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)

Widespread IFR Conditions over the Plains

GOES-R IFR Probability Fields, hourly from 0115-1315 UTC (Click to enlarge)

A cyclone over the southern Plains, in addition to causing severe weather over Texas on 15 January also generated widespread IFR Conditions over the southern Plains, as shown below in screengrabs from the Aviation Weather Center and from the National Weather Service. An overnight Water Vapor image (here) testifies to the ubiquitous presence of high clouds over the Plains; in such cases with widespread high clouds, low-cloud detection by satellite is a big problem. A strength of the GOES-R IFR Probability field is that it is a fused data product, incorporating both satellite information (not particularly useful for much of the overnight hours on 15-16 January) and Rapid Refresh model data that can be used to discern conditions near the surface. When the Rapid Refresh model suggests saturation is occurring near the surface (in, say, the lowest 1000 feet of the model atmosphere), IFR Probabilities will be large. They won’t be as large as they might be if both satellite and model data suggest low clouds are present, but useful information emerges in the IFR Probability fields, above, where the Rapid Refresh is predicting low-level saturation. IFR Probabilities are large over much of the southern Plains where IFR conditions are observed. This is the region where the color enhancement is orange.

The low pressure system develops such that high clouds diminish over Texas and Oklahoma. When that happens, the IFR Probability fields change in two ways. First, values increase because satellite data and model data can be used as predictors. When only model data can be used, IFR Probability fields will have smaller values. Secondly, the character of the IFR Probability field takes on a more pixelated appearance because the satellite data values will vary from pixel to pixel. In contrast, when only model data can drive the IFR Probability field (for example, over Kansas at the beginning of the animation), the IFR Probability fields vary quite slowly from pixel to pixel in part because of model smoothing.

Screen Capture from Aviation Weather Center (left, showing widespread IFR Conditions) and from Weather.Gov (right, showing Dense Fog Advisories in grey) (Click to enlarge)

The toggle below includes sampling over Abilene, TX (KABI), a station at the edge of the IFR Probability field. IFR Probabilities are relatively constant at ~40% for the two hours shown, but station conditions change from IFR to VFR. IFR Probabilities at Abilene become quite small by 1315 UTC, at the end of the animation above.

GOES-R IFR Probability at 1015 and 1215 UTC on 16 January 2017. Station conditions at KABI are indicated by the sample probe (Click to enlarge)

Stratus over Texas

GOES-13 Visible (0.64 µm) Imagery, 1945 UTC on 6 January 2017 and surface observations of ceilings and visibilities (click to enlarge)

Visible imagery over Texas shows an extensive stratus deck blanketing the southern and eastern portions of the state.  Can you tell at a glance — without looking at the observations — if the stratus is extending to the surface?  The animation below shows how GOES-R IFR Probabilities describe the scene, with highest IFR Probabilities offshore (where dense fog is observed over the warm water).  Higher Probabilities also hug the high terrain of eastern Mexico, where IFR conditions are also reported (at Monclova, ID MMMV, where a 500-foot ceiling and 3-mile visibility is reported).  The toggle below cycles through the visible and GOES-R IFR Probability fields and also includes terrain.

GOES-R IFR Probability provides useful situational awareness information during the daytime as well as at night.

GOES-13 Visible (0.64 µm) Imagery, 1945 UTC on 6 January 2017 and surface observations of ceilings and visibilities, and with surface analysis superimposed, as well as GOES-R IFR Probabilities (1945 UTC) and Terrain (click to enlarge)

Persistent IFR Conditions over Kansas

GOES-R IFR Probability fields, 0400-1700 UTC on 2 January 2017 (Click to enlarge)

Late in the morning on Monday 2 January 2017, the weather.gov website shows Dense Fog Advisories persisting in parts of Kansas and Nebraska.  The animation above shows GOES-R IFR Probabilities from 0400 through 1700 UTC on the 2nd. High IFR Probabilities show excellent correspondence with very low ceilings and reduced visibilities. Note, for example, the sharp demarcation at 1700 UTC between IFR conditions (and large IFR Probabilities) and VFR/MVFR conditions (and very low IFR Probabilities) over northwestern Kansas/east central Colorado.

In the animation above, large parts of central Kansas have IFR Probabilities that are uniform, and around 52% (indicated by the mustard orange color). The IFR Probability field has this character at that time — and later in the animation over much of eastern Kansas and Missouri/Iowa — because of high clouds that are present. When high clouds prevent the satellite from viewing low clouds, model data in the form of Rapid Refresh estimates of low-level saturation are the driving force behind the IFR Probability value. The animation below of Brightness Temperature Difference fields shows the characteristic dark streak that in the enhancement used represents high clouds at night. High clouds then spread over Missouri and Iowa during the day.

GOES-13 Brightness Temperature Difference fields (3.9 µm – 10.7 µm), 0400-1700 UTC on 2 January 2017 (Click to enlarge)

GOES-R Cloud Thickness can be used in cases of radiation fog to estimate dissipation time, using the value just before sunrise, here, and this scatterplot. Low clouds on 2 January however were synoptically forced so it would be inappropriate to expect the GOES-R Cloud Thickness field to estimate dissipation times correctly.

Dense Fog in Oregon

GOES-R IFR Probabilities computed with GOES-15 and Rapid Refresh Data, hourly from 0300 through 1400 UTC on 21 December 2016 (Click to enlarge)

Dense Fog developed in the Willamette Valley of western Oregon during the early morning hours of 21 December 2016.  How did GOES-R IFR Probability fields and GOES-15 Brightness Temperature Difference (3.9 µm – 10.7 µm) Fields diagnose this event that led to the issuance of Dense Fog Advisories? The hourly GOES-R IFR Probability animation, above, shows increasing probabilities in the Willamette Valley, starting around Eugene (KEUG) and spreading northward until high probabilities cover the valley by 1400 UTC. IFR Conditions are first reported near Eugene, then through the entire valley by 1400 UTC. Widespread high IFR Probability values are not present elsewhere over Oregon (although they do exist over Washington State, where IFR conditions were also observed).

The Brightness Temperature Difference field (3.9 µm – 10.7 µm), below, shows a different distribution. Early in the animation a strong signal is apparent over much of northern Oregon, and also over the Pacific Ocean. Rapid Refresh output on low-level saturation is used in the GOES-R IFR probability algorithm to screen out regions where stratus that is detected by the satellite likely is not extending down to the surface — over the ocean, for example (coastal sites do not show IFR Conditions), or over much of eastern Oregon/Washington.   Brightness Temperature Difference fields do eventually highlight the presence of fog in the Willamette Valley, but considerable regions outside the valley have a strong return and no indication of IFR conditions.

GOES-15 Brightness Temperature Difference (3.9 µm – 10.7 µm) fields, 0300-1300 on 21 December 2016 (Click to enlarge)

GOES-R IFR Probability fields will frequently (and correctly) screen out regions of strong returns in the Brightness Temperature Difference fields that do not correspond to surface obscuration of visibility and/or low ceilings.

It is possible to alter the Brightness Temperature Difference Colormap, as below (animation courtesy Mike Stavish, SOO at Medford) to better highlight regions of fog in this case.  Note in this enhancement the cirrus clouds appear white, rather than dark, as well.

GOES-15 Brightness Temperature Difference  (3.9 µm – 10.7 µm) Fields, hourly from 0800 to 1400 UTC on 21 December 2016 (Click to enlarge)

The toggle below shows two color enhancements at 1200 UTC: the default version with many orange pixels, and an altered version that shows fewer pixels, mostly in regions where fog is present. A similar toggle for 0400 UTC is here.

Brightness Temperature Difference (3.9 µm – 10.7 µm) fields at 1200 UTC with two different enhancements. (Click to enlarge)