Low, thin clouds and fog developed across northern Illinois snowpack overnight into the morning hours of 13 Jan 2022. Comparison of single band imagery with multispectral Imagery and level-2 products remind us of the advanced methods we have for analyzing low clouds and fog in complex scenes, in this case, during the day. One-minute imagery was available over the region during the period, which is quite valuable when monitoring the real-time evolution of low clouds near TAF sites.

Starting off with visible imagery, the scene is encompassed with a lot of light gray to white, representing both snow and cloud cover, diagnosed by stationary and non-stationary movement, and shadows (Fig 1). Near the IA/IL border, some movement is noted representing likely low clouds, but the delineation between low clouds and snow cover is difficult.

While Geocolor establishes a more familiar scene from space, including adding color to non-snow surface features, it doesn’t do much to help to separate clouds from snow cover (Fig 2).

IR Window imagery helps capture the higher (colder clouds), but again doesn’t help much with differentiating potential low clouds from the similar-temperature snow surface (Fig 3).

By combining the VIS, IR and Snow/Ice bands, we are left with a picture that separates snow cover (green) from low (liquid) clouds (cyan, light blue) from high (ice) clouds (pink/red) in the Day Cloud Phase Distinction RGB (Fig 4). High detail is maintained in the features with the inclusion of the 0.5 km VIS. The reflectance components can easily/quickly be adjusted in AWIPS (lower max) to draw out features during low light situations. The nearly stationary and semi-transparent low clouds across northwest Illinois, which could not be diagnosed in previous imagery, is easily observed in the RGB against the snowy background.

Similarly, the Day Snow-Fog RGB combines the Veggie Band, Snow/ice Band, and Fog Difference to separate snow cover from clouds (Fig 5).

The FLS Probability level-2 product, now available in AWIPS, combines satellite and NWP information to give a probability of MVFR, IFR, and LIFR conditions (and Cloud Thickness). During the day, the areal extent of coverage matches well with appearance in imagery, though with reduced spatial detail and some difficulty in multi-layer cloud scenes (Fig 6).

One method for incorporating the quantitative fog products into AWIPS workflow is to underlay the three fog probability products in your typical Cloud imagery display. In the example shown, sampling the area will not only show the RGB readout information, but also the probabilities of the various restrictions, for that location (Fig 7). This type of display allows one to view the imagery but still get the benefit of the quantitative information without taking away valuable screen real estate, while also helping to connect the quantitative product to the imagery.

Bill Line, NESDIS and CIRA