Monthly Archives: August 2019

Dense Fog over Kansas

Dense Fog Advisory issued by Goodland Kansas on 19 August 2019 (Click to enlarge)

Dense Fog developed over portions of the central Plains on Monday morning, 19 August 2019; The Goodland Kansas office of the National Weather Service issued Dense Fog Advisories for part of their County Warning Area, as shown above.  A variety of satellite-based products are useful for monitoring dense for from satellite.  The one used for the longest time is the so-called Night Fog Brightness Temperature Difference field, shown below, that detects (in blue/cyan, in the default AWIPS color enhancement used) clouds that contain water droplets.  Small water droplets do not emit 3.9 µm radiation as a blackbody would, but they do emit 10.3 µm radiation as a blackbody.  Thus the brightness temperature that is computed by detecting via satellite the amount of radiation emitted and converting those numbers of photons to an emitting temperature (a conversion that does assume blackbody emission!) will be warmer for 10.3 µm radiation than for at 3.9 µm radiation.  An animation of that field is shown below.

GOES-16 ABI ‘Night Fog’ brightness temperature difference field (10.3 µm – 3.9 µm), 1026 – 1421 UTC on 19 August 2019 (Click to animate)

Note in the animation above that dense fog over the higher Plains or western Kansas and Nebraska is well-articulated by this field; dense fog over Iowa and eastern Nebraska is not depicted with clarity. The animation also shows a well-known feature of the Night Fog Brightness Temperature difference field — it loses a signal during sunrise as the amount of reflected 3.9 µm radiation increases.

GOES-R IFR Probability fields, below for the same time, better capture the horizontal extent of low ceilings and reduced visibilities (i.e., IFR conditions) in this case by marrying the brightness temperature difference field with low-level saturation as predicted by the Rapid Refresh model. If satellite detection suggests clouds are present — or likely — and low-level saturation is predicted by the model, then IFR Probabilities will be large. The animation below highlights the IFR conditions over western Nebraska and Kansas — but it also highlight IFR conditions in eastern Nebraska and western Iowa, regions that the Night Fog brightness temperature difference does not capture dramatically. Note that during the animation, IFR probability fields can change quickly — as updated Rapid Refresh data (that is, a more recent model run that is often more accurate) are incorporated into the algorithm.

GOES-R IFR Probabilities, 1026 – 1431 UTC on 19 August 2019 (Click to enlarge)

Because the Night Fog brightness temperature difference does not outline fog features well in eastern Nebraska and Iowa, the Nighttime microphysics Red/Green/Blue composite, that uses the Night Fog Brightness temperature difference as its green component (Night Time Microphysics Quick Guide), similarly does not outline them, unlike IFR Probability. Be alert to the strengths and weaknesses of the product used for detecting fog.

Night time Microphysics RGB, Night Fog Brightness Temperature Difference, and GOES-16 IFR Probabililty, all at 1026 UTC on 19 August 2019 (Click to enlarge)

Fog in the Mid-South on August 8th

GOES-R IFR Probability, 1002 UTC on 8 August 2019, along with surface reports of ceilings and visibility (Click to enlarge)

GOES-R IFR Probability fields from 1002 UTC on 8 August 2019, above, show a region of high probabilities mostly colocated with surface observations of ceilings and visibilities.  IFR conditions are widespread from north of Memphis TN to southern Illinois.  IFR Probability is a fused product, using both satellite imagery to detect low clouds and Rapid Refresh model data to identify regions of low-level saturation.  Where both indicators are present (for example, over extreme western Kentucky and adjacent regions of southern Illinois and northwest Tennessee), IFR Probabilities are very high and IFR conditions are observed.  There are also regions where only model data can be used — because satellites are not detecting low clouds (because high clouds are blocking the view);  such a case is over northwest Arkansas, where IFR Probabilities are high (albeit not as high as over western Kentucky) and the field is not pixelated like a satellite image can be.  IFR Conditions are observed there as well.  (Click here for a screen shot from later in the morning of the Paducah National Weather Service office front page showing Dense Fog Advisories in Tennessee, issued by the Memphis Forecast Office).

The toggle below compares the IFR Probability field with the GOES-16 ‘Night Fog’ brightness temperature difference.  There is no consistent signal in the brightness temperature difference field to indicate fog on the ground.  The color enhancement for the brightness temperature difference is created so that teal to blue is positive.  Clouds made of liquid water droplets — such as stratus, or fog — will have a strong positive value because of the emissivity properties of small water droplets.  (That is, those droplets emit 10.3 µm radiation mostly as a blackbody would, but do not emit 3.9 µm radiation as a blackbody would).  Note in particular the very dark enhancement over northwest Arkansas (suggestive of cirrus there that will block any satellite view of low clouds) and the grey enhancement over west central Tennessee, north of Memphis, where mid-level clouds are similarly blocking a good view of the stratus at the surface.

GOES-16 IFR Probability and GOES-16 ‘Night Fog’ Brightness Temperature Difference field (10.3 µm – 3.9 µm) at 1002 UTC on 8 August 2019 (Click to enlarge)

The Nighttime Microphysics RGB can also be used to alert forecasters to fog — but a main component of that detection is the Night Fog brightness temperature difference field, and where the Night Fog brightness temperature difference fails to identify fog, as above, Nighttime Microphysics will as well, as shown in the toggle below.  Which color is useful for identifying fog in the RGB below?  Almost all of them!