Starting 21 October 2021, GOES-R IFR Probability fields are archived (for both GOES-16 and GOES-17, Full Disk and CONUS/PACUS domains) at NOAA CLASS. These fields are available under the drop-down menu: Choose ‘GOES-R Series L2+ Enterprise Products (GRABINDE)’, as shown below.
Clicking on ‘>>Go‘ after selecting the product takes a user to the page below, from which page ABI Fog/Low Stratus products can be obtained.
The files retrieved from CLASS will be netCDF files with a filename structure such as this:
The file name above is for GOES-16 data from 0811 UTC on 22 October 2021. Such data can be displayed in (for example) Panoply, as shown below. Additionally, one could configure an AWIPS session to accept the fields.
The netCDF files include many different 2-dimensional fields: IFR Probability, MVFR Probability, Low IFR Probability, Cloud Thickness, Maximum Relative Humidity between the surface and 500 feet AGL, Maximum Relative Humidity between the surface and 3000 feet AGL, Band 7 (3.9) Emissivitiy, and many more. A Full Disk image below (courtesy Tim Schmit, NOAA STAR), shows IFR Probability values on 27 October 2021 at 0000 UTC.
The animation above shows various methods typically used to detect fog/low stratus in the early morning. Night Fog Brightness Temperature differences, bottom left, and Night Time microphysics, bottom right, are both satellite-only detection systems; a shortcoming might be that satellite data is challenged in detecting cloud bases — satellites view the cloud top. Additionally, the signal is lost as the sun rises. IFR Probability (upper right) includes information (from the Rapid Refresh model) on low-level saturation, so perhaps that field better defines the scattered pockets of fog apparent on this morning. However, the Rapid Refresh model resolution is 13-km, and a valley fog might not be well-resolved in the model.
The Cloud Thickness information suggests that any clouds are thin, and that morning burn-off will be speedy. That is indeed what happened, as shown by the 1500 UTC image below (taken from the CSPP Geosphere site). Recall that the Cloud Thickness product is not produced in the times that surround sunrise (or sunset).
Mid-day observations over southeastern New England (and the offshore islands) show widespread fog. The toggle above shows mid-day visible imagery and GOES-16 IFR Probability. It’s very difficult to assess from the satellite imagery (especially on a day such as 4 June when high clouds are also present) alone where the reduced visibilities sit. Because IFR PRobability includes information on low-level saturation from the Rapid Refresh model, a better estimate of the horizontal extent of fog results. High IFR Probability values are widespread along the south coast of New England and the offshore islands where IFR and Low IFR conditions were observed. IFR Probability is a useful Situational Awareness tool. It can also be useful to load the imagery such that the IFR Probability is underneath a semi-transparent visible image, as shown below.
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.
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 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!
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)