Category Archives: GOES-16

Dense Fog over Missouri and over Alabama

GOES-R IFR Probability Fields, Hourly from 0215-1315 UTC on 19 September 2017 (Click to enlarge)

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

Dense fog developed over Missouri on Tuesday 19 September and Dense Fog Advisories were issued. The animation above shows the hourly development of GOES-R IFR Probability fields; values increased from northern Missouri to southern Missouri as dense fog developed, first north of I-70, then south into the rest of the state. The morning of 19 September was mostly devoid of mid-level and high-level clouds over Missouri (exception: west-central Missouri starting after 0900 UTC), and that kind of night means that traditional methods of fog detection work well. The brightness temperature difference field between the shortwave Infrared and the Longwave Infrared (3.9 µm and 10.3 µm on GOES-16, 3.9 µm and 10.7 µm on GOES-13) shows the fog development.

Note that the IFR Probability field, above, does not show fog dissipating around sunrise. That’s in contrast to the Brightness Temperature Difference field below. As the sun rises, the amount of solar radiation at 3.9 µm that is reflected off the clouds increases; this changes the brightness temperature difference from positive (cyan in the color enhancement shown) to negative (grey or black in the enhancement shown).

GOES-16 has better spatial resolution than GOES-13; thus, the small valley fogs that can develop in the rugged (ish) terrain of southern Missouri are resolved in GOES-16, but not in GOES-13. When GOES-R IFR Probability is created using GOES-16 data (slated to begin in late 2017), the resolution improvements in GOES-16 will migrate to IFR Probability fields.

GOES-16 data posted on this page are preliminary, non-operational and are undergoing testing.

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), hourly from 0412 to 1112 UTC on 19 September (Click to enlarge)


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On 20 September, Dense Fog developed over Tennessee and Alabama, leading to the issuance of Dense Fog Advisories. The GOES-R IFR Probability field, below, shows good agreement between high probabilities and reduced ceilings/visibilities.

GOES-R IFR Probability Fields, Hourly from 0415-1315 UTC on 20 September 2017 (Click to enlarge)

As on the 19th over Missouri, top, this was a night with relatively few middle- and upper-level cloud decks. On such nights, the GOES-16 Brightness Temperature Difference field can capably identify regions of stratus (it’s up to a human to decide if the stratus deck extends to the surface; on this night, much of the stratus did). The 2-hour animation of Brightness Temperature Difference, below, highlights two particular strengths of GOES-16: Better spatial resolution that allows small valleys to be sampled correctly, and good temporal resolution (every 5 minutes vs. every 15 minutes for GOES-13) that allows superior monitoring of the cloud evolution with time. Note that the rising sun is eroding the GOES-16 Brightness Temperature Difference signal by the end of the animation below.

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), hourly from 1002 to 1202 UTC on 20 September (Click to enlarge)

The Brightness Temperature Difference field (10.3 µm – 3.9 µm) is a key component to the Nighttime Microphysics Red/Green/Blue Composite. As the toggle below shows, the Brightness Temperature Difference field overwhelmingly controls the region identified by the RGB as one with a potential for fog.

Fog over southwest Lower Michigan

GOES-R IFR Probability Fields, 0330-1430 UTC on 14 September 2017 (Click to animate)

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 (From this site, but also available via LDM feed in AWIPS), above, show the development of dense for over Lower Michigan, leading to the issuance of advisories. IFR Probabilities on this morning remained fairly low over the relatively warm late Summer waters of Lake Michigan. There is also a noteworthy gap in Fog of unknown origin from Grand Rapids Michigan southwestward to Lake Michigan as fog forms on either side of that line. This is especially evident around 0845 UTC; the gap subsequently fills in as fog becomes more widespread.

GOES-16 data posted on this page are preliminary, non-operational and are undergoing testing

GOES-16 also viewed the fog field, from the top of the cloud deck, as shown below in an animation (courtesy of Nathan Jeruzal the National Weather Service Grand Rapids Office) of the Brightess Temperature Difference field (10.3  µm – 3.9  µm) for two hours before sunrise on 14 September 2017. A still image at 1117 UTC suggests that fog over Grand Rapids’ city limits was not widespread, perhaps due to slight warming in the city due to an Urban Heat Island that would reduce the relative humidity.

At the end of the animation, there is a consistent change in signal over eastern Michigan, from cyan indicating low clouds/stratus to grey, indicating no cloud, because of increasing amounts of reflected solar radiation at 3.9 as the Sun rises. The GOES-R IFR Probability field animation at top suggests that the fog persists through sunrise.

GOES-16 Brightness Temperature Difference fields (10.3 µm – 3.9 µm), 0947-1142 UTC on 14 September 2017;  City outlines are denoted in Yellow (Click to enlarge)

Dense Fog over Missouri

GOES-R IFR Probability Fields, and surface reports of Ceilings and Visibilities, hourly from 0315 to 1315 UTC on 15 August 2017 (Click to enlarge)

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

IFR Conditions and Dense Fog developed over southeastern Missouri during the early morning on 15 August 2017, leading to the issuance of Dense Fog Advisories. GOES-R IFR Probabilities, above, showed increasing values as the ceilings lowered and visibilities dropped.  The IFR Probability fields over southern Missouri and northern Arkansas (and Kansas and Oklahoma) have the characteristic uniformity that arises when Rapid Refresh data alone are used to drive the IFR Probability values.  In these regions, high clouds (associated with convection over Arkansas) are blocking the satellite view of lower clouds.

Such high clouds will make it difficult for a satellite-only product to identify the regions of clouds.  For example, the Brightness Temperature Difference field below (10.3 µm – 3.9 µm) from GOES-16, color-enhanced so that low clouds are green and that cirrus (at night) are purple) shows widespread low cloudiness at the start of the animation, including some obvious river fog over Missouri (river valleys that are not well-resolved with GOES-13), but developing convection over Arkansas eventually prevents the view of low clouds.

GOES-16 data posted on this page are preliminary, non-operational and are undergoing testing

GOES-16 Brightness Temperature Difference field (10.3 µm – 3.9 µm), hourly from 0312 to 1312 UTC on 15 August 2017 (Click to enlarge)

Because the Brightness Temperature Difference field (helpfully called the ‘Fog’ Channel Difference in AWIPS) is challenged by high clouds in viewing the low clouds, RGB Products that use the brightness temperature difference field are also similarly impeded by high clouds.  Consider, for example, the stations in southern Missouri shrouded by the cirrus shield.  IFR Conditions are occurring there and a strong signal of that appears in the IFR Probability fields.

GOES-R IFR Probability computed with GOES-13 and Rapid Refresh Data, GOES-16 Fog (10.3 µm – 3.9 µm) Brightness Temperature Difference and GOES-16 Advanced Nighttime Microphysics RGB, all near 1115 UTC on 15 August 2017 (Click to enlarge)

Dense Fog over the Texas High Plains

GOES-R IFR Probability fields, hourly from 0215-1115 UTC on 2 August 2017 (Click to enlarge)

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

The National Weather Service in Lubbock issued Dense Fog Advisories (below) for parts of their CWA early in the morning on 2 August 2017.  GOES-R IFR Probability fields, above, show a slow increase in values over west Texas during the night of 1-2 August 2017, as visibilities drop and ceilings lower in the region.  This followed a band of showers that moved through the area around sunset on 1 August (Click here for a visible image from 0017 UTC on 2 August, from this site).  Highest IFR Probability values at the end of the animation generally overlay the Dense Fog Advisory.  As a situational awareness tool for the developing fog/low stratus, IFR Probability performed well.

 

GOES-16 data posted on this page are preliminary, non-operational and are undergoing testing

GOES-16 Brightness Temperature Difference field (10.3 µm – 3.9 µm) at 1117 UTC on 2 August 2017 (Click to enlarge)

The GOES-R IFR Probability fields above mostly show the small-scale variability (i.e., pixelation) that is common when both (legacy) GOES data and Rapid Refresh Data are used to produce a probability that IFR conditions will be present.  Some exceptions:  southeastern New Mexico at the end of animation (1115 UTC);  the yellow and orange region there overlain by mid-level or high clouds that prevent a satellite view of the low clouds.  The GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm) field at 1117 UTC shows a signal of high clouds there (cyan / blue / purple enhancement showing negative values that typify thin cirrus in the Brightness Temperature Difference field at night).  The Green values in the color enhancement are positive values and correspond to stratus (composed of water droplets) clouds.  Because the Brightness Temperature Difference field shows a signal, the Advanced Nighttime Microphysics RGB will also have a signal for fog (the whitish/cyan color), as shown below.

GOES-16’s better temporal and spatial resolution allow for more accurate monitoring of the development of small-scale features.  However, the shortcomings of using a Brightness Temperature Difference from satellite to monitor fog development should not be forgotten:  In regions of cirrus, satellite views of low stratus and fog are blocked.  In addition, over Texas and the rest of the High Plains, upslope flow can generate stratus over the central Plains that becomes fog over the High Plains as the terrain rises into the clouds.  The top of the stratus cloud and the fog bank in such a case can look very similar from satellite.

Advanced Microphysics RGB Composite at 1117 UTC on 2 August 2017 (Click to enlarge)

Below is a toggle between the 1115 UTC IFR Probability field, the GOES16 Brightness Temperature Difference Field, and the GOES16 Advanced Microphysics RGB Composite.

GOES-R IFR Probability fields computed with legacy GOES data and Rapid Refresh model output, GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm) field and GOES-16 Advanced Microphysics RGB, all near 1115 UTC on 2 August 2017 (Click to enlarge)

 

Resolution: GOES-R IFR Probability Fields and GOES-16 Data

GOES-R IFR Probabilities computed with GOES-13 and Rapid Refresh Data, Hourly from 0215-1115 UTC on 31 July 2017 (Click to enlarge)

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

The animation above shows the evolution of GOES-R IFR Probability fields over West Virginia early on 31 July 2017, when IFR and Low IFR Conditions developed over much of the state. In addition to elevated probabilities over West Virginia, probabilities increased over eastern Virginia as well, where IFR conditions were not reported. The IFR probabilities over eastern Virginia diminished rapidly at sunrise, as indicated at the end of the animation.

Much of the fog on 31 July 2017 over West Virginia was valley fog. Legacy GOES (GOES-13 and GOES-15) has nominal 4-km resolution at the sub-satellite point, and this resolution can be insufficient to resolve the narrow valleys of the Appalachian Mountains.

GOES-16 data posted on this page are preliminary, non-operational and are undergoing testing

The GOES-16 Animation below shows the 10.3 µm – 3.9 µm Brightness Temperature Difference field for approximately the same time as above. The superior spatial resolution of GOES-16 is evident: tendrils of low clouds/fog are apparent in the animation that until sunrise highlights in green the clouds composed of water droplets (such as fog and stratus). A similar animation of the Nighttime Microphysics RGB Composite (here) similarly highlights stratus (as a whitish color) in the narrow river valleys.

GOES-16 Brightness Temperature Difference Fields (10.3 µm – 3.9 µm), hourly from 0312 – 1112 UTC on 31 July 2017 (Click to enlarge)

This Toggle between the GOES-R IFR Probability and the GOES-16 Brightness Temperature Difference field at 1015 UTC suggests how the IFR Probability Fields will better handle small valley fogs when GOES-16 data are used in the algorithm.

What GOES-16 Resolution will bring to IFR Probability

GOES-16 Brightness Temperature Difference field (10.3 µm – 3.9 µm) at 1247 UTC on 5 July 2017 (Click to enlarge)

GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing

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 continue to be created using legacy GOES (GOES-13 and GOES-15) data. This is slated to continue through late 2017. The toggle above, over Oregon, hints at how the change in resolution in GOES-16, even far from the sub-satellite point, will likely improve GOES-R IFR Probability performance in regions where topography can constrain low clouds and fog.  The GOES-16 Brightness Temperature Difference field, above, is color enhanced so that positive values (that is, where the brightness temperature at 10.3 µm is warmer than the 3.9 µm brightness temperature, which regions indicate cloud tops composed of water droplets, i.e., stratus) are whitish — and the data shows stratus/fog along the Oregon Coast, with fingers of fog advancing up small valleys.  The image below shows the GOES-R IFR Probability field for the same time (Click here for a toggle).

GOES-R IFR Probability fields show strong probabilities where the Brightness Temperature Difference field above is indicating low clouds.  This is not surprising as the morning fog on this date was not overlain by higher clouds.  However, the resolution inherent in the legacy GOES (inferior resolution compared to GOES-16), shows up plainly as a blocky field.  When GOES-R IFR Probability fields are computed using GOES-16 data, the IFR Probability field resolution will match the GOES-16 resolution.  (Click here for a aviationweather.gov observation of IFR / Low IFR conditions on the morning of 5 July).

GOES-R IFR Probability field computed from GOES-15 data at 1245 UTC on 5 July 2017 (Click to enlarge)

A similar set of figures for California at the same time is below.  The toggle is here, and the aviationweather.gov screen capture is here.

GOES-16 Brightness Temperature Difference field (10.3 µm – 3.9 µm) at 1247 UTC on 5 July 2017 (Click to enlarge)

GOES-R IFR Probability field computed from GOES-15 data at 1245 UTC on 5 July 2017 (Click to enlarge)

 

Methods of Fog Detection in the GOES-16 Era

GOES-16 ‘Fog Detection’ Channel Difference (10.3 µm – 3.9 µm), 0912 – 1132 UTC, 29 June 2017 (Click to enlarge)

GOES-16 data posted on this page are (still!) preliminary, non-operational data and are undergoing testing

The 16 channels on the GOES-R Series Advanced Baseline Imager (ABI) allow for many different channel combinations that can be used to detect atmospheric phenomena. The animation above shows the traditional method for detecting low stratus: the brightness temperature difference between the shortwave infrared (3.9 µm) and the cleanest longwave infrared (10.3 µm) windows. Cloudtops composed of water droplets are highlighted in the animation because they do not emit 3.9 µm radiation as a blackbody, but do emit 10.3 µm radiation as a blackbody; thus, the brightness temperature difference at night (when no reflected solar radiation at 3.9 µm is present) is positive. The range of the colorbar in the above animation is from -50 to +50 C; stratus appears as green over much of northern Wisconsin, Minnesota and North Dakota.  Higher cirrus clouds are cyan, and they interfere with the satellite detection of low clouds, especially over eastern North Dakota where IFR conditions were widespread (source), and where a Dense Fog Advisory existed.  Note the apparent disappearance of the fog signal — in green — as the sun rises.  Increasing amounts of reflected solar radiation are causing the brightness temperature difference value to switch sign from (10.3 µm – 3.9 µm) > 0 at night (because of emissivity differences) to (10.3 µm – 3.9 µm) < 0 during the day (because of solar reflectance).

The ‘Nighttime Microphysics Advanced RGB’ is also used as a fog detection device. In the animation below, low stratus (and by inference, fog) is highlighted in cyan, a signal that comes mostly from the ‘green’ part of the RGB, namely the Brightness Temperature Difference as shown above. Because the two products are linked by the 10.3 – 3.9 brightness temperature difference, shortcomings in that product as far as fog detection affect the RGB. Note how the fog signal erodes over Minnesota/Wisconsin as the sun rises, and how it is obscured by high clouds (dark purple/magenta) over North Dakota.

 

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, shown for this event below, were designed to mitigate detection issues noted above.  Where high clouds are present, meaning the satellite cannot detect low clouds, information about low-level saturation from the Rapid Refresh is used to assess whether or not fog is likely.    That low-level information from the model also can be used to distinguish between fog and elevated stratus that can look very similar from the top, as a satellite views it.  The fusing of model and satellite data makes for a product that has better statistics in detecting low ceilings and reduced visibilities.

At the end of the two animations above, for example, how confident will a satellite analyst or forecaster be that there is dense fog over eastern North Dakota?  How about the analyst/forecaster using IFR Probability fields? IFR Probabilities maintain a signal for fog over the entire region from North Dakota to Wisconsin, even through sunrise and under high clouds.

GOES-R IFR Probabilities, 0915 to 1115 UTC on 29 June 2017 (Click to enlarge)