The northward movement of moist air over a snow-covered surface allowed for widespread advection fog in the midwest overnight from January 9th to 10th. The animation, above, shows GOES-R IFR Probabilities at 2-hour time steps. Included in the plots are surface observations and cloud ceilings (documenting the widespread region of IFR conditions) and the RTMA Dewpoint analysis that shows the slow northward movement of dewpoints at the surface. As this moist air moves over the cold snow-covered surface (the snow analysis from the National Operational Hydrological Remote Sensing Center is below), advection fog is a result. The GOES-R IFR Probability fields do a fine job of outlining where the IFR conditions are observed.
Note in the animation above how the presence of higher clouds moving up from the southwest affects the IFR Probability fields. As high clouds overspread the advection fog, satellite data can no longer be incorporated into the GOES-R IFR probability algorithm, and IFR Probabilities drop, in this case from values near 90% to values near 55%.
Polar-orbiting data can also give information about low clouds and fog. Temporal resolution is far superior to geostationary, as shown below. In cases of small-scale fog, polar orbiter data can give important information by identifying the first region of a developing fog. In large-scale cases such as this, high-resolution data can better identify edges to the fields. The MODIS data in this case does show high probabilities over the midwest; the brightness temperature difference field shows evidence of high clouds from central Iowa southwestward. As with the GOES data, the presence of high clouds results in lower IFR Probabilities.
Suomi/NPP data, below, from the Day/Night band shows widespread cloudiness over the midwest. The clouds are illuminated by the moon, nearly full, setting at this time in the west. Shadows are being cast by high clouds on the lower clouds over western Minnesota. The brightness temperature difference fields from Suomi/NPP are very similar to the MODIS data. In contrast to MODIS, the VIIRS instrument does not have a water vapor sensor, so the IFR Probability algorithms are not directly transferable to Suomi/NPP VIIRS data.