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-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.
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.
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.
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.
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.
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.
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.
Thanks to Penny Harness, WFO Corpus Christi, for alerting us to this event. (Link)
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.
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.
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!
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.
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-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 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).
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 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-17 imagery in this blog post is made from GOES-17 Data that are preliminary and non-operational!
The toggle above shows GOES-16 and GOES-17 Night Fog Brightness Temperature difference fields over the Pacific Northwest shortly after 1200 UTC on 3 December 2018. The Pacific NW is a lot farther from the sub-satellite point (nadir) of GOES-16 (75.2 West Longitude) than from the sub-satellite point (nadir) of GOES-17 (at 137.2 W Longitude). Thus, the GOES-16 view is has inferior spatial resolution. There are also different parallax shifts for clouds between the two views. The scene includes plenty of stratus, based on the observations, and isolated pockets of IFR conditions: Spokane WA, Stampede Pass, WA, Pendleton OR, Medford OR, Salem OR. It’s difficult to tell at a glance from the Brightness Temperature Difference field where the lowest ceilings and poorest visibilities are — because the satellite sees the top of the cloud, and it’s difficult to infer cloud base properties from infrared imagery of the cloud top.
The Advanced Nighttime Microphysics RGB can also be used to detect low ceilings, because its green component is the Night Fog Brightness Temperature Difference as shown above. The toggle below compares the GOES-16 and GOES-17 RGBs. Again, it is difficult to pinpoint at a glance where the IFR conditions are occurring in this product.
There are subtle differences in the colors of the RGB from the two satellites. These are related to the distance from the sub-satellite point. Limb cooling will cause the brightness temperatures from the GOES-16 Clean Window to be slightly cooler than the GOES-17 values, and that will affect the color: The Clean Window is the Blue component of the RGB. In addition, the Split Window Difference values will be slightly different because of the different amounts of limb cooling in 12.3 µm and 10.3 µm brightness temperatures. GOES-17 data also includes striping that is being addressed with ongoing calibration work with the satellite.
The toggle below shows, (from GOES-16 data) the 10.3 µm – 3.9 µm Brightness Temperature Difference, the Nighttime Microphysics RGB, and the IFR Probability fields at 1202 UTC. IFR Probability fields include information about low-level saturation from the Rapid Refresh model, and that information allows the product to screen out regions of mid-level stratus; thus, the region of IFR conditions is better captured. There are three main regions: eastern WA southwestward to Pendleton OR, Seattle southward into Oregon, and the peaks of central Washington.