Monthly Archives: October 2018

Fog under multiple cloud layers

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 1137 – 1452 UTC on 31 October 2018 (Click to animate)

Consider the imagery above: The Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) product can be used to highlight regions of low clouds (cloud made up of water droplets) because those water droplets do not emit 3.9 µm radiation as a blackbody (but do emit 10.3 µm radiation nearly as a blackbody), and the conversion of sensed radiance to brightness temperature assumes blackbody emissions. Thus, the 10.3 µm brightness temperature is warmer than at 3.9 µm. In the enhancement used, low stratus clouds are shades of cyan. Is there fog/low stratus along the coast of the Pacific Northwest? How far inland does it penetrate. It is impossible in this case (and many similar cases) to tell from satellite imagery alone because multiple cloud layers associated with a storm moving onshore prevent the satellite from seeing low clouds. The animation shows the Brightness Temperature Difference field along with surface reports of visibility and ceilings.  IFR and near-IFR conditions are widespread, but there is little correlation between their location and the satellite-only signal.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 1137 – 1452 UTC on 31 October 2018, along with surface reports of ceilings (AGL) and visibility (Click to animate)

GOES-R IFR Probability fields fuse together satellite information and model data to provide a better estimate of where IFR conditions might be occurring. The animation below, for the same times as above, shows a high likelihood of IFR conditions (as observed) over much of the eastern third of Washington State. The satellite doesn’t give information about the near-surface conditions in this case, but the Rapid Refresh data strongly suggests low-level saturation, so IFR probabilities are high. The field also correctly shows small likelihood of IFR probailities over coastal southern Oregon and northern California. The Rapid Refresh data used have 13-km resolution, however; fog at scales smaller than that may be present — in small valleys for example.

GOES-16 IFR Probabilities, 1137 – 1452 UTC on 31 October 2018 (Click to animate)

IFR Probability can distinguish between stratus and fog

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm). 1152 UTC on 11 October (Click to enlarge)

Consider the Night Fog Brightness Temperature Difference product, above. The enhancement is such that blue regions show where 10.3 µm brightness temperatures are warmer than brightness temperatures at 3.9 µm. At night, this occurs because cloud water droplets do not emit as much 3.9 µm radiation as a blackbody; the conversion of the sensed radiation to a brightness temperature assumes blackbody emissions have occurred, however, and as a result, the 3.9 µm brightness temperature is cool. Cloud water droplets do emit as a blackbody at 10.3 µm, so the brightness temperature over cloud water droplets is warmer than the it is at 3.9 µm. Blue, then, signifies stratus clouds in this enhancement. Can you tell where the fog is?  Do you think IFR conditions are occurring wherever the Brightness Temperature Difference field is blue?  How about under the extensive cirrus shield, associated with former Hurricane Michael, that is over the southeastern fifth of the image?

The Advanced NIght time Microphysics RGB for the same time, below, uses as one of its inputs (the ‘green channel’ in the RGB) the Night Fog Brightness Temperature Difference (Click here for a toggle between the two to reinforce that statement).

Night Time Microphysics RGB at 1152 UTC on 11 October (Click to enlarge)

GOES-R IFR Probability fields, below, for the same time are useful because Rapid Refresh model data used in IFR Probability include low-level model estimates of saturation.  If saturation does not exist underneath the cloud deck, then IFR Probabilities are suppressed.  Don’t expect fog, then, underneath the strong signal in the Brightness Temperature Difference field over most of the Midwestern United States!  In addition, the Rapid Refresh Model data defines potential fog under the big cirrus shield over the Appalachians.

GOES-R IFR Probability fields at 1152 UTC on 11 October (Click to enlarge)

Click here for the Advanced Microphyics RGB with observations of ceilings and visibility.  Here are the observations over the Brightness Temperature Difference.  Observations plotted on top of IFR Probability are shown below.

GOES-R IFR Probability fields at 1152 UTC on 11 October along with surface observations of ceilings and visibilities (Click to enlarge)

IFR Conditions with cold-season extratropical cyclones

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Advanced Night Time Microphysics RGB, and GOES-16 IFR Probability fieds at 1142 UTC on 8 October 2018 (Click to enlarge)

Fog and low stratus were widespread on 8 October over the Plains, in particular over Iowa and Minnesota.  What satellite tools exist to highlight such regions of lowered ceilings and reduced visibility?

When IFR conditions — fog and low stratus — occur with extratropical cyclones that generate multiple cloud layers, satellite detection of low clouds is difficult because higher clouds get in the way of the near-surface view. The animation above steps through the Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm; low clouds in the default enhancement are cyan), the Nighttime Microphysics Red-Green_blue (RGB) composite (low clouds in the RGB are cyan to yellow, depending on the temperature) and the GOES-R IFR Probability field (Probabilities for IFR conditions are highest in orange/red regions) for 1142 UTC on 8 October 2018, when low ceilings were widespread over the Plains and East Coast. Abundant high clouds rendered the Night Fog Brightness Temperature difference product (and, by extenstion, the Night Time Microphysics RGB, because the RGB uses the Night Fog Brightness Temperature Difference as its ‘Green’ Component) ineffective in outlining potential regions of low clouds. In contrast, the IFR Probability field was able to highlight low clouds under the high clouds because it fuses satellite data (ineffective at this time) with Rapid Refresh model estimates of low-level saturation.

There are regions — southern Lake Erie, for example — where the lack of high clouds allows the Brightness Temperature Difference field, and the Nighttime Microphysics RGB to operate with success in identifying low clouds.

The toggle below shows the Night Fog Brightness Temperature Difference and the IFR Probabiity fields over the eastern portion of the country.  Very small-scale (in the horizontal) features, such as river fog, are a challenge for IFR probability because the Rapid Refresh horizontal resolution of 13 km may not resolve river valleys.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) and GOES-16 IFR Probability fieds at 1142 UTC on 8 October 2018 (Click to enlarge)