The animation below shows IFR Probability fields layered on top of visible imagery. Early morning fog that reduced visibilities and ceilings to sub-IFR conditions are indicated over much of the middle of the Florida peninsula. (Note that the IFR Probabilty color enhancement was altered so that it was transparent for values < 20%, allowing the visible imagery beneath to appear).
GOES-16 IFR Probability Fields and Visible Band 2 (0.64 µm) imagery, 1151 – 1506 UTC (Click to enlarge)
GOES-16 Cloud Thickness fields, below, depict a shallow fog: thickness values in general are under 1000 feet. This scatterplot relates the last pre-sunrise Cloud Thickness — in meters! — to burn-off time; a value of 1000 feet will burn off very quickly as observed above.
Cloud Thickness at 1201 UTC on 23 February 2022 (Click to enlarge)
This website includes forecasts of visibility over Tampa Bay (and there are links to other coastal regions). The forecast below, for 1400 UTC 23 February / 0900 EST 23 February, has a maximum in predicted low visibility probability in about the right location. This forecast for the 24th suggests fog will be mostly offshore on the 25th.
Probability of low visibilities over/around Tampa Bay, valid 0900 EST on 24 February 2022 (Click to enlarge)
Low pressure just off the coast of South Carolina (0900 UTC map analysis) brought wide-spread fog and low ceilings to the southeastern United States on 7 February. The toggle below shows the Night Fog Brightness Temperature Difference (BTD, 10.3 µm – 3.9 µm) field that is often used to highlight regions where clouds made up of water droplets are widespread. The night time microphysics RGB includes as its green component the Night Fog BTD, and the correlation between the blue/cyan enhancement in the BTD and the cyan/yellowish color in the RGB is obvious. A challenge in using those two fields for low fog/stratus detection arises where multiple cloud layers might exist such that the BTD is not highlighting low cloud — because mid-level or high clouds block the satellite view of low clouds. This shortcoming is mitigated in IFR Probability fields by including information (from the Rapid Refresh model) on low-level saturation. Thus, IFR Probability fields suggest a greater likelihood for low clouds over coastal South Carolina (for example). If low-level saturation is *not* indicated in the model, IFR Probabilities will show minimal values, as over central Georgia (near Atlanta, especially), for example.
GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Night time microphysics RGB, and GOES-R IFR Probability, 1026 UTC on 7 February 2022 (Click to enlarge)
At 1156 UTC, a similar distribution to the three fields continues. Note how the presence of cirriform clouds over south-central Georgia affects the fields. The Night Fog BTD and Night Microphysics RGB both change radically, and IFR probabilities reduce — in part because the algorithm is less confident that low clouds exist. The small IFR Probabilities continue around Atlanta’s airline hub, important information from an aviation standpoint!
GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Night time microphysics RGB, and GOES-R IFR Probability, 1156 UTC on 7 February 2022 (Click to enlarge)
The toggle below compares IFR Probability with GOES-R Cloud Thickness. This is close to the time around sunrise/sunset when GOES-R Cloud Thickness are not computed because of quickly changing reflected solar shortwave infrared (3.9 µm) radiation; indeed, the cutoff can be viewed in the SSW-NNE terminator line over the Atlantic at the eastern edge of this image. If the low clouds on this day were strictly radiation (a dubious claim in the presence of rain!), then this scatterplot could be used to help decide when conditions might clear.
GOES-R IFR Probability and GOES-R Cloud Thickness fields, 1156 UTC on 7 February 2022 (Click to enlarge)
