While it may “come in on little cat feet,” the impact of fog—a visible mass of cloud water droplets (or ice crystals) suspended in the air at or near the Earth's surface— is often greater than Carl Sandburg’s poem suggests.
Unexpected areas of fog or low stratus clouds can drastically reduce visibility, creating dangerous conditions for drivers and pilots. According to the US Department of Transportation’s Federal Highway Administration, fog played a role in an average of 28,533 automobile accidents between 2004 and 2013 and, each year, an estimated 440 people are killed due to weather-related aviation accidents, including the conditions of low visibilities and ceilings.
Because fog can form rapidly and occur in small patches or narrow bands, it can be difficult to detect. Fortunately, NOAA satellite data is helping scientists zero-in on it and making transportation safer.
Detecting Low Clouds from Way Up
NOAA's current suite of geostationary orbiting environmental satellites – GOES-13, -14, and -15 – carry the I-M Imager, a five-channel radiation-detecting imager, and its polar-orbiting environmental satellites (POES) – NOAA-15, -18, and -19 – feature the Advanced Very High Resolution Radiometer (AVHRR), a six-channel imaging radiometer. Both of these instruments possess visible wavelength, shortwave infrared, and longwave infrared channels that can be used to detect the properties that help scientists differentiate fog from other cloud types.
For example, the visible wavelength channel can be used to detect cloud droplet size (fog has smaller-sized cloud droplets as compared to those produced in the formation of other cloud types) and the infrared channels can be used to gauge cloud temperatures by the radiation they reflect, as fog is warmer than other cloud types.
Further, data from GOES or NOAA imager channels can be used in concert to create cloud products (some of these are still in theexperimental stage of development), such as “fog depth” imagery, which scientists can use to estimate the thickness of a cloud layer based on temperature, and a “Low Cloud Base” product that can be used to warn aviators about the location of clouds less than 1,000 feet above the surface.
A Step Up in Detecting Low Clouds
The imagers on the GOES and NOAA satellites are good, but the Visible Infrared Imager Radiometer Suite (VIIRS) aboard NOAA/NASA's Suomi-NPP is better. Building on the legacy of its predecessors, such as the AVHRR, VIIRS offers 22 spectral bands, including a Day-Night band that not only views clouds by the sunlight they reflect during the daytime, but also by the moonlight, and other nightglow, that they reflect at night!
Further, VIIRS data can be processed to create a variety of fog and low-cloud data products, such as the “cloud mask” product, which helps scientists detect where clouds are located, and the “cloud particle size” product, which gives forecasters an idea of the number of cloud particles in a particular area.
Not to be outdone, the next generation of GOES, called GOES-R (for series R), will feature the Advanced Baseline Imager (ABI), which will be able to view the Earth in 16 spectral bands (as compared to just five on the current GOES imager), provide three times more information on the separate wavelengths of light reflected from the atmosphere, offer four times the spatial resolution, and cover areas five times faster than the current technology.
GOES-R isn’t scheduled to launch until October 2016, but by using data from several current satellites (GOES, MTSAT, MODIS, AVHRR and SEVIRI) and numerical weather prediction data from a variety of models (Global Forecast System, Rapid Update Cycle, and Rapid Refresh) to approximate GOES-R data, forecasters are already using the GOES-R fog/low cloud detection algorithm with success. Whereas heritage GOES fog detection products provide a more quantitative assessment of fog in an area, the GOES-R algorithm provides quantitative information on fog probability. The GOES-R fog/low stratus products also work day and night and provide information even when multiple cloud layers are present. The GOES-R algorithm is currently used by the North American Mesoscale (NAM) Forecast System models to estimate the onset and dissipation of fog/low ceilings over air terminals.
The advent of these multi-spectral, high-resolution imagers are a boon to the scientific community, as the data they provide will lead to more accurate information about atmospheric conditions that can then be conveyed to motorists and pilots, potentially saving hundreds of lives each year.