Category Archives: GOES-16

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)

Dense Fog over the Midwestern United States

GOES-R IFR Probability Fields, 0337 – 1332 UTC on 8 August 2018 (Click to enlarge)

The longer August nights over the upper Midwest (for example, Madison Wisconsin’s night is about 70 minutes longer now than it was at the Summer Solstice) can allow for dense fog to form when light winds and clear skies follow a cloudy, damp day. The animation above shows the evolution of the GOES-R IFR Probability fields as the dense fog develops, a fog for which advisories were issued.  The horizontal extent of the widespread fog is captured well in the IFR Probability fields.  There are a couple of things worth noting.

There is a subtle — but noticeable — change in the IFR Probability Fields each hour in the animation. That change is related to model data in this fused product. Rapid Refresh Model output are used to identify regions of low-level saturation that must occur with fog. (The inclusion of this data helps IFR Probability better distinguish — compared to satellite imagery alone — between elevated stratus and fog). When output from newer model runs is incorporated (and that happens every hour), the IFR probability fields are affected. The amount of change is testimony to whether the sequential runs of the Rapid Refresh are consistent in capturing the developing fog. In this case, there were differences from one model run to the next.

GOES-R IFR Probability fields, 1202 UTC on 8 August 2018 (Click to enlarge)

Two boundaries are apparent in the animation above, captured in the 1202 UTC image above, and in the 1302 UTC image below. These boundaries are related to the Terminator, the dividing line between night and day. During an hour around sunrise, rapid changes in reflected 3.9 µm solar radiation make the detection of low clouds difficult. Temporal adjustments are incorporated into the IFR Probability fields to create a cleaner field. In the 1202 UTC image, above, the effects of sunrise are occurring along the NNW-SSE oriented boundary near the Mississippi River in southwestern WI (The boundary is parallel to the Terminator line, so it will be vertical — parallel to a Longitudinal Line — on the Equinoxes).   In the 1302 UTC image, below, the second boundary is over far northwestern Wisconsin, far southeastern Minnesota, and eastern Iowa.  The region between these two westward-propagating boundaries is where information from previous times is used in the IFR Probability fields.  Thus, when the second boundary passes, you may observe rapid changes in IFR Probability fields.

GOES-R IFR Probability fields, 1302 UTC on 8 August 2018 (Click to enlarge)

The Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) can be used to detect stratus, and that field is also a constituent (the ‘green’ part) of the Advanced Nighttime Microphysics RGB. The animation below compares these two products used to detect stratus with IFR Probability at 1002 UTC on 8 August 2018.  The Night Fog Brightness Temperature Difference fails to highlight regions of fog over central WI (and elsewhere), so neither it nor the RGB give a consistent signal over the entire fog-shrouded region.

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), GOES-R IFR Probability, and Advanced Nighttime Microphysics RGB at 1002 UTC on 8 August 2018 (Click to enlarge)

Detecting Fog under a Pall of Smoke in the Pacific Northwest

HRRR forecast of Vertically-Integrated Smoke over the Pacific Northwest (for more information see text), forecast valid at 1200 UTC on 30 July 2018 (Click to enlarge)

When smoke covers a geographic region, visible detection of low-level fog is difficult because smoke can scatter or obscure the signal from the low-level clouds.  The image above shows a Vertically Integrated Smoke Forecast from a High-Resolution Rapid Refresh Model simulation in Real Earth (link). Thick smoke was predicted to occur over the coast of Oregon.

The animation below steps through the GOES-R IFR Probability, and then the ‘Blue Band’ (0.47 µm), the ‘Red Band’) (0.64 µm), the ABI channel with the highest spatial resolution, the ‘Veggie Band’ (0.86 µm) and the ‘Snow/Ice Band’ (1.61 µm). Two things of note: Because of the low sun angle, and the enhanced forward-scattering properties of smoke at low sun angle, it is very hard to detect fog through the smoke in the visible wavelengths near Sunrise. As the wavelength of the observation increases, scattering is less of an issue. In addition, smoke is more transparent to longer wavelength radiation. Thus, the cloud edges become more apparent under the smoke in the 0.86 µm and especially the 1.61 µm imagery compared to the visible.

GOES-16 IFR Probability, and GOES-16 Single Bands (Band 1, 0.47 µm, Band 2, 0.64 µm, Band 3, 0.86 µm and Band 5, 1.61 µm) at 1342 UTC on 30 July 2018, along with surface observations of Ceilings, Visibility, and Visibility Restrictions at 1400 UTC. (Click to enlarge)

GOES-16 IFR Probability can indicate the regions of fog and corresponding restrictions in visibility because it relies on longer wavelength observations from GOES-16 (3.9 µm and 10.3 µm, principally) and information about low-level saturation from the Rapid Refresh model.  Smoke is mostly transparent to radiation in the infrared unless it becomes extraordinarily thick  (indeed, that is one reason why smoke is difficult to detect at night);  thus, the brightness temperature difference between the shortwave (3.9 µm)  and longwave (10.3 µm) infrared channels on GOES-16’s ABI can highlight cloud tops made up of water droplets that occur underneath elevated smoke.

As the Sun gets higher in the sky, fog edges beneath the smoke become more apparent because forward scattering decreases.  The animation below of the visible confirms this. In contrast, the fog edge in the IFR Probability is well-represented during the entire animation (although the horizontal resolution of the infrared channels on GOES-16 (at the sub-satellite point) is only two kilometers vs. 1/2-km for the Red Visible).

Note that IFR conditions are also occurring during this animation due to smoke over southwest Oregon.  GOES-R IFR probability detects only cloud-forced IFR conditions, but not IFR conditions because of thick smoke only.  Again, this is because smoke detection in the infrared is a challenge for ABI Channels and Rapid Refresh Model output does not as yet predict visibility restrictions due to smoke.

GOES-16 ABI ‘Red Visible’ Imagery (0.64 µm), 1342 – 1557 UTC on 30 July 2018, along with surface observations of Ceilings, Visibility, and Visibility Restrictions (Click to enlarge)

GOES-16 IFR Probability, 1342 – 1557 UTC on 30 July 2018, along with surface observations of Ceilings, Visibility, and Visibility Restrictions (Click to enlarge)

IFR Probability indicating a Cold Front

GOES-16 IFR Probability Fields, 0607-1422 UTC on 1 June 2018 (Click to enlarge)

The animation above shows increasing amounts of IFR Probability moving southward and westward over eastern Wisconsin as a cold front with Lake-influenced air pushed inward. Ceilings lowered and visibilities reduced as the front passed, and the IFR probability field’s motion could be used to predict when the temperature change occurred. High clouds did not impede the satellite view of this event, so the brightness temperature difference field, below, also showed the stratus deck as it moved inland. Missing from the satellite-only view of this event, of course, is the information on whether the cloud is extending to the surface. Furthermore, the cloud signal vanishes from the brightness temperature difference product at sunrise, as it flips sign from positive at night to negative during the day as amounts of reflected solar 3.9 µm radiation increase.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 0607-1422 UTC on 1 June 2018 (Click to enlarge)

A Meteorogram for Milwaukee for the 24 hours ending at 1500 UTC on 1 June shows the dramatic change in ceilings, temperature and wind between 10 and 11 UTC on 1 June. A similar meteorogram for Madison (here), shows a less dramatic change at 1400 UTC on 1 June.

Meteorogram for KMKE (Mitchell International Airport, Milwaukee, WI) from 1500 UTC 31 May through 1500 UTC 1 June. Note the abrupt change in surface conditions at 1100 UTC on 1 June as the front moved through (Click to enlarge)

An animation of Low IFR Probabilities is shown below.

GOES-16 Low IFR Probability Fields, 0607-1422 UTC on 1 June 2018 (Click to enlarge)

Fog in the Canadian Maritimes

GOES-16 ABI Band 2 (0.64 µm) from 0902-1312 UTC on 9 May 2018 (Click to enlarge)

GOES-16 Visible Imagery on the morning of 9 May 2018 shows the steady erosion of fog in/around the Bay of Fundy, and along coastal Maine.  The default 5-minute temporal cadence with the CONUS GOES-16 sector allows for a precise observation for when coastal fog will clear.

The satellite view of the fog in the bay was unobstructed by high clouds.  (except to the east of Nova Scotia, where a cirrus shield is apparent in the visible animation above, and in animation below)    Thus, the GOES-16 Night Fog Brightness Temperature Difference field (10.3 µm- 3.9 µm), below, could ably capture the fog’s presence and evolution.  The animation of that product, below, shows how the signal changes at sunrise as reflected solar 3.9 µm radiation overwhelms the brightness temperature difference (driven at night by differences in emissivity at 3.9 and 10.3 µm from cloud droplets): the sign flips.  Because the fog was captured in the Night Fog Brightness Temperature Difference, it was also present in the Nighttime Microsphysics RGB Composite (here), although the color associated with fog  changes as the sun rises, and clear skies also allowed the Day Snow Fog RGB Product to show the fog during the day (here).

None of the Satellite-based products can provide information on the likelihood of fog over the ocean to the east of Nova Scotia, however, because the presence of cirrus clouds there prevents the satellite from viewing low clouds.  What products can help with that?

GOES-16 ABI Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) from 0817-1312 UTC on 9 May 2018 (Click to enlarge)

GOES-16 IFR Probability fields, below, combine together satellite and model information to determine where IFR Conditions are most likely.  Very high probabilities exist where other satellite fog detection products suggest the presence of fog/low stratus (and where surface observations confirm the presence of fog).  But there are also high probabilities over the ocean east of Nova Scotia where satellite-only fog detection fails because of the presence of high clouds;  this large signal is derived from Rapid Refresh data there that suggests low-level saturation. IFR Probability combines the strengths of both satellite data and model output to provide useful information to a forecaster.

GOES-16 IFR Probability (10.3 µm – 3.9 µm) from 0817-1322 UTC on 9 May 2018

(Thanks to Paul Ford, ECC Canada, for alerting us to this event)

Added: The GOES-16 ABI Band 3 (0.86 µm) “Veggie” Band, which has great land/sea contrast, shows the fog encroaching into the Bay of Fundy during the day on 8 May. Note in particular how the low clouds race up the west coast of Nova Scotia near sunset.

GOES-16 ABI Band 3 (0.86 µm) from 1512-2257 UTC on 8 May 2018 (Click to enlarge)

Fog over the mid-South

GOES-16 IFR Probability fields with a 10-minute time step from 0752-1422 UTC on 25 April 2018 (Click to enlarge)

Dense Fog developed over the mid-south on April 25th, and Dense Fog Advisories were issued by the National Weather Service Forecast Office in Memphis for portions of western Tennessee and northern Mississippi.  GOES-16 IFR Probability fields above, show the development of strong signal in IFR Probability over western Tennessee starting after 0900 UTC.  The satellite signal for this event was weak (see below); the sudden appearance of an IFR Probability signal at 0900 UTC suggests that the Rapid Refresh model simulation quickly changed from insufficient saturation for a strong signal to a better signal of fog when the model simulation valid at 0900 UTC was used.  When IFR Probabilities suddenly change absent a big change in satellite signal, the cause is likely a change in the Rapid Refresh model output.

Night fog Brightness temperature difference, below, shows a weak signal over river valleys of western Tennessee and northwestern Mississippi.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9µm) 0822-1452 UTC on 25 April 2018 (Click to enlarge)

Because the signal in the brighntess temperature difference field is weak, the signal for fog in the Nighttime Microphysics RGB (which has as its green component the Night Fog Brightness Temperature Difference) is also weak. The toggle below shows the Night Fog Brightness Temperature Difference, the RGB, and the IFR Probability fields, all at 0952 UTC on 25 April.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9µm), NIghttime Microphysics RGB and GOES-16 IFR Probability fields, all at 0952 UTC on 25 April 2018 (Click to enlarge)

IFR Conditions in the Northeast

GOES-16 IFR Probability, 1007 UTC on 20 February 2018, along with surface observations of ceilings and visibilities (Click to enlarge)

A complex set of Low Pressure systems over the eastern half of the United States brought multiple cloud layers and IFR conditions to the northeastern United States on 20 February. The image above shows the IFR Probability field at 1007 UTC. IFR Conditions are apparent from the Chesapeake Bay northeastward through southeastern Pennsylvania and New York and coastal New England, as well as over southeastern Ontario Province in Canada and the Canadian Maritimes. These are also regions where IFR Probabilities are high, generally exceeding 80%. In regions where IFR conditions are not observed (Western Pennsylvania and Ohio, for example), IFR Probabilities are generally small.

When multiple cloud decks are present, as occurred on 20 February, satellite-only detection of low clouds is a challenge, as shown with by the brightness temperature difference field (10.3 µm – 3.9 µm), called the ‘Night Fog’ difference in AWIPS, below. High and mid-level clouds (grey/black in the enhancement used) make satellite detection of low-level stratus impossible.  So, for example, stations with IFR conditions over Long Island sit under a much different enhancement in the brightness temperature difference field compared to stations with IFR conditions over southern New Jersey and southeastern Pennsylvania.

Because the Brightness Temperature Field cannot view the low clouds, the Nighttime Microphysics RGB (shown below the Brightness Temperature Difference field) similarly cannot identify all regions of low, warm clouds — typically yellow or cyan in that RGB.

Night Fog Brightness Temperature Difference field (10.3 µm – 3.9 µm) at 1007 UTC on 20 February 2018, along with surface observations of ceilings and visibilities (Click to enlarge)

NightTime Microphysics RGB at 1007 UTC on 20 February 2018, along with surface observations of ceilings and visibilities (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.