Fast-moving Fog over northeast Montana

GOES-R IFR Probability fields computed with GOES-13 and Rapid Refresh Data, 1400-1500 UTC on 24 March 2017 (Click to enlarge)

Rains over Montana earlier this month (data from this site) (along with snowmelt) caused substantial flooding on Big Muddy Creek in the extreme northeast part of the state. Saturated soils in that region have increased the likelihood of fog, and fog was indicated by IFR Probability in that region on the morning of 24 March as shown above.

GOES-16 Visible Imagery showed the fog speedily moving down Big Muddy Creek. An animation using GOES-13 Visible imagery (0.64 µm) is shown below. The GOES-16 CONUS cadence is every five minutes; it is every 15 minutes with GOES-13, except when Full Disks are being scanned (14:45 UTC) or when housekeeping is occurring (15:30 UTC).

GOES-13 and GOES-16 visible data both show quick movement of the fog. For this case, it was harder to judge motion from the IFR Probability fields. This could be related to Infrared and model resolution; the creek valley might be too narrow for the satellite infrared data and for the model.

GOES-13 VIsible (0.64 µm) imagery, 1415-1615 UTC. Sheridan County Montana is outlined in the first image. Fog advancing down Big Muddy Creek is apparent

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)

Marine Stratus over southern California

GOES-R IFR Probability, hourly from 0300 to 1300 UTC, 13 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.

IFR Conditions developed early on March 13th 2017 as Marine Stratus moved over the southern California. This is a typical occurrence that nevertheless requires timely monitoring because of the impact of fog on transportation. The Brightness Temperature Difference fields, below, show the tops of the clouds. Water clouds do not emit 3.9 µm radiation as a blackbody, but they do emit 10.7 µm radiation nearly as a blackbody. Result: Inferred brightness temperatures (a computation that assumes blackbody emission from the source) are cooler and 3.9 µm than at 10.7 µm, and a difference field will highlight clouds made up of water droplets, i.e., stratus. If the stratus is at the surface, fog is a result. Low IFR Probability fields, above, include surface information in the form of low-level relative humidity fields from the Rapid Refresh model. Only where saturation near the surface is indicated by the model will Low IFR Probabilities be large.

In the animation above, IFR conditions develop along the coast and penetrate inland as Low IFR Probabilities increase.  Probabilities are decreasing by 1300 UTC.

IFR and Low IFR Conditions are shown in this plot from the Aviation Weather CenterThis toggle, from 0300 UTC, shows both Low IFR Probability and IFR Probability.  As might be expected, IFR Probabilities exceed Low IFR Probabilities

GOES-15 Brightness Temperature Difference (3.9 µm – 10.7 µm) Fields, hourly from 0300 to 1300 UTC on 13 March 2017 (Click to enlarge)

GOES-16 Data are Flowing

GOES-R IFR Probability that uses present GOES (GOES-13 and GOES-15) data in the computation of GOES-R IFR Probability fields was designed in anticipation of GOES-16 data that are now flowing to National Weather Service Forecast offices. Click here for a description of the Brightness Temperature Difference field values that are available now in AWIPS from GOES-16.

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 in Ohio, Indiana and Illinois

Toggle between 1100 UTC GOES-R IFR Probability fields and GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm) fields, with surface observations of ceilings and observations. (Click to enlarge)

Dense Fog developed over central/southern Ohio, Indiana and Illinois on the morning of 20 February 2017 (Screen shot from here; IFR Depiction from here). The toggle above includes the GOES-R IFR Probability fields; large values of IFR Probability overspread the region of low ceilings and visibilities. In contrast, high clouds (dark grey in the enhancement used) are preventing the Brightness Temperature Difference field from articulating where the fog/low ceilings might be occurring. Because satellite data cannot be used as a predictor at 1100 UTC, the character of the IFR Probability field is mostly uniform, lacking the pixelation that occurs when low clouds can be viewed from the satellite (as over southwestern Pennsylvania, West Virginia, central Kentucky, parts of central Illinois, and elsewhere).

High clouds have not moved into Ohio and Indiana at 0500 UTC on 20 February as the fog was developing (they are present over Illinois, however). The toggle below, from that time, shows low probabilities of IFR conditions over Ohio, and only a few reports of IFR conditions, mostly over central and southern Ohio.

Toggle between 0500 UTC GOES-R IFR Probability fields and GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm) fields, with surface observations of ceilings and observations. (Click to enlarge)

Toggle between 0700 UTC GOES-R IFR Probability fields and GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm) fields, with surface observations of ceilings and observations. (Click to enlarge)

By 0700 UTC (above), IFR conditions are becoming more widespread as IFR Probabilities increase.  The dark regions in the Brightness Temperature Difference fields over Wisconsin and Lower Michigan and surrounding regions show the advance of high clouds.  By 1000 UTC, those clouds have overspread Ohio and Indiana, and the brightness temperature difference field loses utility as far as low-cloud detection goes.  Because the IFR Probability fields incorporate low-level saturation information from the Rapid Refresh Model, however, IFR Probability fields can continue to provide a useful signal when high clouds are present or move in.

Toggle between 1000 UTC GOES-R IFR Probability fields and GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm) fields, with surface observations of ceilings and observations. (Click to enlarge)

IFR Conditions over Maine

GOES-R IFR Probability and with surface observations of ceilings and visibilities, 1045 UTC on 13 February 2017 (Click to enlarge)

A strong storm off the East Coast of the United States produced a variety of winter weather over Maine on 13 February 2017, including Blizzard conditions. Although ceilings and visibilities above show IFR or near-IFR conditions at 1045 UTC, GOES-R IFR probabilities over Maine are small (less than 20%). Why?

The image below from this site shows Cloud Type, Low-Level Saturation, IFR Probability, and the Nighttime Microphysics.  Both Ice clouds and falling snow are widespread over Maine. GOES-R IFR Probabilities typically assume saturation with respect to water.   The Gray, ME morning sounding shows maximum RH (with respect to water) at only 94% (Link).  Assuming saturation with respect to water rather than with respect to ice may be a source of error that will have to be investigated in the future.

Note that after sunrise, IFR Probabilities increased over Maine to values between 30 and 45% (Link).

Satellite-derived Cloud Type (upper left), Maximum Low-Level Relative Humidity in the Rapid Refresh (upper right), GOES-R IFR Probability (lower left) and Nighttime microphysics (lower right), all from 1045 UTC on 13 February (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)

Fog over Kansas

GOES-R IFR Probability fields, 1345 UTC on 6 February 2017, along with 1400 UTC surface observations of ceilings and visibilities (Click to enlarge)

Dense Fog Advisories were issued for much of central Kansas early on 6 February 2017.  This was an example of how GOES-R IFR Probability fields (above) can help identify regions of dense fog when high clouds prevent satellite detection of low clouds.  The brightness temperature difference field, below, shows high clouds over much of Kansas — it’s therefore very difficult to relate cloud signatures to obstructions to visibility near the surface.  In contrast, IFR Probability fields, above, use saturation in the lowest part of the Rapid Refresh Model and capably highlight regions where fog/low ceilings are occurring.

Brightness Temperature DIfference field (3.9µm – 10.7µm) at 1345 UTC on 6 February 2017, along with surface observations of ceilings and visibility (Click to enlarge)

Ice Fog in Kansas City

GOES-R IFR Probabilities, hourly from 0115 through 1815 UTC, and surface observations of ceilings and visibilities, on 18 January 2017 (Click to enlarge)

Ice Fog developed over Kansas City during the early morning hours of 18 January 2017, with accidents that snarled traffic (tweeted image courtesy @DrWxologist Chad Gravelle)  starting before sunrise and continuing through the morning rush hour  (Screenshot of News link from here).    Dense Fog Advisories were issued.  The animation above, of GOES-R IFR Probability fields, shows the slow westward progression of the Fog/Low Clouds into the Kansas City Metro area shortly after 4 AM CST.  High IFR Probabilities persist through 1800 UTC and diminished shortly thereafter.

During this case, an absence of mid-level and high clouds allowed IFR Probabilities to reach very large values.  The toggle below shows Brightness Temperature Difference fields (3.9 – 10.7) and GOES-R IFR Probabilities at 1115 UTC.  Low clouds cover Missouri except for the region over the Missouri Bootheel.  Note that the western edge of the satellite-detected low clouds is slightly to the east of the western edge of the IFR Probability in this case.  Model data are suggesting that low-level saturation is occurring in those regions (over far southwest Iowa, for example) although satellite data were not yet showing a strong signal.  Observations show IFR conditions (at Clarinda, Iowa, for example, where freezing fog is reported with 200-foot ceilings and 1/4-mile visibility).

Dense Fog over the Carolinas

GOES-13 Brightness Temperature Difference (3.9 µm – 10.7 µm), GOES-R IFR Probability and GOES-R Cloud Thickness at 1115 UTC on 17 January 2017 (Click the enlarge)

Dense Fog Advisories (National Weather Service Website) and IFR SIGMETs (Aviation Weather website) were issued early in the morning for dense fog over the southeastern United States.  The toggle above from 1115 UTC on 17 January shows the Brightness Temperature Difference field (3.9 µm – 10.7 µm), the GOES-R IFR Probability Field, and the GOES-R Cloud Thickness fields associated with this dense fog event.  Note the presence of high clouds over northern South Carolina and western North Carolina — the dark region in the Brightness Temperature Difference enhancement — prevents the brightness temperature difference field from highlighting that region of reduced ceilings/visibilities.  The GOES-R Cloud Thickness field is not computed under cirrus either, as it relates 3.9 µm emissivity of water-based clouds to cloud thickness (based on a look-up table generated using data from a SODAR off the West Coast of the United States).  If cirrus blocks the view, then, neither the Brightness Temperature Difference field nor the GOES-R Cloud Thickness field can give useful information about low clouds.

In contrast, the GOES-R IFR Probability field does give useful information in regions where cirrus clouds (and low clouds/fog) are present — because Rapid Refresh information about the lower troposphere can be used.  IFR Probability values will be smaller in those regions because satellite predictors are unavailable, and the Probability incorporates both predictors from satellites and from Rapid Refresh model output — if the satellite predictors are missing because of cirrus, the IFR Probability values will be affected. Despite the smaller values, however, the IFR Probability fields in regions of cirrus are giving useful information for this event.

GOES-R Cloud thickness fields can be used to estimate Fog dissipation using the last GOES-R Cloud Thickness field produced before twilight conditions at sunrise (shown below for this case). (GOES-R Cloud Thickness is not computed during twilight conditions because of rapidly changing 3.9 µm emissivity related to the reflected solar radiation as the sun rises, or as it sets). This scatterplot gives the relationship between thickness and dissipation time after the Cloud Thickness time stamp (1215 UTC in this case).  In this case, the thickest fog is near Athens GA;  the algorithm predicts that clearing should happen there last, at about 1515 UTC.

GOES-R Cloud Thickness, 1215 UTC on 17 January 2017 (Click to enlarge)