GOES-R IFR Probabilities, hourly from 0400 through 1215 UTC on 5 December 2016 (Click to enlarge)
Dense Fog developed over the southern Plains early on Monday 5 December, and the GOES-R IFR Probability fields, above, were a tool that could be used to monitor the evolution of this event. A challenge presented on this date was the widespread cirrus (Here’s the 0700 UTC GOES-13 Water Vapor (6.5 µm) Image, for example) that prevented satellite detection of low clouds. The Brightness Temperature Difference fields, below, at 3-hourly intervals, also show a signature (dark grey/black in the enhancement used) of high clouds, although they are shifting east with time — by 1300 UTC there is a signature (orange/yellow in the enhancement used) of stratus clouds over central and eastern Oklahoma.
The IFR Probability fields, above, have a characteristic flat nature over Arkansas and Missouri, that is, a uniformity to the field, that is typical when model data are driving the probabilities. The more pixelated nature to the fields over Kansas and Oklahoma, especially near the end of the animation, typifies what the fields look like when both satellite data and model data are driving the computation of probabilities. Careful inspection of the fields over Arkansas shows regions — around Fayetteville, for example, around 1000 UTC where IFR Probabilities are too low given the observation at the airport of IFR conditions. This inconsistency gives information on either the small-scale nature of the fog (unlikely in this case) or on the accuracy of the Rapid Refresh model simulation that is contributing to the probabilities. In general, the Rapid Refresh model has accurately captured this event, and therefore the IFR Probabilities are mostly overlapping regions of IFR or near-IFR conditions. The region over southern Illinois that has stratus, and low probabilities of IFR conditions, for example. Adjacent regions have higher IFR Probabilities and lower ceilings and/or reduced visibilities. A screen shot from the National Weather Service, and from the Aviation Weather Center, at about 1300 UTC document the advisories that were issued for this event.
Brightness Temperature Difference fields (3.9 µm – 10.7 µm), 0400, 0700, 1000 and 1300 UTC on 5 December 2016 (Click to enlarge)
GOES-R IFR Probability Fields, 0200-1400 UTC on 13 October 2016 along with surface observations of ceilings/visibility (Click to enlarge)
Because GOES-R IFR Probability fields are computed with the same time latency as GOES imagery, motion of the IFR Probability fields can have predictive value. In the animation above, higher GOES-R IFR Probability is moving eastward; IFR Conditions are reported as the higher IFR conditions move overhead (consider, for example, Bowling Green, KY, or Clarksville, TN), and ceilings / visibilities improve as the band of higher IFR conditions moves eastward from a station (over southern Illinois, for example).
GOES-R IFR Probability Fields, 1437 UTC on 31 August 2016, with surface observations of ceilings and visibilities (Click to enlarge)
GOES-R IFR Probability Fields over Colorado and Nebraska on the morning of 31 August 2016 show high IFR Probabilities in close proximity to Denver International Airport (DIA), which airport was reporting IFR conditions starting at 1237 UTC. Webcams to the southwest and northeast of the airport shortly after 1500 UTC confirm that the IFR conditions’ edge was very near the airport.
The hourly animation of GOES-R IFR Probability fields, below, shows the evolution of the field. Its motion could be used in a prognostic manner.
GOES-R IFR Probability fields, ~hourly from 0400 through 1400 UTC on 31 August 2016 (Click to enlarge). Surface observations of ceilings and visibility are also plotted.
A similar event occurred on 22 September, see below from Mike Eckert and Amanda Terborg.
GOES-R IFR Probability, hourly from 0600 through 1400 UTC on 9 August 2016 [Click to enlarge]
GOES-R IFR Probabilities show the development of IFR-producing stratus and fog over central and western Nebraska between midnight and dawn on 9 August 2016. The character of the field suggests that satellite data and Rapid Refresh Model output are both contributing to IFR Probability fields; IFR Probability fields will look far flatter in appearance (just one color) when model fields only are used.
When the Sun rises, the predictors that are used to compute IFR Probabilities change, and that change is evident in the 1245 UTC image below. Night-time predictors are being used to the west of the obvious boundary through central Nebraska, and day-time predictors are being used to the east. It’s more common for IFR Probability values to increase when Day-Time predictors are used, but on 9 August values decreased. (You can see from the animation above that the IFR Probability values subsequently rebounded)
GOES-R IFR Probability at 1245 UTC on 9 August 2016 [Click to enlarge]
GOES-R Cloud Thickness can be used to estimate when fog/low stratus will dissipate (using this scatterplot
). The image below shows the last Cloud Thickness before twilight conditions (during twilight conditions, GOES-R Cloud Thickness is not computed — over Nebraska at this time of year, that’s generally about 2 hours starting around 1145 UTC). The largest values are around 1280 feet, which corresponds to a dissipation time of more than four hours, meaning the fog/low clouds should persist to at least 1530 UTC!
GOES-R Cloud Thickness just before Twilight Conditions over Nebraska, 1130 UTC on 9 August [Click to enlarge]
GOES-14 was observing Nebraska at 1-minute intervals on 9 August, as part of GOES-14’s SRSO-R. The animation from dawn (~1204) through 1610 UTC is below. Fog Dissipation is mostly complete by 1600 UTC.
GOES-14 Visible Imagery (0.62 µm) from 1204-1610 UTC [Click to view very large animation]
GOES-R IFR Probability Fields, hourly from 0315 through 1215 UTC on 18 May 2016 (Click to animate)
Dense Fog Advisories were issued by the Des Moines Forecast Office on 18 May as fog developed across southern Iowa. The IFR Probability Field animation, above, articulates where the fog is developing — most of the stations reporting IFR (or near-IFR) conditions are within the region of enhanced IFR Probability, and regions where IFR conditions did not develop show persistent low values of IFR Probability.
Compare the 1015 UTC image of GOES-R IFR Probability and the GOES-13 Brightness Temperature Difference (a traditional way of detecting the presence of low clouds/fog at night), below. Because the IFR Probability fields incorporate information from the Rapid Refresh Model about low-level saturation, IFR Probability screens out the region in central and northern Iowa where the Brightness Temperature Difference field suggests clouds might be forming (but where surface observations show scant evidence of cloud).
GOES-R IFR Probability and GOES-13 Brightness Temperature Difference (10.7 µm – 3.9 µm) fields, 1015 UTC on 18 May 2016 (Click to enlarge)
The fog that developed over Iowa was fairly thin and should dissipate quickly under a strong May sun. The GOES-R Cloud Thickness field from 1045 UTC, the last complete field before twilight conditions, below, shows values mostly less than 700 feet with a few pockets of 800-900 feet. The toggle below shows the GOES-R Cloud Thickness at 1045 UTC and the IFR Probability field 90 minutes later. Regions with the thickest fog at 1045 UTC do show a persistent signal in the IFR Probability field 90 minutes later.
GOES-R IFR Probabilities at 1115 UTC and 1100 UTC surface observations of ceiling and visibility (Click to enlarge)
The image above shows GOES-R IFR Probabilities over North/South Dakota and Minnesota shortly before sunrise on Monday April 18 2016. There is a distinct difference in the field between western Minnesota and eastern North and South Dakota that occurs because Rapid Refresh model fields (low-level saturation) are used as a predictor of IFR Probability. Reduced visibilities and ceilings are reported where IFR Probabilities exceed 50% (the orange shading). In contrast, the window channel and water vapor imagery for the same time, below, gives little indication that fog and low ceilings are present over eastern North and South Dakota: satellite views of the lowest levels are blocked by mid- and upper-level clouds. Fusing model data and satellite data into one predictor yields a superior product for detection of low ceilings and reduced visibilities.
GOES Infrared imagery (10.7 µm and 6.5 µm) and GOES-R IFR Probability fields, 1115 UTC on 18 April (Click to enlarge)
GOES-13 Brightness Temperature Difference (10.7 µm – 3.9 µm) at 1215 UTC on 29 March 2016 (Click to enlarge)
Consider the brightness temperature difference field above, from 1215 UTC on 29 March 2016. A strong signal that indicates water-based clouds extends from central Oklahoma to west Texas, and also from south Texas to west Texas. Are these water-based clouds obscuring visibilities at the surface? Over much of the region they are not. The Brightness Temperature Difference field gives information about the top of the cloud, but not the cloud base.
The GOES-R IFR Probability field for the same time, below, has screened out much of the region of mid-level stratus over Oklahoma and Texas. This can occur because IFR Probability fields include information from the Rapid Refresh Model. If that model does not indicated low-level saturation, IFR Probabilities will not be large. In the example shown, large values of IFR Probabilities are restricted to regions where IFR or near-IFR conditions are occurring.
GOES-R IFR Probability Fields at 1215 UTC on 29 March 2016 (Click to enlarge)
GOES-R IFR Probabilities, 2200 UTC on 28 February 2016 as well as surface observations of ceilings and visibilities (click to enlarge)
Late in the day on 28 February, as shown above, GOES-R IFR Probability fields included a small region of enhancement over west-central Arkansas and east-central Oklahoma. In this case, that field heralded the development of more widespread IFR conditions over northeast Texas (and surroundings). By 0300 on 29 February, below, IFR probailities in the region over east-central Oklahoma/west-central Arkansas had increased, and there is a suggestion of increasing IFR Probabilities over northeast Texas as well. This is a case where IFR Probabilities can alert a forecaster to pay attention to a region long before a hazard develops.
GOES-R IFR Probabilities, 0315 UTC on 29 February 2016 as well as surface observations of ceilings and visibilities (click to enlarge)
Late February starts the time when GOES-13 is near enough to eclipse season that stray light can creep into imagery. In this case, a large signal increase between 0500 and 0515, below, is in part related to stray light, and in part to low cloud development. By 0530, IFR Probability fields show less affect from stray light. (Click here for an animation of brightness temperature difference fields alone; Stray Light has an obvious impact at 0515 UTC).
GOES-R IFR Probability fields, 0500-0530 UTC, 29 February 2016, showing Stray Light Effects (Click to enlarge)
IFR Probability fields from 0615 through 1215 UTC are shown below. Very high IFR Probabilities (and IFR conditions) were widespread in the early morning over northeast Texas and surrounding states.
GOES-R IFR Probabilities fields, hourly from 0615-1215 UTC, and surface reports of ceilings and observations (Click to enlarge)
GOES-R IFR Probability fields, hourly from 0415 to 1515 UTC on 22 February, along with surface observations of ceilings and visibilities (Click to enlarge)
Dense Fog developed in two regions over Nebraska overnight, as shown in the screen capture below (from 1445 UTC) showing Dense Fog Advisories. GOES-R IFR Probabilities discerned the differences between the two regions, as shown in the animation above. The fog feature near the Missouri River (the boundary between Iowa and Nebraska) developed first in a region where high clouds were also present. That high clouds are present is apparent from the flat nature (that is, not pixelated) of the IFR Probability field at, say, 0415 and 0515 over western Iowa. The second region of fog, over south-central Nebraska, develops under clear skies as evidences by the (initially) very pixelated field. Towards the end of the animation high clouds overspread that region also. When that happens, IFR Probability values drop (because only model predictors can be used in the computation of IFR Probability in regions where high clouds exist). At the end of the animation, largest IFR Probabilities overlap the two regions where Dense Fog Advisories were issued. The region in between the advisories has lower Probabilities.
Compare the IFR Probability field, above, to Brightness Temperature Difference, below. Brightness Temperature Difference fields identify regions of Fog and Stratus, but near-surface information cannot be extrapolated (consistently) from cloud-top information. Thus, many stations with ceilings and visibilities far better than IFR conditions are in regions where a strong Brightness Temperature Difference signal exists (for example, KONL in northeastern Nebraska), The incorporation of surface information via Rapid Refresh model predictions of near-surface saturation allows the IFR Probability fields to better outline regions of IFR conditions only.
GOES-13 Brightness Temperature Difference (10.7 µm – 3.9 µm), 1300 UTC on 22 February 2016 (click to enlarge)
GOES-13 IFR Probability fields, 0100-1400 UTC, 6 January 2015, and surface observations of ceilings and visibility (Click to enlarge)
National Weather Service offices in El Paso and in Lubbock issued dense fog advisories for portions of their respective CWAs early on 6 January 2016. Moisture from a storm entering from the Pacific Ocean (as suggested by this graphic showing the GFS 00-h analysis from 1200 UTC showing the 300-mb jet) means multiple cloud layers. Higher clouds make satellite-only detection of low clouds difficult, and the animation above shows regions (north of Roswell — KROW — at the end of the animation, for example) where the flat GOES-R IFR Probability field suggests only Rapid Refresh data are diagnosing the probability of IFR conditions.
The Brightness Temperature Difference fields, below, for the same times as the IFR Probability fields at top, miss regions of reduced visibility under multiple cloud layers, and also have strong returns in regions of mid-level stratus. Because GOES-R IFR Probability incorporates information about saturation in the lowest 1000 feet of the atmosphere (in the form of Rapid Refresh Model Output), regions that are saturated in low levels that cannot be diagnosed as foggy by satellite alone because of mid-level/high-level clouds can be flagged as likely having IFR conditions, and regions that are flagged by the satellite as having stratus (stratus and fog can look very similar to a satellite) can be screened out if low-level saturation is not diagnosed in the model. Both of these actions serve to increase the GOES-R IFR Probability’s ability to diagnose correctly areas of low clouds/fog relative to brightness temperature difference fields alone.
One other advantage to GOES-R IFR probability fields: They are not strongly affected by changing amounts of 3.9 µm radiation around sunrise/sunset. In the animation below, note how at 1400 UTC (just past sunrise) the brightness temperature difference signal is collapsing. This is because increasing amounts of reflected solar 3.9 µm radiation are changing the difference between observed 10.7 µm and 3.9 µm radiation above water-based clouds. Little change occurs in the IFR Probability fields at this time however.
GOES-13 Brightness Temperature Difference (10.7µm – 3.9µm) fields, 0100-1400 UTC, 6 January 2015, and surface observations of ceilings and visibility (Click to enlarge)