Category Archives: GOES-16

Coastal fog under clouds in South Carolina

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), 0831 – 1331 UTC 1 March 2021 (Click to enlarge)

GOES-16 Night Fog Brightness Temperature Difference (BTD) fields (10.3 µm – 3.9 µm), above, show different cloud types in and around South Carolina before and through sunrise on 1 March 2021. Before sunrises, low clouds — stratus and fog — are characterized by blue/cyan/aqua colors in this enhancement. The positive brightness temperature difference arises because of emissivity differences in small cloud droplets for shortwave (3.9 µm) and longwave (10.3 µm) infrared radiation. Negative brightness temperature differences occur for higher clouds.

The presence of high clouds interferes with the satellite’s ability to view low clouds. Although one can infer a low cloud’s presence from an animation (and the assumption that the cloud doesn’t substantively change when a high cloud overspreads it), it’s a bit more difficult to extrapolate the cloud base from the cloud top behavior. In other words: Are the low clouds highlighted actually fog? Note also how the BTD enhancement changes as reflected solar radiation around sunrise starts to overwhelm any differences attributable to emissivity.

IFR Probability fields, shown below, combine the strength of satellite detection of low clouds with the strength model depiction of low-level saturation. IFR Probabilities will be quite high where satellites detect low clouds, and where Rapid Refresh model simulations show near-surface saturation. But if high clouds are in the way, IFR Probabilities can still be large if the Rapid Refresh model shows low-level saturation. This is occurring off the coasts of South and North Carolina. Note also: IFR Probability fields aren’t changing radically as the sun rises.

GOES-16 IFR Probability, along with surface observations of ceilings and visibility, 0831 UTC – 1326 UTC 1 March 2021 (Click to enlarge)
Night Fog Brightness Temperature Difference, Night time microphysics RGB, GOES-16 IFR Probability, 1001 UTC on 1 March 2021 (Click to enlarge)

The toggle above compares the Night Fog BTD with the Night time microphysics RGB (an RGB that takes as its green component the Night Fog BTD), and the GOES-16 IFR Probability fields at 1001 UTC on 1 March, shortly before sunrise. There is an obvious relationship between the RGB color and the regions of low clouds highlighted in the BTD by blue/cyan/aqua colors; the color of the RGB is tempered by the cloud temperature, however: the blue component of the RGB is the longwave infrared brightness temperature, and that is different over the ocean compared to over southwestern Georgia (for example). Note also how IFR Probability shows large values under the deep clouds over northwest South Carolina/western North Carolina.

Why is fog occurring offshore? Moist air over South Carolina is moving over relatively cool shelf waters, and cooled to its dewpoint; advection fog is the result. The toggle below shows surface dewpoints in the low 60s over coastal South Carolina. Sea-surface temperatures, shown at bottom from VIIRS at 0700 UTC and GOES-16 at 1300 UTC, show cool shelf waters with surface temperatures in the 50s (F).

GOES-16 IFR Probability with surface observations of ceilings/observations and surface METARs, 1001 UTC on 1 March 2021 (Click to enlarge)
NOAA-20 ACSPO VIIRS Sea Surface Temperatures (0701 UTC) and GOES-16 SST Temperatures (1301 UTC), click to enlarge

GOES-R Fog/Low Stratus Products are available in Real Earth

GOES-16 versions of the GOES-R Fog/Low Stratus products are now available in Real Earth (see this post also). (The GOES-17 versions will become available when deemed operational). At present, only the CONUS domain is rendered into Real Earth. The animation below can also be accessed at this link.

GOES-16 IFR Probability, 1451 – 1516 UTC on 5 January 2021 (click to enlarge)

GOES-R Fog/Low Stratus Products are now flowing over the SBN

GOES-16 Visible Imagery, 1706 UTC on 9 September, with IFR Probability shown at the same time (with different alpha levels) (Click to enlarge)

GOES-R Fog/Low Stratus Products have been available in NWS Forecast Offices since 2012 via an LDM feed. GOES-16 versions for these products over the CONUS domain are now flowing over the Satellite Broadcast Network (SBN), effective 9 September 2020 (Announcement). Responsibility for this data feed is now at NESDIS following an extensive research-to-operations path. Fields distributed include Probability of: Marginal Visual Flight Rules (MVFR), Instrument Flight Rules (IFR) and Low Instrument Flight Rules (LIFR). In addition to these three probabilities (Click here to see an explanation), there is also a Low Cloud Thickness product that can be used to predict the dissipation time of radiation fogs.

IFR Probabilities, as shown above, are useful because they highlight regions under clouds where visibility restrictions are most likely. Loading it under a visible image and making the visible semi-transparent, as shown above, is a handy way to use the product. A forecaster responsible for transportation concerns can therefore focus their attention where it is needed, as defined by the IFR Probability field: IFR Probability is a good situational awareness tool.

Accessing the Fog/Low Stratus products via the SBN requires TOWR-S RPM v. 19 (It will be baselined in AWIPS v. 21.3.1 in 2021). GOES-17 (and GOES-16) IFR Probabilities are available at this website for the GOES-16 CONUS and GOES-17 PACUS sectors. Work is ongoing to product GOES-17 IFR Probabilities for Alaska.

Morning IFR Conditions over South Carolina

Fog developed over North and South Carolina (some of this region has been cloudy and wet for much of the past week; here is a weekly precipitation total from this site) on the morning of 19 June 2020; the screenshot above, from this site, shows a sigmet related to the IFR conditions present:

How did GOES-R IFR Probability capture this event? The animation below, from 0900 to 1306 UTC, shows generally high IFR Probabilities over most of the region. There are stations where IFR conditions are occurring and IFR Probabilities are low: the Columbus County Municipal Airport (KCPC, in southeast North Carolina), for example, shows obstructed ceilings and reduced visibility. This might be a localized sub-pixel scale fog related to the small streams near the airport there. A similarly small-scale fog event may be happening at Macon County airport (K1A5) in western North Carolina. The 0901 UTC Brightness Temperature Difference field shows a signal consistent with valley fog along the Little Tennessee River (see image at bottom)

Note how the signal shows little discernible impact from the rising of the Sun. A strength of this product is that uniformity — in contrast to the Night Fog Brightness Temperature difference field.

GOES-16 IFR Probabilities, 0901 UTC – 1306 UTC on 19 June 2020. Surface observations of ceilings and visibilities shown in blue (Click to enlarge)

The 4-panel image below shows the ‘Night Fog’ Brightness Temperature Difference (10.3 µm – 3.9 µm, top) at 0901 and 1056 UTC and the IFR Probability fields, also at 0901 and 1056 UTC. IFR probability shows an expansion in the region of low ceilings reduced visibilities, as might be expected to occur around sunrise. The Night Fog Difference field shows a decrease in signal related to the increasing amount of reflected 3.9 µm solar insolation.

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), top and GOES-R IFR Probability, bottom, both at 0901 UTC (let) and 1056 UTC (right) on 19 June 2020.

Sea Fog near Corpus Christi

GOES-16 ABI Band 02 (0.64 mm “Red Visible”) visible imagery, 1201-2311 UTC on 20 April 2020

GOES_16 Visible imagery, above (along with surface observations of ceilings and visibilities), shows fog and low clouds over south Texas and offshore waters. The observations plotted can allow you to determine where IFR conditions are apparent — where visibilities are between 1 and 3 statute miles and ceilings are between 500 and 1000 feet. It’s difficult to determine the area of IFR conditions based solely on cloud cover however.

The animation below shows the probability of IFR conditions, a product that fuses satellite information with low-level saturation information from the Rapid Refresh model (Click here for an animation with no observations). The morning fog over east Texas burns off fairly quickly, and only dense sea fog is left after about 1700 UTC (10 AM CDT). In many offshore regions (and over east Texas before sunrise), the IFR Probability field has a flat character to it that is typical of a IFR Probability field determined mostly by model data. More pixelated data (and somewhat higher probabilities) occur where breaks in the cloud allow for satellite data to identify low clouds.

GOES-R IFR Probability, 1101 UTC to 2311 UTC on 20 April 2020

The night fog brightness temperature difference field, below, highlights a challenge in identifying low clouds using satellite data alone (in contrast to the IFR Probability above that uses satellite and model data, fusing the strengths of both). When cirrus is present, it can mask the satellite’s view of the low cloud beneath. In addition, the Night Fog Brightness Temperature difference product is not consistent through sunrise, as the emissivity differences that drive the signal at night time (small cloud droplets are not black body emitters of 3.9 µm radiation, but they are blackbody emitters of 10.3 µm radiation) become overwhelmed by reflectivity differences during the day when far more 3.9 µm solar radiation is reflected than 10.3 µm solar radiation. Thus, in the day, both low clouds and high clouds show up as black in this enhancement: they are both able reflectors of 3.9 µm radiation.

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) fields from 1101 UTC to 2311 UTC on 20 April 2020

The Day Fog Brightness Temperature Difference field, below, shows how cirrus ice crystals are initially more reflective of solar radiation, but as the sun climbs higher in the sky, low clouds start to reflect just as much solar radiation.

Day Fog Brightness Temperature Difference (3.9 µm – 10.3 µm) fields from 1201 UTC to 2311 UTC on 20 April 2020
GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 1101 UTC on 20 April 2020

The Night Fog Brightness Temperature Difference field, above, is a key component (the ‘green’ part) of the Advanced Night Time Microphysics RGB, shown below. Where the Brightness Temperature Difference field is unable to view low clouds, similarly the Night Time Microphysics RGB will be unable to highlight them.

GOES_16 Night Fog Microphysics, 1101 UTC 20 April 2020

Thanks to Penny Harness, WFO Corpus Christi, for alerting us to this event. (Link)

IFR Probability, Brightness Temperature Differences and Nighttime Microphysics RGB estimates of Fog

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and IFR Probability Fields, 1126 UTC on 17 December 2019. Also included are sky conditions, ceilings and visibilities in black or green.

Fog and low clouds were widespread over the eastern half of the United States on 17 December 2019. In this example over ArklLaTex the Brightness Temperature Difference suggests low stratus clouds over the region, and the Nighttime Microphysics shows a signal congruent with low clouds. Note, however, that observations over much of the region do not suggest IFR conditions are present. Accordingly, IFR Probability shows fairly low probabilities in this region, with values increasing to the north where visibilities decrease. IFR Probability fields screen out regions of elevated stratus because the Rapid Refresh model in this region does not suggest low-level saturation. Over northeast Oklahoma and northwest Arkansas, however, saturation at low levels is more likely and IFR Probabilities there are larger.

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and IFR Probability Fields, 1126 UTC on 17 December 2019. Also included are sky conditions, ceilings and visibilities in green.

At the same time, high clouds overspread most of the east coast as a storm moved through the area. The high clouds prevent the satellite from seeing low clouds, so both the Brightness Temperature Difference and the Nighttime Microphysics RGB will not have a signal that comports with low stratus detection. However, IFR Probability includes a signal from the Rapid Refresh model if that model shows low-layer saturation in a region of multiple cloud layers; IFR Probability has a strong signal on this date over the east coast were clouds and fog are widespread. IFR Probability also shows IFR Conditions under the low clouds that the satellite does detect over eastern Ohio, and correctly notes the a region of higher ceilings over West Virginia, western Virginia and eastern Tennessee.

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and IFR Probability Fields, 1126 UTC on 17 December 2019. Also included are sky conditions, ceilings and visibilities in green.

When high clouds are not present, there are different equally good ways to estimate low clouds, and that’s shown above. The Brightness Temperature Difference fields, the Nighttime RGB and the IFR Probability fields all tell a similar tale: Much of Iowa and regions to the south and northeast have low ceilings and reduced visibility.

Careful observers to the toggle note that the RGB has a different color over Wisconsin compared to Iowa. In part this is because the Brightness Temperature Field has values that are smaller over Wisconsin. A bigger driver of the color difference, however, is the 10.3 µm brightness temperature — the blue component of the Nighttime Microphysics RGB. Values are around -25º C over Wisconsin, and closer to -10º C over Iowa!

Nighttime Microphysics RGB and Band 13 10.3 µm Brightness Temperature, 17 December 2019

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)

Cloud Layers and Detection of IFR Conditions

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and GOES-16 IFR Probability at 1116 UTC on 22 February 2019; Surface observations of ceilings and visibilities at 1100 UTC are also plotted (Click to enlarge).

A strong storm embedded within a subtropical jet stream over the southern United States was associated with widespread fog on the morning of 22 February 2019. This screen-capture from this site shows Dense Fog Advisories over much of Georgia, and over regions near Dallas. Which products allowed an accurate depiction of the low ceilings and reduced visibilities?

The toggle above cycles between the Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), which product identifies low clouds (cyan blue in the default AWIPS enhancement shown) because of differences in emissivity at 3.9 µm and 10.3 µm from small water droplets that make up stratus clouds, the Nighttime Microphysics RGB, which RGB uses the Night Fog Brightness Temperature Difference as it green component, and the GOES-16 IFR Probability product.  IFR conditions are defined as surface visibilities between 1 and 3 miles, and ceiling heights between 500 and 1000 feet above ground level.  The plotted observations help define where that is occurring.  Multiple cloud layers from Arkansas east-northeastward make a satellite-only detection of IFR conditions challenging.  IFR Probability gives useful information below cloud decks because model-based saturation information from the Rapid Refresh Model fill in regions below multiple cloud decks where satellite information about low clouds is unavailable.

The toggle below shows the same three satellite-based fields (Night Fog Brightness Temperature Difference, Nighttime Microphysics RGB and IFR Probability)  at the same time, but centered over Oklahoma.  In this case, the Rapid Refresh Data are used to screen out a region of elevated stratus over northeast Oklahoma. Note that these is little in the Night Fog Brightness Temperature Difference field to distinguish between the IFR and non-IFR locations.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and GOES-16 IFR Probability at 1116 UTC on 22 February 2019; Surface observations of ceilings and visibilities at 1100 UTC are also plotted (Click to enlarge).

GOES-R IFR Probability over the southeast United States in this case is identifying regions of IFR conditions underneath multiple cloud decks (and also where only the low clouds are present) by incorporating low-level saturation information from the Rapid Refresh model. Over Oklahoma, non-IFR conditions under an elevated stratus deck are identified (and screened out in IFR Probability fields) by the lack of low-level saturation information in the Rapid Refresh.

Advection Fog in Warm Air Advection Regimes

‘Night Fog’ Brightness Temperature Difference field (10.3 μm – 3.9 μm) and GOES-R IFR Probability at 1202 UTC on 4 February 2019 (Click to enlarge)

Advection Fog during thaws, when very cold surfaces are overrun by air with dewpoints above freezing, can be very dense, and very difficult to detect via satellite; typically advection fog accompanies extratropical cyclones and their accompanying multiple cloud layers. The toggle above compares the ‘Night Fog’ Brightness Temperature Difference field (10.3 μm – 3.9 μm), historically used to detect low stratus because of radiation emissivity differences of clouds made up of water droplets at those two wavelengths, and GOES-R IFR Probability which fuses information from the satellite — not particularly useful in this case as far as low-level visibility is concerned — with information about low-level saturation from the Rapid Refresh Model. GOES-R IFR Probability gives a much more accurate depiction of exactly where the reduced visibilities and lowered ceilings are present, a vital piece of information for aviation (for example).

In addition, Low IFR Probability suggests where the lowest ceilings and greatest visibility reductions occur. The toggle below compares IFR Probability and Low IFR Probability at 1202 UTC (Here’s the toggle at 1642 UTC).  As expected, the region of Highest Low IFR Probability is contained within the region of highest IFR probability;  values of Low IFR Probability are somewhat smaller than those for IFR Probability (the same colorscale is used for both products).

GOES-R IFR Probability and Low IFR Probability at 1202 UTC on 4 February 2019 (Click to enlarge)

Fog over the Northeast: Where is it?

GOES-16 ABI Band 02 (0.64 µm), Band 13 (10.3 µm), Day Fog Brightness Temperature (3.9 µm – 10.3 µm), Day Snow Fog RGB and Band 5 (1.61 µm) at 1602 UTC on 28 December 2018 (Click to enlarge)

The animation above cycles through the GOES-16 Visible Imagery (Band 2, 0.64 µm), Band 13 (Clean Window Infrared, 10.3 µm), the Day Fog Brightness Temperature Difference (3.9 µm – 10.3 µm), the Day Snow Fog Red Green Blue (RGB) Composite and the Snow/Ice near-Infrared channel (Band 5, 1.61 µm) that is the green component of the Day Snow Fog RGB. (That’s very apparent in this toggle between the Day Snow Fog RGB and the 1.61 µm) Do any of these products give you a good idea of where IFR conditions (Low ceilings and reduced visibilities) are occurring?

Consider the toggle of visible imagery below, with and without surface observations of ceilings and visibility. It is a difficult prospect to relate the top-of-cloud reflectance (which is what the visible imagery gives you!) to the ceilings beneath the cloud.

GOES-16 ABI Band 02 (0.64 µm) with an without surface observations of ceilings and visibility at 1602 UTC on 28 December 2018 (Click to enlarge)

GOES-16 IFR Probability fields blend satellite observations of cloud with Rapid Refresh model data that predicts saturation near the surface. That model data, incorporated into a statistical prediction of IFR conditions, allows the field to outline the regions where low ceilings and reduced visibilities occur, as shown in the toggle below with and without observations. (Click here to see the Visible and IFR Probability fields toggled). The inclusion of near-surface saturation values extracted from the Rapid Refresh model allows the IFR Probability field to discriminate between low ceilings/fog — as over central Pennsylvania, Massachusetts and central Ohio (among other places) — and mid-level stratus — as over southwestern Pennsyvlania and surrounding Lakes Erie and Ontario (among other places).

GOES-16 IFR Probability with surface observations of ceilings/visibilities at 1602 UTC on 28 December 2018 (Click to enlarge)