Fog developed over south Texas during the morning of 4 February. How did the GOES-R IFR Probability Products perform for this example, and what can be learned from them? There are at least two distinct regions in the animation above. Over much of southeast Texas, the IFR Probability field suggests multiple cloud layers are present. IFR Probabilities are smaller here because satellite-based cloud information cannot be used in the algorithm in regions where high/mid-level clouds preclude a satellite’s view of low stratus and fog. It is important to interpret the IFR Probability fields with knowledge of the cloud levels that are present. Towards the middle of the loop, fog develops in/around Midland over the high Plains. IFR Probabilities are large there because satellite data are used as a predictor because high clouds are not impeding the satellite’s view of the developing region of fog/stratus. Brightness Temperature Difference Fields from GOES, below, show the difficulty in using that field to detect fog/low stratus in regions where multiple cloud layers exist. There are many stations underneath high clouds that have undetectable (via satellite) IFR conditions.
MODIS data from Aqua can also be used to compute IFR Probabilities, as shown above. In general, there is very good agreement between GOES and MODIS-based fields, but there are some very interesting differences along the limb of the MODIS scan in central TX where GOES data shows smaller values of IFR Probabilities than is shown in the MODIS fields — for example at San Angelo (KSJT), Kirksville (KCOM) and Brady (KBBD). This occurs in a region where limited observations show near-IFR conditions. The higher values along the limb of the MODIS scan are likely due to limb brightening that arises because the radiation being detected comes from a path that traverses more of the (colder) upper atmosphere. The affect is wavelength-dependent, and thus will show up in a brightness temperature difference field as a stronger signal, and that stronger signal will influence the IFR Probability fields. In short: interpret MODIS IFR Probability fields along the edge of the MODIS swath with this knowledge of limb effects.
Suomi NPP also viewed the evolving fog/stratus field over Texas, and two brightness temperature difference fields, from sequential overpasses, are shown above. Brightness Temperature Difference fields can only give information about the top of the cloud, not the cloud base, and the cloud base is the important piece of information needed for fog detection. There are regions under the high clouds, for example, with IFR conditions. The eye is drawn by the enhancement to regions of low clouds/stratus, but important visibility restrictions are occurring elsewhere as well. The high resolution imagery of Suomi NPP does show compelling structures in the cloud fields, however. Note also the presence of limb brightening: Compare the brightness temperature fields west of Midland during the two times.
The Day Night Band from the morning of 4 February — near Full Moon — showed excellent structure in the cloud features, all made visible by ample lunar illumination as shown below. It is difficult, however, to use cloud-top information from the Day Night band to infer the presence of IFR conditions.