GOES-13 Brightness Temperature Difference (3.9 µm- 10.7 µm) and GOES-R IFR Probability fields computed with GOES-13 and Rapid Refresh Data, 1100 UTC 18 October. Plots of ceilings and surface visibilities are included (Click to enlarge)
GOES-R IFR Probability fields often to a better job (compared to brightness temperature difference fields) in outlining exactly where low ceilings and reduced visibilities are occurring because IFR Probability fields include information about low-level saturation from the Rapid Refresh model. That information about near-surface saturation allows the IFR Probability algorithms to screen out regions where only mid-level stratus is occurring. A low fog — a stratiform cloud of water droplets that sits on/near the surface — and a mid-level stratus deck (also a stratiform cloud of water droplets) can look very similar in a brightness temperature difference field. In the example above, consider much of northeastern Alabama and northern Georgia. There is a strong return in the brightness temperature difference field because mid-level stratus is present — but IFR Probabilities are small because the Rapid Refresh does not diagnose low-level saturation in the region. Compare Brightness Temperature Difference returns over northeast Alabama and over extreme western North Carolina — to the west of Asheville. IFR Conditions are observed over western North Carolina, and IFR Probabilities are high there. In general, the region with high IFR Probabilities in the toggle above includes stations that are reporting IFR or near-IFR conditions. Most stations outside the region of high IFR Probability are not showing IFR Conditions, even though they may be in a region with the Brightness Temperature Difference signal is large.
A similar story can be told farther west at 0800 UTC, shown below. Focus on the region with a strong Brightness Temperature Difference signal over southeast Arkansas. IFR Conditions are not occurring under that mid-level stratus deck, and IFR Probabilities are very low. Similarly, IFR Probabilities are small over Oklahoma and north-central Texas because the Rapid Refresh Model is not showing low-level saturation in those regions; IFR Probabilities cannot be large when low-level saturation is not indicated in the model.
Using both Satellite Data and Model Data accentuates the strengths of both. That’s the power of a fused data product.
GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm) and GOES-R IFR Probability fields computed with GOES-13 and Rapid Refresh Data, 0800 UTC 18 October. Plots of ceilings and surface visibilities are included (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-13 Brightness Temperature Difference Fields and GOES-13-based GOES-R IFR Probability fields, 1107 UTC on 6 October (Click to enlarge)
The toggle above between the GOES-R IFR Probability fields at 1107 UTC on 6 October, and the corresponding Brightness Temperature Difference field from GOES-13, is an example of the strength of the GOES-R IFR Probability field. By fusing Satellite Data with model (Rapid Refresh) estimates of low-level saturation, the Probability field is able to differentiate between regions where Brightness Temperature Difference fields are showing a signal but where widespread low-level fog is not occurring (Mississippi) from regions where Brightness Temperature Difference Fields show a signal and where IFR conditions are present (Louisiana and Texas). An IFR SIGMET was issued associated with the Fog over Louisiana and Texas.
GOES-R IFR Probability Fields, 0200-0700 UTC on 3 October 2016 (Click to enlarge)
Fog developed over portions of the Ohio River Valley from Indiana westward to the Mississippi River at Cairo IL on the morning of 3 October 2016. Dense Fog Advisories were issued by the National Weather Service Offices in St. Louis, Lincoln IL and Paducah between 3:30 and 4:15 CDT (0830 to 0915 UTC). A SIGMET was also issued. How effective was Satellite detection of this developing fog?
The brightness temperature difference product, below, shows hourly measures of water-based clouds, a detection that keys off the emissivity differences of water based clouds for 3.9 radiation (at which wavelength near-blackbody emission is not occurring) and 10.7 radaiation (at which wavelength near-blackbody emission is occurring). Significant changes to the brightness temperature difference field did not occur until after 0500 UTC. In addition, Brightness Temperature Difference fields overestimated the region of developing fog. In contrast, the GOES-R IFR Probability field, above, showed a more gradual increase from 0200 UTC onward, and the region of the strong signal was better confined to where dense fog developed. On this day, GOES-R IFR Probability fields were better for situational awareness, generating an earlier alert for forecasters to the potential for fog. In addition, the GOES-R IFR Probability fields better defined the region of hazardous ceilings and visibilities.
Brightness Temperature Difference Field (3.9 – 10.7) from 0100 to 0700 UTC on 3 October 2016 (Click the enlarge)
GOES-R IFR Probability fields, hourly from 0215 UTC through 1115 UTC on 28 September 2016 (Click to enlarge)
IFR and Low IFR Conditions developed over parts of Virginia and the Carolinas Piedmont Region during the morning of 28 September 2016. The screengrab below, from the Aviation Weather Center, shows the areal extent of the reduced visibilities and/or low ceilings. (The text of the IFR Sigmet is here.) Fog over southeastern Virginia is developing under multiple cloud decks associated with the convection near a front. IFR Probabiities in this region are determined by Rapid Refresh data that shows low-level saturation; the flat-looking field over that region is characteristic of model-only IFR Probability fields. Farther to the southwest, over western North Carolina, IFR Probabilities are determined by both satellite and model data; notice how pixelated the data are in that region.
Screengrab from the Aviation Weather Center at 1215 UTC on 28 September 2016 (Click to enlarge)
Suomi NPP overflew the eastern United States shortly after 0730 UTC, and the toggle below shows the Day Night Visible Band and the Brightness Temperature Difference field (11.45 – 3.74 ). Water-based clouds (yellow and orange in the enhancement used) are detected just to the west of cirrus and mixed-phase clouds (black in the enhancement used). The 0737 UTC IFR Probability field, at bottom, had model-data only as predictors in regions where Suomi NPP shows multiple cloud layers. Note also that the 1-km resolution of Suomi NPP is resolving the developing valley fogs in the Appalachian mountains of Ohio, West Virginia and Kentucky. There are only a few pixels in the IFR Probability field that are suggesting valley fog development — but note in the end of the animation at the top of this post that more valley pixels show IFR Probability signals. When GOES-R is flying, its superior (to GOES-13) 2-km resolution should mitigate this too-slow identification of valley fogs.
Suomi NPP Day Night Band Visible (0.70) and Brightness Temperature Difference (11.45 – 3.74) fields at 0736 UTC on 28 September 2016 (Click to enlarge)
GOES-R IFR Probability fields at 0737 UTC, and surface observations of ceilings and visibilities at 0800 UTC (Click to enlarge)
GOES-R Cloud Thickness Fields, 1130 UTC on 20 September 2016 (Click to enlarge)
GOES-R Cloud Thickness is created from a look-up table created from observations of 3.9 µm emissivity and sodar observations of cloud thickness off the west coast of the United States. The product is not computed during twilight conditions when rapid changes in reflected solar radiation (either increases around sunrise or decreases around sunset). The image above shows the GOES-R Cloud Thickness field over the midwest just before sunrise on 20 September 2016 (Radiation fog formed subsequent to late-afternoon and evening thunderstorms over Wisconsin and Illinois). This scatterplot relates the last pre-sunrise value to dissipation time. GOES-R Cloud thickness shows values over the Wisconsin River Valley in southwest Wisconsin, and over regions south of Military Ridge. Largest values — 1100 feet over Illinois and Iowa — suggest (from the scatterplot) a dissipation time of around 4 hours, which would be 1130 UTC (the time of the image) + 4 hours, or 1530 UTC. There is also a region of thick clouds on northwest Indiana on the shore of Lake Michigan. It’s these regions where you should expect large-scale fog/low clouds to dissipate last. The animation below shows that to be true. Fog over the river valleys is taking a bit longer to dissipate than expected, however. Note: navigation in the animation shows the effect of the loss of one star-tracker on GOES-13.
GOES-13 Visible (0.63 µm) animation, 1245-1515 UTC on 20 September 2016 (Click to enlarge)
The Day Night band on the VIIRS instrument on board Suomi NPP produces visible imagery at night that showed the regions of fog distinctly shortly after 0800 UTC on 20 September as shown below.
VIIRS Day/Night Band Visible (0.70 µm) Imagery from Suomi NPP at 0827 UTC on 20 September (Click to enlarge)
GOES-R IFR Probability Fields and surface reports of ceilings and visibilities, 0100-1000 UTC on 13 September 2016 (Click to enlarge)
High Pressure over the eastern United States allowed Radiation Fog to form over much of the southeast early on the morning of 13 September 2016. The GOES-R IFR Probability hourly animation, above, shows increasing probabilities of IFR conditions over much of North and South Carolina, with IFR conditions observed at many stations by sunrise (graphic from here). IFR Probabilities provided an earlier alert to the fog development (as such, it’s a good situational awareness tool) than was possible from the traditional brightness temperature difference field (see the 0400 UTC image below — click here for a much larger image) because of multiple cloud layers present over the Carolinas in the wake of departing showers. The enhancement for the brightness temperature difference field is such that clouds composed of water droplets are typically shaded orange or yellow. In the 0400 UTC brightness temperature difference field below (right), fog is not indicated over South Carolina.
GOES-R IFR Probability fields (left) and GOES-13 Brightness Temperature Difference Fields (right), both from 0400 UTC on 13 September 2016 (Click to enlarge)
GOES-R Cloud Thickness fields can be used to estimate fog dissipation time for radiation fog. This scatterplot shows a rough relationship between the last thickness field produced before twilight conditions and the dissipation time. That field is shown below — note that portions of eastern North Carolina have slipped into twilight conditions already by 1100 UTC. Maximum values over South Carolina are around 850 feet (near Greenville/Spartanburg), while those over North Carolina exceed 1200 (near Asheville). Fog dissipation should occur first over South Carolina, then over North Carolina.
GOES-R Cloud Thickness Field, 1100 UTC on 13 September 2016 (Click to enlarge)
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 Fields (Upper left), GOES-East Brightness Temperature Difference (3.9 – 10.7) (Upper Right), GOES-R Cloud Thickness (Lower Left) and GOES-East Water Vapor imagery (Lower Right), all at 1045 UTC on 18 August 2016. Surface observations of ceilings and visibilities at 1100 UTC are included in the upper right (Click to enlarge)
Dense Fog developed over southern Indiana on the morning of August 18 (and advisories were hoisted). The single image above demonstrates an advantage of GOES-R IFR Probability fields in determining the areal extent of fog: the traditional method of night-time fog detection from satellite fails in regions where cirrus clouds obscure the view of low clouds. That was the case over the Ohio River Valley where IFR conditions were occurring. GOES-R IFR Probability fields have a signal where high clouds exist in regions where Rapid Refresh model output shows low-level saturation, as over southwestern Indiana. Because satellite data cannot be used there to compute IFR Probabilities, the magnitude of the probability is smaller. Tailor your interpretation of the IFR Values based on the presence of high clouds. The presence of high clouds changes the character of the IFR Probability field, from a pixelated field where satellite data are present to a flatter field where only model data can be used.
GOES-R Cloud Thickness can be used to estimate fog dissipation time (using this scatterplot, where the thickness values are from the last pre-sunrise scene). That field, however, is only produced where the satellite has an unimpeded view of the low clouds (therefore, where cirrus clouds are present, as over the Ohio River Valley, Cloud Thickness is not produced). Note the line parallel to the terminator over eastern Ohio: GOES-R Cloud Thickness is not produced during twilight times around sunrise or sunset. This 1045 UTC image is the final one over Indiana before sunrise. Maximum thickness values are just over 1000 feet over southwest Indiana, suggesting a dissipation time of about three hours, that is, around 1345 UTC.
When GOES-R IFR Probability fields are governed solely by Rapid Refresh model output because of thick cloudiness (as was the case over Illinois on 15 August 2016), there can be changes in the field at the top of the hour that are related to changes in the Rapid Refresh model output — that is, changes in which hour Rapid Refresh Model is used. The toggle above shows the IFR Probability fields at 1045 UTC and 1100 UTC on 15 August. Both fields are characterized by smooth values that come with IFR Probability that is driven by Rapid Refresh model output, output that is smooth and not pixelated like satellite data. It’s pretty noticeable, however, that values increase (from ~39% to ~52%) in those 15 minutes. Why?
The image below shows Rapid Refresh Model Predictions of 1000-700 mb Relative Humidity at 1100 UTC from the 0800 UTC model run (that is, a 3-hour forecast, left) and from the 0900 UTC model run (that is, a 2-hour forecast, right). Relative Humidity Values from the 0800 UTC Run (interpolated to 1045) are used in the computation of IFR Probabilities at 1045 UTC; values from the 0900 UTC Run are used in the computation of IFR Probabilities at 1100 UTC. It’s not this relative humidity field (value from 1000-700 hPa) precisely that is used, but rather maximum values in the vertical. Certainly there are changes in the predicted low-level relative humidity field at 1100 UTC between the sequential model runs; it’s more likely that saturation is occurring in the later model run, and that greater likelihood of saturation is reflected in the change of IFR Probability from 1045 UTC (when 0800 UTC Rapid Refresh Model fields are used) to 1100 UTC (when 0900 UTC Rapid Refresh Model fields are used).
Rapid Refresh model predictions of 1000-700 mb Relative Humidity; 3-hour forecast from the 0800 UTC Rapid Refresh Model (left) and 2-hour forecast from the 0900 UTC Rapid Refresh Model (Right), both from 15 August 2016 (Click to enlarge)