Category Archives: Multiple Cloud Layers

Fog and Low Stratus under cirrus

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 0801-1311 UTC on 7 May 2019 (Click to animate)

Consider the animation above, of the Brightness Temperature Difference product (10.3 µm – 3.9 µm) centered on Colorado on the morning of Tuesday 7 May 2019. The surface observations show widespread IFR conditions, but because of widespread high clouds over the region, the brightness temperature difference shows little signal that is consistent with low clouds (blue or cyan in this enhancement). There isn’t much horizontal spatial correlation between observations of low ceilings/reduced visibility and the Brightness Temperature Difference product. When low clouds are overlain by high clouds, don’t expect a satellite detection of low clouds to work. Note also how the Brightness Temperature Difference field loses its signal as the sun rises and a general increase in the amount of reflected solar shortwave (3.9 µm) infrared radiation increases.

GOES-R IFR Probability includes near-surface information that is useful, especially when mid-level or high clouds obscure the satellite view of low clouds. Rapid Refresh estimates of near-surface saturation are used to gauge the probability of IFR conditions. In the case on 7 May 2019, that information allowed GOES-R IFR Probability to approximate exactly where the lowest ceilings and more reduced visibilities were. There is therefore a much better spatial correlation between the location of surface observations showing IFR conditions, and the IFR Probability field. This has a tacit implication on how well the Rapid Refresh Model is simulating the evolution of the atmosphere. Note also that in contrast to the Brightness Temperature Difference field, a consistent signal is maintained through sunrise.

GOES-R IFR Probability, and surface observations of ceilings/visibility, 0801-1311 UTC on 7 May 2019 (Click to animate)

Because the NightTime Microphysics RGB relies on the Night Fog Brightness Temperature difference field, it rises or falls on fog detection on the shoulders of the Brightness Temperature Difference field. On this day, it fell. Click here for the Nighttime Microphysics RGB animation; the animation below toggles between the three fields — Night Fog Brightness Temperature Difference, Nighttime Microphysics RGB, and IFR Probability — at 1002 UTC on 7 May 2019.

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and GOES-R IFR Probability fields, 1001 UTC on 7 May 2019 (Click to enlarge)

Fog surrounding convection in the Midwestern United States

GOES-16 IFR Probability and GOES-16 ‘Night Fog’ Brightness Temperature Difference (10.3 µm – 3.9 µm) at 1001 UTC on 2 May 2019, along with surface observations of ceilings and visibility (Click to enlarge)

Widespread Fog occurred over the midwestern United States on Thursday morning, 2 May 2019, with some Dense Fog Advisories issued. Some of the fog developed under an extensive cirrus canopy associated with strong convection over north-central Illinois, and those cloud layers make satellite-based detection of stratus near the surface (i.e., fog) a challenge.  The toggle above between the Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) and GOES-16 IFR Probability highlights the difficulty in using the brightness temperature difference alone to outline regions of fog. In contrast, the Rapid Refresh model information on low-level saturation allows IFR Probability to alert a forecaster to the likelihood of fog in regions underneath cirrus, regions such as southeastern Illinois and southwestern Indiana.

There is an excellent spatial correlation between regions with high IFR probability and low ceilings/reduced visibilities, and also with regions with low IFR probability and non-IFR conditions (central Iowa, for example, and central Illinois southwestward into central Missouri).

Because the Night Fog Brightness Temperature difference is a central feature of the Nighttime Microphysics RGB product — Night Fog Brightness Temperature difference is the green part of that RGB, as apparent in the toggle below — Nighttime Microphysics also is challenged to identify fog in regions under cirrus

Advection Fog and Multiple Cloud Layers

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Low IFR Probability and Advanced Nighttime Microphysics RGB at 0837 UTC on 13 March 2019 (Click to enlarge)

An intense early Spring storm produced blizzard conditions over the western Great Plains on 13 March 2019 (See this blog post for example). The southerly flow in advance of the storm moved moist air over a dense snowpack over the upper Midwest, resulting in dense Advection Fog. The animation above cycles between the Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), the Advanced Nighttime Microphysics RGB that uses the Night Fog Brightness Temperature Difference as the ‘green’ and GOES-16 Low IFR Probabilities.

At 0837 UTC, high clouds had not yet covered all of the upper Midwest, and the satellite still viewed stratus clouds over Wisconsin and Minnesota (bright cyan in the Night Fog Brightness Temperature difference enhancement). Note the difference in the Low IFR Probability field in regions where high clouds are present (Iowa and states to the south and west) and where they are not. Low IFR Probability has a pixelated look over Wisconsin because modest satellite pixel-level variability is included in the IFR probability field. Over Iowa, in contrast, satellite data gives no information about reductions to visibility under the thick cloud cover; low-level data from the Rapid Refresh model drives the Low IFR Probability field there. Probabilities are high in regions where observations suggest IFR/Low IFR conditions are present. This suggest the Rapid Refresh is simulating the evolution of the atmosphere well over the Plains.

The Advanced Nighttime Microphysics RGB can detect low clouds — but only when high clouds are not in the way. For this case, the RGB signal over Wisconsin is consistent with stratus and fog, but over Iowa the signal is consistent with cirrus that is occurring there. Surface restrictions in visibility and lowered ceilings are similar in the two states, and the IFR Probability field has similar values in the two states.

By 1502 UTC on 13 March (below), high clouds had overspread the entire Midwest; Low IFR Probability relies almost entirely on Rapid Refresh Model estimates of low-level saturation.  That is why the field over northern Minnesota and northern Wisconsin is flat.  Some holes in the high clouds are suggested by the pixelated look of the field in Iowa and southern Wisconsin.

GOES-16 Low IFR Probability, 1502 UTC on 13 March 2019 (Click to enlarge)

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)

Advection Fog with a Spring Storm in the Ohio River Valley

GOES-16 IFR Probability fields, 0002 UTC through 1152 UTC on 29 March 2018, every 20 minutes (Click to enlarge)

Advection fog in the Spring, when high dewpoints overrun very cold ground surfaces, usually in association with an extratropical cyclone, are very difficult to detect using satellite-only products, as shown in the Brightness Temperature Difference field animation below (Click here for the same animation but with a 5-minute time step as observed in the CONUS domain by GOES-16). GOES-16 IFR Probability, above (Click here for an animation with a 5-minute cadence), is able to highlight the region of low ceilings and visibilities because Rapid Refresh Data supplies information about near-surface saturation that is lacking in satellite-only products such as the Brightness Temperature Difference, below, or, say, the Nighttime Microphysics RGB that uses the Brightness Temperature Difference. A toggle including IFR Probability, Night Fog Brightness Temperature Difference, and Nighttime Microphysics is below (from 0902 UTC on 29 March). Only the IFR Probability has an obvious signal difference between regions with IFR Conditions and regions without.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 0002 – 1152 UTC at 20-minute timesteps (Click to enlarge)

GOES-16 IFR Probability, Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), and Nighttime Microphysics at 0902 on 29 MArch 2018 (Click to enlarge)

IFR Probability discriminates between fog and elevated stratus over Texas

GOES-16 IFR Probability field, 1127 UTC on 13 February, along with observations of ceilings and visibility. (Click to enlarge)

GOES-16 IFR Probability fields on 13 February at 1127 UTC, above, suggest a clear difference in sky conditions between northeast Texas, where IFR Probabilities are very high, and where IFR conditions are widespread, and north-central Texas, around Dallas, where IFR Probabilities are small, and where ceilings and visibilities do not match IFR Conditions.

In contrast, the Brightness Temperature Difference field, below, (and the Nighttime Microphysics Red/Green/Blue product, shown here in a toggle with the Brightness Temperature Difference field) shows little difference in signal between the region of IFR conditions over northeast Texas and non-IFR conditions over Dallas and environs.

GOES-16 views the top of the cloud, and a region of fog and a region of stratus can look very similar in the Night Fog Brightness Temperature Difference. Because IFR Probability fields fuse satellite observations of low clouds with Numerical Model Output estimates of near-surface saturation, IFR Probabilities can differentiate between regions of elevated stratus (where near-surface saturation is not suggested by the model), such as near Dallas, and regions of stratus that is obstructing visibility (where near-surface saturation is suggested by the model).

A toggle of all three fields is shown at the bottom of this post.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 1127 UTC on 13 February 2018 (Click to enlarge)

GOES-16 IFR Probabilities, Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) and NightTime Advanced Microphysics RGB, 1127 UTC on 13 February 2018 (Click to enlarge)

Advection Fog with a strong storm in the Midwest

GOES-16 IFR Probabilities, 1152 UTC on 22 January 2018, along with 1200 UTC surface observations of ceilings and visibilities (Click to enlarge)

When skies are clear, and radiation fog forms, limiting visibilities, it’s straightforward to use satellite-only products to gauge where stratus and fog might exist. Extratropical storms generate multiple cloud layers, however; when warm sector air under multiple cloud layers overruns snow-covered or frozen ground, dense advection fog can develop, and that fog is difficult to discern from satellite because it is typically overlain by higher clouds.

GOES-R IFR Probabilities, above, (and Low IFR Probabilities here) show highest probabilities in general occur in the regions where IFR conditions were observed on 22 January.  Over much of Wisconsin and Minnesota, the IFR Probability field is mostly uniform.  Such a flat field is characteristic of a region where satellite data cannot be used to judge whether low stratus is present (because high clouds are also present).  Rapid Refresh model information only is used to outline regions of low-level saturation. There is more variability to the IFR Probability field — that is, it is more pixelated — over southwest Iowa, for example, and over North Dakota.  In these regions, low stratus clouds are being observed by satellite and both satellite and model data can be used to estimate regions of significantly reduced ceilings and visibilities.

Consider the Brightness Temperature Difference shown below. The 10.3 µm – 3.9 µm product is typically used to identify stratus and radiation fog, and it does detect those low clouds over North Dakota, and over Kansas, Missouri and southern Iowa, and over Ontario.  However, the dense clouds associated with the storm over much of Minnesota and Wisconsin meant that this brightness temperature difference field, and also the NightTime Microphysics Red Green Blue Product (which is sometimes used to detect fog), could not ‘see’ the fog over the upper midwest.

Know the limitations, strengths and weaknesses of your products as you use them!  On 22 January, High Clouds underscored limitations in the Brightness Temperature Difference product, and in the NightTime Microphysics product that relies on the Brightness Tempearature Difference product for fog detection.  That limitation meant the product was not useful in identifying IFR conditions in parts of the Upper Midwest.

GOES-16 “Night Fog” Brightness Temperature Difference (10.3 µm – 3.9 µm) at 1152 UTC on 22 January 2018. Surface reports of ceilings and visibilities at 1200 UTC are also plotted (Click to enlarge)

Dense Fog Advisories over the Plains

Dense Fog Advisories were issued over parts of the central and northern Plains states on Friday January 5. For example, from the North Platte Office (similar warnings were issued by Billings, Rapid City and Bismark offices):

URGENT – WEATHER MESSAGE
National Weather Service North Platte NE
634 AM CST Fri Jan 5 2018

…Areas of dense fog likely this morning…

.Areas of fog reducing visibilities below one quarter mile at
times will be likely from parts of southwest into the central
Nebraska Sandhills this morning. With the fog occurring where
temperatures are below freezing, some slick spots may develop on
area roads and sidewalks as well.

NEZ025-026-037-038-059-071-051800-
/O.NEW.KLBF.FG.Y.0001.180105T1234Z-180105T1800Z/
Thomas-Blaine-Logan-Custer-Lincoln-Frontier-
Including the cities of Thedford, Halsey, Dunning, Purdum,
Brewster, Stapleton, Broken Bow, North Platte, Curtis, Eustis,
and Maywood
634 AM CST Fri Jan 5 2018

…DENSE FOG ADVISORY IN EFFECT UNTIL NOON CST TODAY…

The National Weather Service in North Platte has issued a Dense
Fog Advisory, which is in effect until noon CST today.

* Visibilities…as low as one quarter mile or less at times.

* Timing…Through the morning hours with visibilities improving
after noon CST.

* Impacts…Hazardous driving conditions due to low visibility.
Fog may freeze on area roads and walkways as well.

PRECAUTIONARY/PREPAREDNESS ACTIONS…

A Dense Fog Advisory means visibilities will frequently be
reduced to less than one quarter mile. If driving, slow down, use
your headlights, and leave plenty of distance ahead of you.

&&

$$

JWS

GOES-16 IFR Probability fields captured the development of these regions of dense fog. The animation from 0400-1200 UTC on 5 January is below. Highest values of IFR Probability are consistent in the areas where IFR Conditions are developing and where Dense Fog Advisories were issued.

GOES-16 IFR Probability, 0402 – 1207 UTC on 5 January 2018 (Click to animate)

Note that IFR Probability fields are fairly high over Iowa and the eastern Dakotas, regions where mid-level stratus was widespread but where IFR observations did not occur. On this day, Low IFR Probability fields better screened out this region of mid-level stratus. The toggle below compares IFR Probability and Low IFR Probability on 0957 UTC. The region where dense fog advisories were issued shows high values in both fields. The stratus deck over Iowa and the eastern Dakotas shows much smaller values of Low IFR Probability.

GOES-16 also has a ‘Fog Product’ brightness temperature difference (10.3 – 3.9) that has historically been used to detect low clouds. However, when cirrus clouds are present, as on 5 January, the efficacy of this product in fog detection is affected. Although fog and stratus detection is identifiable underneath the moving cirrus (the same is true in the Advanced NightTime Microphysics RGB product below), identifying the low cloud as stratus or fog from satellite data is a challenge because a consistent color married to IFR Probability does not exist.

GOES-16 ‘Fog Product’ Brightness Temperature Difference (10.3 µm – 3.9 µm), 0402 – 1207 UTC, 5 January 2017 (Click to animate)

GOES-16 Advanced Nighttime Microphysics RGB, 0402-1207 UTC on 5 January 2018 (Click to animate)

GOES-16 IFR Probability fields maintain a consistent look from night to day. Both the (10.3 µm – 3.9 µm) Brightness Temperature Difference field and the Advanced Nighttime Microphysics RGB (that uses the ‘Fog Product’ BTD) will change because the increase in reflected solar radiation at 3.9 µm will change the sign of the Brightness Temperature Difference field. There is a Daytime Day/Snow/Fog RGB Product in AWIPS, and the toggle below from 1612 UTC on 5 January compares IFR Probability and the Day/Snow/Fog RGB. As with the nighttime products, the presence of high (or mid-level) clouds makes it difficult to use the RGB alone to identify regions of fog/low stratus. In contrast, the IFR Probability field continues to correctly identify where the obstructions to visibility exist.