droplet activation; 1 for airmasses over land


A constant in mass-size relationships (page 368), depending on particle shape


Local Ensemble Prediction System


Low visibility procedure


Liquid water content


Meteorological observing range


Meteorological Service of Canada


Aerosol number concentration over ocean


Aerosol number concentration over land


Droplet number concentration


Droplet number concentration in spectral bin i


Total droplet number concentration


North American Model


National Center for Atmospheric Research


National Centers for Environmental Prediction (NCEP)


National Environmental Satellite, Data, and Information Systems


Numerical Weather Prediction


National Weather Service


The intercept parameter in gamma distribution


Droplet spectral concentration


Total droplet number concentration


Droplet spectral value at size r


Droplet number concentration at a specific supersaturation ration


Planetary boundary layer


Polar warming amplification


Fog deposition rate on a mesh


Extinction efficiency


Water mixing ratio


Effective droplet size


Regional Deterministic Prediction System


Relative humidity with respect to water


Droplet size


Effective droplet size


High resolution deterministic prediction system model


Supersaturation with respect to water


Satellite Application for Arctic Weather and SAR Operations


Search and rescue


Solar radiation sensor


Settling rate (or deposition rate) of fog droplets


Short Range Ensemble Forecast


Air temperature


273.15 K


Total precipitation sensor


Horizontal wind speed




Observed visibility


Model based visibility


Droplet terminal velocity


Fog droplet settling velocity


Vertical air velocity


Vertical air velocity after taking mean or trend out


Observed vertical air velocity


wa fluctuations


An empirical constant in Eq. (7.8) e.g., 0.49

x and y

Constants in Eq. (7.19)


Radar reflectivity factor


Radar equivalent reflectivity factor


An empirical constant in Eq. (7.8) e.g., 0.877


Dispersion parameter for size distribution (sd/mean)


Spectral shape parameter for gamma distribution or dynamic viscosity coefficient in Eq. (7.16)


Visible wavelength


Gamma distribution slope parameter


0.05 for MOR


Extinction of a visible light


Collection efficiency


Air density


Water droplet density


Surface temperature change



This work is funded by the DND SAR Office during FRAM and SAAWSO projects and focused on fog, low visibilities, and Arctic weather. Additional financial and logistic support was also provided by EC Cloud Physics and Research Section, Toronto, Ontario, Canada.


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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Ismail Gultepe
    • 1
    Email author
  • Jason A. Milbrandt
    • 2
  • Binbin Zhou
    • 3
  1. 1.Cloud Physics and Severe Weather ResearchEnvironment and Climate Change CanadaTorontoCanada
  2. 2.Atmospheric Numerical Weather Prediction ResearchEnvironment and Climate Change CanadaDorvalCanada
  3. 3.I. M. Systems Group and NOAA/NCEP/Environmental Modeling CenterCollege ParkUSA

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