Marine Fog: Challenges and Advancements in Observations, Modeling, and Forecasting

Marine fog has a significant impact on human activities and the environment. A substantial portions of all accidents at sea worldwide occur in the presence of dense fog. Fog’s disruption of marine transport, harbor activities, coastal road traffic, and life threatening situations are often in the news. Fog transports droplets and their ions, aerosols, and microorganisms that alter the hydrologic, thermodynamic, nutrient, and toxicological properties of ecosystems in coastal regions. Fog also controls temperature and moisture conditions in coastal areas and consequently affects vegetation and especially forest evolution. Some of the highest degradations of air quality occur during fog under stable and stagnant anticyclonic conditions. In principle, fog forecast models should resolve a huge span of physical processes ranging from the characteristic 10⁻⁷ m scales of aerosols to synoptic processes with scales of 10⁶ m, which means the range of the smallest to the largest scales is on an order of 10¹³ m. The main variables and processes relevant to fog include aerosols and fog condensation nuclei; microphysics and precipitation; advection; synoptic conditions; air-sea interaction through surface fluxes of heat, latent heat, moisture, and momentum; air and sea surface temperature; ocean currents and upwelling; land-sea interactions and local circulations; characteristics of low marine inversion and entrainment; and coastal topography. The main goal of this book is to provide comprehensive understanding of the major processes leading to formation, evolution, and dissipation of fog by using observations, modeling, and forecasting. Discussed topics include fog observational in situ and remote sensing techniques, worldwide fog climatology, radiation and turbulence properties, microphysics and visibility parameterizations, effects of precipitation on fog, and deterministic and probabilistic fog modeling and forecasting.

Herein, an analysis is presented of the world’s marine fog distribution based upon the International Comprehensive Ocean-atmosphere Data Set (ICOADS) ship observations taken during 1950–2007. Fog, shallow fog, and mist are taken from routine weather reports that are encoded in an ICOADS ship observation with the “present weather” code. Occurrence is estimated by the number of observations of a type divided by the total present weather observations in a one-degree area. The bulk of the observations are in the northern temperate and tropical oceans, with decreasing numbers south of 20 °S and large data voids in the polar oceans. Marine fog is infrequent over most of the world’s oceans with the median occurrence 0.2 % while it is in isolated maxima for values larger than about 2 %. In a specific location, either fog or mist are the most frequent, followed with an order of magnitude lower occurrence by shallow fog.

The two major open ocean fog maxima in the world occur on the northwestern side of northern hemisphere oceans during the summer under atmospheric subsidence over a cold polar current. The distribution of the center of the maximum and highest values are over shallow water and follow the shape of the shallow bathymetry. For the highest occurrences, surface air is preconditioned by warming over a western boundary current followed by cooling over a negative SST gradient and stable lower atmosphere suppressing boundary layer exchange with the air above. The horizontal fog structure is set by surface ocean currents, sea surface temperature gradients and seasonal wind direction. Marine fog’s most frequent occurrence and largest areal coverage is in the NW Pacific in June–July–August, reaching its peak value of 59.8 % over the Kuril Islands on the western side of the Ohyashio current. The second largest marine fog maximum occurrence is in the NW Atlantic in June–July–August, reaching 45.0 % over the Grand Banks and the Labrador Current. The eastward extent of both of the NW ocean maxima is determined by the sub-polar ocean gyre.

Wind driven coastal ocean upwelling regions have a narrow zone of fog located against the coast, over the inner shelf and over the sea surface temperature minimum along the coast. A mist maximum occurs in a broader area beyond the temperature minimum. The lowest fog occurrence is in the cold season and the highest is in the warm season for all five areas except SW Africa which has its maximum in March–April–May. SW Africa has the highest single grid point fog occurrence and its upwelling, which lasts all year, and fog maximum, are both divided into two, separate areas. California–Oregon has the greatest along coast extent of fog occurrence and SST minimum as well at the lowest SST minimum. NW Africa, and Peru have significantly less fog occurrence, a shorter extent along coast of fog and a higher minimum SST. For all of the wind driven coastal upwelling zones, the Arabian Peninsula has the least fog occurrence, the shortest along coast extent as well as the highest SST minimum.

Significant fog and mist occurs at mid-latitudes in marginal seas and along the western side of northern hemisphere oceans. Over the NW Pacific, fog occurrence average of the 5 highest grid point values in the Sea of Okhotsk is 51 % in June–July–August, in the Japan Sea it is 27 % in June–July–August and the Yellow Sea it nears 15 % during March–April–May and June–July–August. The greatest fog and mist occurs along the southern China coast in December–January–March and March–April–May when the average of the 5 highest values are between 4 % and 6 %. On the NW Atlantic along the NE United States and Canada fog is most prevalent in June–July–August and least in December–January–February. During June–July–August, an elevated fog occurrence over the shelf extends along the coast from Cape Cod to SW Labrador that includes a maximum centered off the SE tip of Nova Scotia where the average of the five highest fog grid point occurrences is 41 %. The Nova Scotia maximum center is separate from that over the Grand Banks.

On the NE Atlantic appreciable fog and mist occurs around the N. European coastline in all seasons. In the North Sea, the average of the fog 5 highest grid point occurrences is greatest in March–April–May (8 %) and least in September–October–November (4 %). For the Baltic Sea, the average of the five highest fog grid point occurrences is most in March–April–May (15 %), and least is in September–October–November (6 %).

The polar seas have their greatest fog and mist occurrences during the warm season and the least during the cold season. The transitional seasons appear to have intermediate fog and mist values around the periphery while the interior is largely unsampled. Observations are mostly limited to the warm season, distributed unevenly and with vast areal data voids.

There are significant fog occurrence climate trend increases tested at the 0.05 significance level for June–July–August based upon the 1950–2007 record in three areas with high numbers of ship observations. The open ocean Kuril Island maximum occurrence in NW Pacific increased by 15.8 % and the Grand Banks maximum in the NW Atlantic increased by 12.8 %. The sea surface temperature (SST) over the same area and same period also increased which is consistent with published SST increases in the adjacent western boundary currents in both oceans. The third case is the increase of 7.4 % of the fog occurrence maximum along the California–Oregon coast over wind driven upwelling water. In contrast to the NW Ocean maximums, this coastal fog maximum is associated with a long term SST decrease.

This is a review of ground based instruments and techniques for fog detection and characterization. A review of light transmission and object perception is given as a background for visibility which is central to the definition, detection and intensity of fog. The weather reporting code characterization of fog and related aspects are discussed. The primary detection of fog has been by eye and a key variable is the horizontal visibility distance. Measurement instruments useful for fog are light transmission systems (transmissometers), light scattering visibility sensors, and present weather stations. Nearly universally and widely employed are conventional surface-based temperature and moisture sensors that are useful in identifying fog situations and closely related conditions. Solar radiation and downward longwave radiation instrument measurements are closely related to fog conditions although infrequently used in operational situations. Widely deployed automated meteorological stations have great flexibility to record data using a wide variety of instruments to detect and track meteorological changes related to fog. Automated meteorological stations and instruments are becoming more widely adapted to marine platforms including ships and buoys. Ground based, remote sensing systems at land stations measure structures in the boundary layer closely related to fog and its occurrence. Upward looking, fixed beam microwave systems detect details of the boundary layer including air temperature and moisture. Ceilometers, widely deployed at established airports are mostly used to measure the elevations of cloud bases although are capable of detecting other aspects of the boundary layer. SODAR profilers a capable of resolving small details in the winds from the surface to above 200 m. Radar wind profilers with RASS in low mode generate wind vectors and virtual temperature in approximately 60–100 m bins below about 1.5 km. Ground based scanning radar and lidar, useful for investigating three-dimensional aspects of the boundary layer related to fog conditions are largely restricted to research efforts.

Selected modeling and observational studies on the role of turbulence on marine fog formation are introduced. There can be basically three types of marine fog. Advection fog forms usually when turbulence generated by wind shear or longwave radiative cooling plays a crucial role in cooling and moistening the air above a cold sea surface after the advection of warm and moist air. In contrast, steam fog would be generated by the turbulence which plays an important role in transporting moisture from a relatively warm sea surface. The transition of stratus cloud into marine fog is another formation mechanism. The bottom of marine stratus clouds can be lowered to form marine fog by the cooling of the air just below the cloud base caused by turbulent heat loss and droplet evaporation, which can also supply moisture. Moreover, stratus cloud top can descend owing to the evaporation of cloud droplets in this region by entrainment of warm and dry air from above the cloud top under strong subsidence.

Studies on the role of radiation on the formation, evolution and dissipation of marine fog are introduced. Cooling of the air above colder sea surface can be caused by longwave radiative flux divergence and if this cooling is strong enough water vapor saturation can occur to form advection fog. Once fog droplets are formed, fog top radiative cooling due to outgoing longwave radiation plays a significant role in developing the fog layer. The dependency of longwave radiation on the fog microphysics is also examined. Contrary to longwave radiation, solar warming is found to be a main cause of fog dissipation.

This chapter provides synoptic processes in the formation, maintenance and dissipation of marine fog over the mid-latitude of the Northwestern Pacific Ocean in general and the nearby waters off China and Korea in particular based primarily, but not exclusively, on observational datasets. The marine fog examples are mostly associated with cold sea fog (warmer air flowing over a colder sea) influenced by different synoptic pressure systems, such as a local high pressure in the Yellow Sea, a cold front in the South China Sea and the Mei-Yu (Baiu in Japanese) front in the Kuroshio Extension region. Some warm sea fog (colder air flowing over a warmer sea) processes are included. Emphasis is put on two marine fog events in the Yellow Sea occurred in spring and summer, respectively. Though both are cold sea fog, they differ in many aspects, such as stratifications, synoptic-mesoscale systems, physical processes like radiative cooling and moisture supply.  Information on marine fog climatology in the mid-latitude of the Northwestern Pacific and the China/Korea adjacent seas are included in the chapter, which helps readers better understand the synoptic/dynamical analyses in marine fog events.The level of dynamical/synoptic analysis is aimed at a senior undergraduate or graduate level atmospheric science audience. It is still useful for all atmospheric science professionals at any level and for weather forecasters as well. 

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.

Although generally not discussed in the literature dedicated to fog, the presence of precipitation can have significant influences on the presence and evolution of fog. In this chapter, influences of precipitation are described, with a particular interest in its dual role in fog formation and dissipation. By the same token, the chapter also discusses a relatively overlooked phenomenon: fog formation in precipitation areas within mid-latitude cyclonic systems. A description of the multi-scale mechanisms and interactions influencing the presence of fog under this scenario is provided through the analysis of historical weather observations, theoretical concepts and results from detailed numerical modeling of rainfall evaporation. This updated description shows that precipitation-related fog formation and dissipation is determined by intricate multi-scale interactions, involving specific conditions over a wide range of scales. These include synoptic scale circulations leading to the formation of temperature inversions to the microstructure of precipitating hydrometeors. The latter determines the lagged temperature adjustment of the precipitating particles and hence their evaporation rates in near or saturated environments (influencing fog formation), as well as their size-dependent capacity to scavenge fog droplets (influencing fog dissipation).

All problems inherent to models’ imperfection and generally insufficient vertical and horizontal resolution, as well as inability to obtain full and accurate initial and boundary conditions, amplify for fog predictions. This is due to a huge span of relevant parameters and processes ranging from aerosols to hemispheric synoptic conditions. Understanding fog characteristics and evolution as well as constructing accurate initial and boundary conditions for forecasting is severely hindered by absence of dense routine and also special measurements over the vast oceans. Fog modeling and forecasting has a long history from early methods based on persistence and synoptic indicators and later through weather analysis to contemporary methods using high-resolution numerical models on regional scales, mesoscales, and microscales. The main issues that are critical to understanding and forecasting marine fog include synoptic conditions and advection, local circulations and flow properties, turbulence, characteristics of inversion and subsidence, longwave and shortwave radiative fluxes, air-sea interaction, aerosols, microphysics, and coastal topography. The two main approaches to fog predictions are statistical and dynamical forecasting methods. Some of the statistical methods are based on various statistical analyses including regressions, correlations, classifications, and tree decision diagrams. Additional statistical methods include artificial neural networks and fuzzy logic, which can successfully treat nonlinear relationships between fog predictors and predictands. The statistical methods are applicable and useful when there is a sufficient archive of fog predictor parameters and fog observations at a location of interest. An advantage of using statistical methods is their computational efficiency allowing for fog nowcasting as an independent tool or in conjunction with operational forecasting models. A disadvantage is that the statistical approach does not take into account the actual three-dimensional weather structure and evolution. Dynamical models for fog forecasting use mathematical representations of basic conservation laws and parameterizations of physical processes including the ones relevant to fog. Early research in numerical studies has used one- (1D) and two-dimensional (2D) models, which can allow for high vertical resolutions and detailed parameterization schemes. Since 1D and 2D models cannot represent the full structure and evolution of atmospheric processes, three-dimensional (3D) models have been used for operational weather forecasts. An important objective of 3D modeling studies is understanding the path history of an air mass transformation that leads to fog or fog-free conditions. Some of the main drawbacks of 3D models include the high computational requirements, which usually result in inadequate horizontal and vertical resolution, and simplifications in physics parameterization schemes. It is obviously best to use the advantages of each of these types of models and to combine them into an integrated modeling system that can improve the accuracy of the forecast. Further improvement in marine fog forecasting is obtained by treating air-sea interaction with coupled atmospheric and ocean models. Besides a deterministic approach with a single fog forecast outcome, probabilistic methods based on an ensemble of solutions are emerging. The probabilistic forecasts are able to reveal uncertainties due to the initial and boundary conditions, physics parameterizations, and model structure and setup. Advanced modeling approaches such as the large-eddy simulation (LES) technique has been also used for fog predictions. LES can simulate high-resolution atmospheric fields including turbulence on limited domains, however, they have limitations in representing realistic synoptic processes. With the rapid development of measurement networks, and especially with satellite data, it has been shown that assimilation of data into the models can significantly improve the forecast accuracy. Although initially fog forecasts were developed and applied to marine areas of North America and Europe, it is encouraging that various fog forecasting methods are being developed and applied to marine areas of other continents. Of definite interest is to estimate projections of fog characteristics using regional climate models that are recently under rapid developments. In spite of their uncertainties in initial and boundary conditions as well as in emissions of aerosols and greenhouse gases, limited resolutions, and generally simplified physics parameterizations, they are valuable tools in assessing meteorological parameters relevant to future fog occurrence and evolution.

Due to the complex structure and evolution of marine fog as well as the generally significant influence of microlocations on fog processes, many studies show that a subjective forecaster’s experience still represents a valuable component in the final creation of an accurate fog forecast.

This chapter is about ensemble fog prediction using numerical models. First, we briefly discuss why we need ensemble prediction. The sensitivity work of fog forecasts to model initial condition and physics are then reviewed. A case study is analyzed to demonstrate how ensemble approach improves over a single-run forecast in both deterministic and probabilistic point of view. The current status of operational ensemble fog forecasting and their performance at NCEP and other agencies are presented. Challenges in model-based fog forecasts are briefly discussed. Finally, ensemble verification method is overviewed as background information to readers.

Mitigating the impacts of sea fog can be facilitated with accurate detection of sea fog events in satellite observations. While low stratus clouds and fog layers are apparent in both visible and infrared passive imager observations, some challenges remain in positively identifying cases of fog. Low liquid water clouds typically appear bright in visible imagery, but are difficult to distinguish from high clouds based only on visible reflectance. Emission from cloud tops in common infrared imagery is increasingly difficult to distinguish from surface emission as the cloud top altitude decreases. Prior work suggests that knowledge of the surface temperature can increase the reliability of satellite fog detection based on visible and infrared satellite observations. However, that work relied on output from a complex weather model. Here we exploit the co-location of sea surface temperature retrievals from passive microwave imagery with visible and infrared brightness temperature observations on the NASA Aqua polar-orbiting satellite to test a method for sea fog detection that does not rely on ancillary data from weather models or surface station data. The method exploits sea surface temperature retrievals based on microwave emission even in the presence of non-precipitating clouds. Two examples of sea fog are explored that have been verified as true cases of fog in the literature. They are found to have substantial areas of cloud where the 11 μm emission temperature of the cloud is very close to the sea surface temperature value. This differs substantially from an example of subtropical stratus and stratocumulus cloud, which has been similarly explored and found to have cloud tops substantially colder relative to the sea surface compared to the fog cases. This result suggests that the multispectral approach including microwave sea surface temperature retrievals may be able to discriminate between some types of fog and other types of low water clouds that are not fog. Application of the method is currently limited by the poor spatio-temporal sampling of polar orbiting satellites and a lack of data in the coastal zone. Validation of the method will require an independent identification of open-ocean fog cases as ground-truth. Combining the microwave sea surface temperature retrievals with geostationary visible and infrared observations may be able to overcome the sampling bias of polar-orbiting satellites, which limit views of any location to only once or twice per day. Greater than 10 years of microwave sea surface temperature retrievals allow for the possibility of constructing a global climatology of sea fog if the distinguishing features of sea fog found in this study can be validated with many more cases.