Category Archives: Deep South

Dense Fog along the Florida Gulf Coast

GOES-R IFR Probability Fields, hourly from 0415-1107 UTC on 17 April 2017 (Click to enlarge)

Note: GOES-R IFR Probabilities are computed using Legacy GOES (GOES-13 and GOES-15) and Rapid Refresh model information; GOES-16 data will be incorporated into the IFR Probability algorithm in late 2017.

GOES-R IFR Probability fields, above, show increases in IFR Probability starting around midnight local time. The IFR Probability fields generally outline the regions where fog occurred (and which led to the issuance of dense fog advisories to the east of Mobile). How did the brightness temperature difference field capture this event? Brightness Temperature Difference fields have been used historically to identify regions of stratus.

GOES-13 Brightness Temperature Difference fields (3.9 µm – 10.7 µm), hourly from 0415-1107 UTC on 17 April 2017 (Click to enlarge)

The brightness temperature difference field, above, shows a slow increase in negative values (negative because the brightness temperature computed from emitted 3.9 µm radiation is cooler than that computed from emitted 10.7 µm radiation over clouds composed of water because such clouds do not emit 3.9 µm radiation as a blackbody), but careful inspection of the field shows IFR conditions in regions outside the largest signal (highlighted in this enhancement in yellow). This occurs mostly were cirrus clouds are indicated (represented as dark regions in the enhancement, over central Mississippi, for example). In such regions, the IFR Probability fields can maintain a signal of IFR conditions because low-level saturation is predicted by the Rapid Refresh Model.

This fused product combines the strengths of both inputs: Satellite detection of low clouds, and model prediction of low-level saturation.

As the sun rises, the amount of reflected solar radiation at 3.9 µm increases, and the sign of the brightness temperature difference changes from negative at night over water clouds to positive. This toggle below shows the brightness temperature difference at 1107 and 1145 UTC. The decrease in signal does not necessarily mean fog is decreasing.

GOES-13 Brightness Temperature Difference fields (3.9 µm – 10.7 µm) at 1107 UTC and 1145 UTC on 17 April 2017 (Click to enlarge)

A toggle of the IFR Probability and the Brightness Temperature Difference at 1145 UTC, below, shows that the IFR Probability fields can maintain a useful signal during the time of rapid changes in reflected solar radiation with a wavelength of 3.9 µm.

GOES-R IFR Probability and GOES-13 Brightness Temperature Difference fields (3.9 µm – 10.7 µm) at 1145 UTC on 17 April 2017 (Click to enlarge)

Dense Fog in Louisiana

GOES-R IFR Probabilities computed using GOES-13 and Rapid Refresh Data, 0400-1000 UTC on 20 March 2017 (Click to enlarge)

Note: GOES-R FLS products are currently derived from GOES-13 and GOES-15 data. A GOES-16 version of the GOES-R FLS products will not be available until later in 2017.

Dense Fog advisories were issued for much of central and southern Louisiana (screenshot taken from this site) on Monday morning, 20 March 2017; IFR and Low IFR conditions were widespread (screenshot from this site). The animation above shows the development of IFR Probabilities in concert with the development of IFR conditions. A strength of the IFR Probability field on this day was that it indicated the possibility of fog development some time before satellite brightness temperature difference fields. Low-level saturation was (correctly) occurring in the Rapid Refresh model, and that helped increase IFR Probability values.

Consider the toggle below, showing, the IFR Probability and Brightness Temperature Difference fields at 0500 UTC. The Brightness Temperature Difference field over coastal Louisiana at 0500 shows little indication of fog development. An animation brightness temperature difference fields that matches the 0400-1000 UTC timeframe shown above for IFR Probabilities is below. Although a strong brightness temperature difference signal is present in Texas, it does take some time for the signal to develop over Louisiana. IFR Probabilities were more helpful for situational awareness on this day.

IFR Probabilities and GOES-13 Brightness Temperature Difference Fields (3.9 µm – 10.7 µm), 0500 UTC on 20 March 2017 (Click to enlarge)

GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm), 0400-1000 UTC on 20 March 2017 (Click to enlarge)

Dense Fog Advisories along the western Gulf Coast

GOES-R IFR Probability fields, hourly from 0145-1345 UTC on 08 February 2017, along with surface observations of visibility and ceiling height (Click to enlarge)

Dense Fog developed along the western Gulf Coast early on the morning of 8 February 2017, leading to the issuance of Dense Fog Advisories (graphic from this site) and of IFR Conditions (graphic from this site). The animation above shows the expansion of the field of high IFR Probabilities northwestward from the Gulf of Mexico starting at 0145 UTC. IFR Conditions reported in concert with the arrival of higher IFR probabilities. Relatively high IFR Probability values also develop over northern MIssissippi and Alabama.

The traditional method of detecting low clouds at night, the brightness temperature difference field computed using brightness temperatures at 3.9 µm and 10.7 µm detects water-based clouds because of the different emissivity properties of the water-based cloud at those two wavelengths. If ice clouds (at high levels) or mixed phase clouds (at mid-levels) exist, however, the satellite cannot view the low clouds. This was the case on 8 February over northern Mississippi and northern Alabama, and also occasionally over Louisiana and Texas. The toggle below from 0945 UTC, between the GOES-R IFR Probability field and the Brightness Temperature Difference field, shows several regions where Brightness Temperature Difference field enhancements do not indicate low clouds (over northwestern Mississippi, for example); in these regions, IFR Probabilities are nevertheless large because Rapid Refresh model data shows saturation in the lowest 1000 feet of the atmosphere, strongly suggestive of high IFR Probabilities, and that predictor serves to increase the value of the IFR Probability. The animation of the Brightness Temperature Difference fields is at the bottom of this blog post; compare it to the IFR Probability fields at the top. The IFR Probability algorithm capably fills in regions under high clouds/mid-level clouds where the satellite cannot view low clouds. It gives a more consistent (and more accurate) depiction of the spread of the low clouds/fog.

Brightness Temperature Difference (3.9 µm – 10.7 µm) and GOES-R IFR probability at 0945 UTC on 8 February 2017 (Click to enlarge)

Another difficulty with Brightness Temperature Difference fields occurs around sunrise when increasing amounts of reflected solar radiation at 3.9 µm cause a sign change in the brightness temperature difference field (reflected 3.9 µm radiation increases as the sun rises and the computed brightness temperature therefore changes because reflected solar radiation at 10.7 µm is minimal; emissivity-related differences between the two bands are overwhelmed). The toggle below compares 1245 UTC and 1345 UTC Brightness Temperature Values.

Brightness Temperature Difference (3.9 µm – 10.7 µm) at 1245 and 1345 UTC on 8 February 2017 (Click to enlarge). Decreases in the brightness temperature differences occur at 1345 UTC because of increases in reflected solar radiation at 3.9 µm.

Brightness Temperature Difference (3.9 µm – 10.7 µm), 0145 – 1345 UTC on 8 February 2017, along with surface observations of ceilings and visibility (Click to enlarge)

IFR Conditions across the Deep South

GOES-R IFR Probability computed with GOES-13 and Rapid Refresh Model Data, hourly from 0215 through 1415 UTC on 20 December 2016 (Click to enlarge)

Widespread IFR Conditions developed across Mississippi, Alabama, Georgia and neighboring states on Tuesday morning 20 December, as evidenced by the Aviation Weather Center website screen grab at the bottom. GOES-R IFR Probabilities captured the evolution of the low ceilings and reduced visibilities. In particular, note in the animation above the westward progress of the higher IFR probabilities through Mississippi; IFR conditions develop at, for example, Jackson (KJAN), Greenwood (KGWO) and Oxford (KUOX) as the high probabilities move over the station. Its motion was useful as a forecast tool on this morning.

The GOES-R IFR Probability field has noticeable stripes in it at the end of the animation. This occurs because high clouds have overspread the low stratus/fog. When that happens, satellite data can no longer be used as a predictor in the IFR Probability algorithm because the satellite can no longer view the low clouds; Rapid Refresh data alone are driving the values. The toggle between the brightness temperature difference field (3.9 µm – 10.7 µm) and the IFR Probability field, below, from 1115 UTC on 20 December, shows the effect. Where fog/stratus are present (yellow in the enhancement used for the brightness temperature difference field), IFR Probability values are larger because satellite and model data can be used to compute IFR Probability. Where high clouds are present (dark grey in the brightness temperature difference enhancement), only Rapid Refresh data can be used.

GOES-R IFR Probability and GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm) fields, 1115 UTC on 20 December 2016 (Click to enlarge)

Aviation Weather Center website screengrab, 1443 UTC on 20 December 2016 (Click to enlarge)

Dense Fog in Georgia and Florida

GOES-R IFR Probability Fields, 0000 – 1300 UTC on 25 November 2016 (Click to enlarge)

Light winds and a long November night allowed radiation fog formation over much of the deep south early on 25 November 2016. (1200 UTC Surface analysis is here). The Aviation Weather Center Website indicated widespread IFR Conditions, below, over the south, with the sigmet suggesting improving visibilities after 1400 UTC.

The animation above shows the evolution of the GOES-R IFR Probability fields from just after sunset to just after sunrise. There is a good spatial match between observed IFR conditions and the developing field. IFR Probability can thus be a good situational awareness tool, identifying regions where IFR Conditions exist, or may be developing presently.

Screenshot of Aviation Weather Center Front Page, 1405 UTC on 25 November (Click to enlarge)

Did the GOES-13 Brightness Temperature Difference Field identify the fields? The animation below, from 0200-1300 UTC, shows a widespread signal that shows no distinguishable correlation with observed IFR conditions. Note also how the rising sun at the end of the animation changes the difference field as more and more reflected solar radiation with a wavelength of 3.9 µm is present. In addition, high clouds that move from the west (starting at 0400 UTC over Louisiana) prevent the satellite from viewing low clouds in regions where IFR conditions exist.

GOES-13 Brightness Temperature Difference field (3.9 µm – 10.7 µm), 0200-1300 UTC on 25 November 2016 (Click to enlarge)

The high clouds that prevent satellite detection of low clouds, as for example at 1100 UTC over parts of Alabama, cause a noticeable change in the IFR Probability fields, as shown in the toggle below. Values over the central part of the Florida panhandle are suppressed, and the field itself has a flatter character (compared to the pixelated field over southern Georgia, for example, where high clouds are not present). Even though high clouds prevent the satellite from providing useful information about low clouds in that region, GOES-R IFR Probability fields can provide useful information because of the fused nature of the product: Rapid Refresh information adds information about low-level saturation there, so IFR Probability values are large. In contrast, over southern Florida — near Tampa, for example, Rapid Refresh data does not show saturation, and IFR Probabiities are minimized even through the satellite data has a strong signal — caused by mid-level stratus. Soundings from Tampa and from Cape Kennedy suggest the saturated layer is around 800 mb.

GOES-R IFR Probability fields and GOES-13 Brightness Temperature Difference Fields, 1100 UTC on 25 November 2016 (Click to enlarge)

GOES-R Cloud Thickness, below, related 3.9 µm emissivity to cloud thickness via a look-up table that was generated using GOES-West Observations of marine stratus and sodar observations of cloud thickness. The last pre-sunrise thickness field, below, is related to dissipation time via this scatterplot. The largest values in the scene below are around 1000 feet, which value suggests a dissipation time of about 3 hours, or at 1445 UTC.

GOES-R Cloud Thickness Field, 1145 UTC on 25 November 2016 (Click to enlarge)

IFR Conditions over the Deep South

GOES-R IFR Probability Fields, 0100-0500 UTC on 31 October 2016 (Click to enlarge)

GOES-13 Brightness Temperature Difference Fields (3.9 µm – 10.7 µm), 0100-0500 UTC on 31 October 2016 (Click to enlarge)

Compare the two animation from 0100-0500 above, showing GOES-R IFR Probability fields (top) and GOES-13 Brightness Temperature Difference fields (bottom) from shortly after sunset on 30 October 2016 until Midnight. IFR Probability shows very little signal at first, and IFR conditions are rare (Jack Edwards Airport near Gulf Shores AL report IFR conditions). IFR Probabilities increase slowly in the next 4 hours, especially in regions where IFR conditions develop. In contrast, the trend in the Brightness Temperature Difference field is a slow decrease in areal coverage with little spatial correlation between a strong signal and IFR reports. These animations demonstrate a strength of IFR Probabilities: By combining satellite information with Rapid Refresh predictions of low-level saturation, a better estimate of visibility restrictions can be created.

Subsequent to 0500 UTC, in the animations shown below, IFR Probability fields expanded as IFR conditions developed over western Louisiana and southern/eastern Texas; a strong signal develops in the brightness temperature difference field in these regions as well. Note the lack of signal in the GOES-R IFR Probability field over Alabama and Mississippi where Brightness Temperature Difference fields show a consistent signal (and where IFR Conditions are not present). Brightness Temperature Difference signals over those states may be related to changes in emissivity properties that occur during severe drought, as discussed here.

GOES-R IFR Probability fields, 0500-1215 UTC on 31 October 2016 (Click to enlarge)

GOES-13 Brightness Temperature Difference Fields (3.9 µm – 10.7 µm), 0500-1215 UTC on 31 October 2016

GOES-R Cloud Thickness relates future dissipation of fog to present observations of Cloud Thickness. The last pre-sunrise GOES-R Cloud Thickness field is related to dissipation time in this scatterplot. (GOES-R Cloud Thickness is not computed during twilight times surrounding sunrise and sunset) The animation below shows the thickest clouds over south-central Texas; fog over Louisiana and coastal Texas is comparatively thin. Dissipation should occur last over interior Texas.

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GOES-R Cloud thickness every half hour from 1145-1245 UTC on 31 October 2016 (click to enlarge)

IFR probabilities were noted by the Aviation Weather Center, and Dense Fog Advisories were issued along the Gulf Coast for this case.

IFR Probability Fields let you peek beneath the Cirrus

GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm) fields, hourly from 0215-1215 UTC on 27 October (Click to enlarge)

If you rely on satellite data alone to anticipate the development of IFR conditions — fog, low ceilings, and reduced visibilities — then the presence of widespread cirrus, shown here with the GOES-13 6.5 µm image, makes situational awareness difficult. At a glance, can you tell in the animation of brightness temperature difference, above, hourly from 0215 through 1215 UTC, where IFR Conditions are occurring? The widespread cirrus, present in the enhancement as dark grey and black, prevents the satellite from viewing any fog development, hence making this brightness temperature difference field, traditionally used to detect the development of fog and low stratus, unsuitable for large-scale situational awareness.

GOES-R IFR Probability fuses satellite data with Rapid Refresh Model output and allows a product that in essence peeks beneath the cirrus because near-surface saturation predicted in the Rapid Refresh Model allows the IFR Probability product to have a strong signal where fog might be developing. Consider the animation below, that covers the same spatial and temporal domain as the brightness temperature difference animation above. IFR Probability increases over inland southeast Georgia in concert with the development of low ceilings/reduced visibilities. It gave a few hours alert to the possibility that IFR conditions would be developing. Note in the animation below that the 1215 UTC image includes IFR Probabilities computed using daytime predictors and nighttime predictors. There is therefore a discontinuity in the field values over central Georgia at 1215 UTC, the end of the animation.

Compare the animation below to the one above. Which yields better situational awareness for the developing fog field?

GOES-R IFR Probability Fields, hourly from 0215 through 1215 UTC on 27 October (Click to enlarge)

The Aviation Weather Center plot (below) highlights the presence of an IFR SIGMET over the region at 1324 UTC on 27 October.

Aviation Weather Center plot showing MVFR, IFR and LIFR stations over Georgia, along with an IFR Sigmet at 1324 UTC 27 October 2016 (Click to enlarge)

IFR Probability Screens out mid-level Stratus

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)

IFR Probabilities over Louisiana

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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.

Fog over the lower Ohio River Valley

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 Fog Product Examples

Fog detection fusing GOES, Terra/Aqua or Suomi/NPP Satellite data with Model output