Category Archives: Midwest

IFR Probability as a Heads Up in Indiana

Because IFR Probability includes both model information on low-level saturation and satellite information on low-level clouds, it can give an advanced warning on the development of fog when high clouds — at might occur behind departing convection, for example — prevent the satellite from viewing the low cloud beneath high clouds.  Consider the animation below, that shows IFR Probability fields along with surface observations of ceilings and visibilities plotted so that regions with IFR conditions can be identified.  IFR probability fields develop over northwest Indiana over the course of the night, especially over extreme northern Indiana where the east-west Indiana Toll road sits.

GOES-R IFR Probability fields, along with observations of ceilings and visibility, 0051 – 1321 UTC (every 10 minutes) on 3 August 2020 (Click to enlarge)

Compare the IFR Probability fields above to the Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) field below. The field below historically has been used at night to identify regions of low clouds/fog — regions that are cyan in the enhancement are low clouds, regions that are black are high clouds. As the sun rises, the Night Fog brightness temperature difference field will struggle to identify regions of low clouds (although a different enhacement can be used to highlight the low cloud regions after sunrise). The satellite is not able to view low clouds over northern Indiana until the high clouds move out. Thus, a distinct indication of low clouds over the Indiana Toll road lags the suggestion of low clouds given by IFR Probability fields.

GOES-16 ‘Night Fog’ Brightness Temperature Difference (10.3 µm – 3.9 µm), every ten minutes from 0051 to 1321 UTC, 3 August 2020 (click to enlarge)

Consider the toggle below of GOES-R IFR Probability, Night Fog Brightness Temperature Difference and the Nighttime Microphysics RGB at 0601 UTC on 3 August.. IFR Probability fields show a developing region of IFR conditions (in yellow) over extreme NW Indiana. The two satellite-only detectors show only a scant suggestiong that fog is present. (A similar scenario is occurring near the bootheel of Missouri)

GOES-R IFR Probability, Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), and Nighttime Microphysics RGB, 0601 UTC on 3 August 2020 (Click to enlarge)

At 0901 UTC, below, all three indicators of low clouds are in better agreement over northwest Indiana (and over the Missouri Bootheel) as high clouds move from those areas.

GOES-R IFR Probability, Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), and Nighttime Microphysics RGB, 0901 UTC on 3 August 2020 (Click to enlarge)

Fields at 0931 and 1001 UTC continue this trend of stronger signals in the regions initially highlighted at 0601 UTC by the IFR Probability fields.

GOES-R IFR Probability, Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), and Nighttime Microphysics RGB, 1031 UTC on 3 August 2020 (Click to enlarge)

By 1131 UTC, below, increasing solar reflectance over the eastern part of the domain has changed the signal in both the Nighttime fog and Nighttime microphysics RGB over northern Indiana and Ohio. The GOES-R IFR Probability signal however is maintained.

GOES-R IFR Probability, Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), and Nighttime Microphysics RGB, 1131 UTC on 3 August 2020 (Click to enlarge)

IFR Probability, Brightness Temperature Differences and Nighttime Microphysics RGB estimates of Fog

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and IFR Probability Fields, 1126 UTC on 17 December 2019. Also included are sky conditions, ceilings and visibilities in black or green.

Fog and low clouds were widespread over the eastern half of the United States on 17 December 2019. In this example over ArklLaTex the Brightness Temperature Difference suggests low stratus clouds over the region, and the Nighttime Microphysics shows a signal congruent with low clouds. Note, however, that observations over much of the region do not suggest IFR conditions are present. Accordingly, IFR Probability shows fairly low probabilities in this region, with values increasing to the north where visibilities decrease. IFR Probability fields screen out regions of elevated stratus because the Rapid Refresh model in this region does not suggest low-level saturation. Over northeast Oklahoma and northwest Arkansas, however, saturation at low levels is more likely and IFR Probabilities there are larger.

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and IFR Probability Fields, 1126 UTC on 17 December 2019. Also included are sky conditions, ceilings and visibilities in green.

At the same time, high clouds overspread most of the east coast as a storm moved through the area. The high clouds prevent the satellite from seeing low clouds, so both the Brightness Temperature Difference and the Nighttime Microphysics RGB will not have a signal that comports with low stratus detection. However, IFR Probability includes a signal from the Rapid Refresh model if that model shows low-layer saturation in a region of multiple cloud layers; IFR Probability has a strong signal on this date over the east coast were clouds and fog are widespread. IFR Probability also shows IFR Conditions under the low clouds that the satellite does detect over eastern Ohio, and correctly notes the a region of higher ceilings over West Virginia, western Virginia and eastern Tennessee.

GOES-16 Brightness Temperature Difference (10.3 µm – 3.9 µm), Nighttime Microphysics RGB and IFR Probability Fields, 1126 UTC on 17 December 2019. Also included are sky conditions, ceilings and visibilities in green.

When high clouds are not present, there are different equally good ways to estimate low clouds, and that’s shown above. The Brightness Temperature Difference fields, the Nighttime RGB and the IFR Probability fields all tell a similar tale: Much of Iowa and regions to the south and northeast have low ceilings and reduced visibility.

Careful observers to the toggle note that the RGB has a different color over Wisconsin compared to Iowa. In part this is because the Brightness Temperature Field has values that are smaller over Wisconsin. A bigger driver of the color difference, however, is the 10.3 µm brightness temperature — the blue component of the Nighttime Microphysics RGB. Values are around -25º C over Wisconsin, and closer to -10º C over Iowa!

Nighttime Microphysics RGB and Band 13 10.3 µm Brightness Temperature, 17 December 2019

Fog surrounding convection in the Midwestern United States

GOES-16 IFR Probability and GOES-16 ‘Night Fog’ Brightness Temperature Difference (10.3 µm – 3.9 µm) at 1001 UTC on 2 May 2019, along with surface observations of ceilings and visibility (Click to enlarge)

Widespread Fog occurred over the midwestern United States on Thursday morning, 2 May 2019, with some Dense Fog Advisories issued. Some of the fog developed under an extensive cirrus canopy associated with strong convection over north-central Illinois, and those cloud layers make satellite-based detection of stratus near the surface (i.e., fog) a challenge.  The toggle above between the Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) and GOES-16 IFR Probability highlights the difficulty in using the brightness temperature difference alone to outline regions of fog. In contrast, the Rapid Refresh model information on low-level saturation allows IFR Probability to alert a forecaster to the likelihood of fog in regions underneath cirrus, regions such as southeastern Illinois and southwestern Indiana.

There is an excellent spatial correlation between regions with high IFR probability and low ceilings/reduced visibilities, and also with regions with low IFR probability and non-IFR conditions (central Iowa, for example, and central Illinois southwestward into central Missouri).

Because the Night Fog Brightness Temperature difference is a central feature of the Nighttime Microphysics RGB product — Night Fog Brightness Temperature difference is the green part of that RGB, as apparent in the toggle below — Nighttime Microphysics also is challenged to identify fog in regions under cirrus

Advection Fog in Warm Air Advection Regimes

‘Night Fog’ Brightness Temperature Difference field (10.3 μm – 3.9 μm) and GOES-R IFR Probability at 1202 UTC on 4 February 2019 (Click to enlarge)

Advection Fog during thaws, when very cold surfaces are overrun by air with dewpoints above freezing, can be very dense, and very difficult to detect via satellite; typically advection fog accompanies extratropical cyclones and their accompanying multiple cloud layers. The toggle above compares the ‘Night Fog’ Brightness Temperature Difference field (10.3 μm – 3.9 μm), historically used to detect low stratus because of radiation emissivity differences of clouds made up of water droplets at those two wavelengths, and GOES-R IFR Probability which fuses information from the satellite — not particularly useful in this case as far as low-level visibility is concerned — with information about low-level saturation from the Rapid Refresh Model. GOES-R IFR Probability gives a much more accurate depiction of exactly where the reduced visibilities and lowered ceilings are present, a vital piece of information for aviation (for example).

In addition, Low IFR Probability suggests where the lowest ceilings and greatest visibility reductions occur. The toggle below compares IFR Probability and Low IFR Probability at 1202 UTC (Here’s the toggle at 1642 UTC).  As expected, the region of Highest Low IFR Probability is contained within the region of highest IFR probability;  values of Low IFR Probability are somewhat smaller than those for IFR Probability (the same colorscale is used for both products).

GOES-R IFR Probability and Low IFR Probability at 1202 UTC on 4 February 2019 (Click to enlarge)

Fog over the central United States

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) and Nighttime Microphysics RGB at 0507 UTC on 1 February 2019, and surface observations of ceilings and visibilities (Click to enlarge)

The toggle above displays the Night Fog Brightness Temperature Difference field (10.3 µm – 3.9 µm) and the Night Time Microphysics Red/Green/Blue (RGB) Product that uses the Night Fog Brightness Temprature Difference field as its green value. In the color enhancements above, cyan in the Night Fog Brightness Temperature Difference denotes positive values that occur because stratus clouds — that is, clouds that are made up of water droplets — do not emit 3.9 µm radiation as a blackbody. Consequently, the computation of brightness temperature (which assumes blackbody emission) results in a 3.9 µm brightness temperature that is cooler than at 10.3 µm (clouds are emitting 10.3 µm radiation very nearly like a blackbody).  Low clouds in the RGB that may or may not support IFR conditions range in color from light cyan (over Texas and Florida) to more orange and yellow (yellow over the Great Lakes were exceptionally cold air is in place).

The fields above are overpredicting where fog/low ceilings might be occurring because cloud top measurements from the Brightness Temperature Difference do not always give reliable guidance on cloud base.

By merging satellite information about clouds and cloud type with Rapid Refresh model information at about low-level saturation, GOES-R IFR Probability fields screen out regions where IFR conditions are unlikely;  the map suggests low ceilings and fog are most likely over Texas and Oklahoma.  The zoomed in image, below shows that IFR conditions are indeed occurring in this region.  Other regions with a strong signal in the Brightness Temperature Difference field — Tennessee, for example — show low IFR Probability and surface observations that do not show IFR conditions.

GOES-R IFR Probability field, 0507 UTC on 1 February, along with surface reports of ceilings and visibility (Click to enlarge)

GOES-R IFR Probability field, 0507 UTC on 1 February, along with surface reports of ceilings and visibility zoomed in over the southern Plains (Click to enlarge)

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) and Nighttime Microphysics RGB at 1007 UTC on 1 February 2019, and surface observations of ceilings and visibilities (Click to enlarge)

The same relationships occur at 1007 UTC; the Night Fog Brightness Temperature Difference and Nighttime Microphysics RGB overpredict the regions of low clouds/fog; IFR Probability’s use of Rapid Refresh Data allows it to screen out regions where fog is not present, but stratus clouds are, and also add in regions where cirrus clouds prevent the detection of low clouds, but Rapid Refresh data suggests low-level saturation is present (such as over the Gulf of Mexico south of Louisiana).

The IFR Probability field is accurately outlining the region of IFR conditions.

GOES-R IFR Probability field, 1007 UTC on 1 February, along with surface reports of ceilings and visibility (Click to enlarge)

GOES-R IFR Probability field, 1007 UTC on 1 February, along with surface reports of ceilings and visibility zoomed in over the southern Plains (Click to enlarge)

Fog over the Dakotas and Minnesota: Where is it?

GOES-16 “Red Visible” Band 2 0.64 µm imagery at 1502 UTC on 21 November 2018 (Click to enlarge)

Consider the GOES-16 Visible (Band 2, 0.64 µm) Image above.  Where is the fog in this image?  Certainly you can tell where clouds exist, and if animated, you could identify snow on the ground (because it wouldn’t move like clouds do).  Alternatively, you could toggle between the visible and the Snow/Ice band (Band 5, 1.61 µm), below;  regions of snow/ice — such as in western North Dakota, or northeastern South Dakota, or Ontario appear bright in the 0.64 µm but dark in the 1.61 µm.

GOES-16 “Red Visible” Band 2 0.64 µm imagery and “Snow/Ice” Band 5 1.61 µm imagery at 1502 UTC on 21 November 2018 (Click to enlarge)

The Day Fog Brightness Temperature Difference product (3.9 µm – 10.3 µm) highlights low clouds. Stratus clouds with water droplets are scatterers of incoming solar radiation. The clouds over Minnesota and Iowa appear to be composed of much smaller water droplets, however, because they are so much warmer — the brightness temperature difference is much larger.  Smaller droplets are better scatterers of incoming solar radiation.  The image below shows the field, also at 1502 UTC on 21 November.  Are there any differences in this field that suggests fog might be present in one location, but not in the other?

GOES-16 Day Fog Brightness Temperature Difference (3.9 µm – 10.3 µm) imagery at 1502 UTC on 21 November 2018 (Click to enlarge)

The Day Snow Fog RGB composite, below, highlights regions of low clouds, snow/ice, and higher clouds.  Snow (and clouds made of ice) are shaded red, low clouds are shades of grey/blue.  Where is the fog?

GOES-16 Day Snow Fog RGB imagery at 1502 UTC on 21 November 2018 (Click to enlarge)

GOES-R IFR Probability Fields are a better predictor of where IFR conditions (that is, reduced visibility and lowered ceilings as might occur with fog) are occurring.  It combines satellite information and low-level informatio0n about saturation (from the Rapid Refresh model).  This fusing of data accentuates a satellite strength (detection of low clouds made up of water droplets — that is, stratus) and the model strength (namely, where are the low-level saturated?)   In the image below, fog and high probabilities of IFR conditions neatly overlap.  This toggle is between the visible, Day Snow-Fog RGB and IFR Probability field.

GOES-16 IFR Probability at 1502 UTC on 21 November 2018 along with surface observations of ceilings and visibility (Click to enlarge)

IFR Conditions with cold-season extratropical cyclones

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), Advanced Night Time Microphysics RGB, and GOES-16 IFR Probability fieds at 1142 UTC on 8 October 2018 (Click to enlarge)

Fog and low stratus were widespread on 8 October over the Plains, in particular over Iowa and Minnesota.  What satellite tools exist to highlight such regions of lowered ceilings and reduced visibility?

When IFR conditions — fog and low stratus — occur with extratropical cyclones that generate multiple cloud layers, satellite detection of low clouds is difficult because higher clouds get in the way of the near-surface view. The animation above steps through the Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm; low clouds in the default enhancement are cyan), the Nighttime Microphysics Red-Green_blue (RGB) composite (low clouds in the RGB are cyan to yellow, depending on the temperature) and the GOES-R IFR Probability field (Probabilities for IFR conditions are highest in orange/red regions) for 1142 UTC on 8 October 2018, when low ceilings were widespread over the Plains and East Coast. Abundant high clouds rendered the Night Fog Brightness Temperature difference product (and, by extenstion, the Night Time Microphysics RGB, because the RGB uses the Night Fog Brightness Temperature Difference as its ‘Green’ Component) ineffective in outlining potential regions of low clouds. In contrast, the IFR Probability field was able to highlight low clouds under the high clouds because it fuses satellite data (ineffective at this time) with Rapid Refresh model estimates of low-level saturation.

There are regions — southern Lake Erie, for example — where the lack of high clouds allows the Brightness Temperature Difference field, and the Nighttime Microphysics RGB to operate with success in identifying low clouds.

The toggle below shows the Night Fog Brightness Temperature Difference and the IFR Probabiity fields over the eastern portion of the country.  Very small-scale (in the horizontal) features, such as river fog, are a challenge for IFR probability because the Rapid Refresh horizontal resolution of 13 km may not resolve river valleys.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) and GOES-16 IFR Probability fieds at 1142 UTC on 8 October 2018 (Click to enlarge)

Dense Fog over the Midwestern United States

GOES-R IFR Probability Fields, 0337 – 1332 UTC on 8 August 2018 (Click to enlarge)

The longer August nights over the upper Midwest (for example, Madison Wisconsin’s night is about 70 minutes longer now than it was at the Summer Solstice) can allow for dense fog to form when light winds and clear skies follow a cloudy, damp day. The animation above shows the evolution of the GOES-R IFR Probability fields as the dense fog develops, a fog for which advisories were issued.  The horizontal extent of the widespread fog is captured well in the IFR Probability fields.  There are a couple of things worth noting.

There is a subtle — but noticeable — change in the IFR Probability Fields each hour in the animation. That change is related to model data in this fused product. Rapid Refresh Model output are used to identify regions of low-level saturation that must occur with fog. (The inclusion of this data helps IFR Probability better distinguish — compared to satellite imagery alone — between elevated stratus and fog). When output from newer model runs is incorporated (and that happens every hour), the IFR probability fields are affected. The amount of change is testimony to whether the sequential runs of the Rapid Refresh are consistent in capturing the developing fog. In this case, there were differences from one model run to the next.

GOES-R IFR Probability fields, 1202 UTC on 8 August 2018 (Click to enlarge)

Two boundaries are apparent in the animation above, captured in the 1202 UTC image above, and in the 1302 UTC image below. These boundaries are related to the Terminator, the dividing line between night and day. During an hour around sunrise, rapid changes in reflected 3.9 µm solar radiation make the detection of low clouds difficult. Temporal adjustments are incorporated into the IFR Probability fields to create a cleaner field. In the 1202 UTC image, above, the effects of sunrise are occurring along the NNW-SSE oriented boundary near the Mississippi River in southwestern WI (The boundary is parallel to the Terminator line, so it will be vertical — parallel to a Longitudinal Line — on the Equinoxes).   In the 1302 UTC image, below, the second boundary is over far northwestern Wisconsin, far southeastern Minnesota, and eastern Iowa.  The region between these two westward-propagating boundaries is where information from previous times is used in the IFR Probability fields.  Thus, when the second boundary passes, you may observe rapid changes in IFR Probability fields.

GOES-R IFR Probability fields, 1302 UTC on 8 August 2018 (Click to enlarge)

The Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) can be used to detect stratus, and that field is also a constituent (the ‘green’ part) of the Advanced Nighttime Microphysics RGB. The animation below compares these two products used to detect stratus with IFR Probability at 1002 UTC on 8 August 2018.  The Night Fog Brightness Temperature Difference fails to highlight regions of fog over central WI (and elsewhere), so neither it nor the RGB give a consistent signal over the entire fog-shrouded region.

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), GOES-R IFR Probability, and Advanced Nighttime Microphysics RGB at 1002 UTC on 8 August 2018 (Click to enlarge)

Advection Fog with a Spring Storm in the Ohio River Valley

GOES-16 IFR Probability fields, 0002 UTC through 1152 UTC on 29 March 2018, every 20 minutes (Click to enlarge)

Advection fog in the Spring, when high dewpoints overrun very cold ground surfaces, usually in association with an extratropical cyclone, are very difficult to detect using satellite-only products, as shown in the Brightness Temperature Difference field animation below (Click here for the same animation but with a 5-minute time step as observed in the CONUS domain by GOES-16). GOES-16 IFR Probability, above (Click here for an animation with a 5-minute cadence), is able to highlight the region of low ceilings and visibilities because Rapid Refresh Data supplies information about near-surface saturation that is lacking in satellite-only products such as the Brightness Temperature Difference, below, or, say, the Nighttime Microphysics RGB that uses the Brightness Temperature Difference. A toggle including IFR Probability, Night Fog Brightness Temperature Difference, and Nighttime Microphysics is below (from 0902 UTC on 29 March). Only the IFR Probability has an obvious signal difference between regions with IFR Conditions and regions without.

GOES-16 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 0002 – 1152 UTC at 20-minute timesteps (Click to enlarge)

GOES-16 IFR Probability, Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), and Nighttime Microphysics at 0902 on 29 MArch 2018 (Click to enlarge)

Advection Fog with a strong storm in the Midwest

GOES-16 IFR Probabilities, 1152 UTC on 22 January 2018, along with 1200 UTC surface observations of ceilings and visibilities (Click to enlarge)

When skies are clear, and radiation fog forms, limiting visibilities, it’s straightforward to use satellite-only products to gauge where stratus and fog might exist. Extratropical storms generate multiple cloud layers, however; when warm sector air under multiple cloud layers overruns snow-covered or frozen ground, dense advection fog can develop, and that fog is difficult to discern from satellite because it is typically overlain by higher clouds.

GOES-R IFR Probabilities, above, (and Low IFR Probabilities here) show highest probabilities in general occur in the regions where IFR conditions were observed on 22 January.  Over much of Wisconsin and Minnesota, the IFR Probability field is mostly uniform.  Such a flat field is characteristic of a region where satellite data cannot be used to judge whether low stratus is present (because high clouds are also present).  Rapid Refresh model information only is used to outline regions of low-level saturation. There is more variability to the IFR Probability field — that is, it is more pixelated — over southwest Iowa, for example, and over North Dakota.  In these regions, low stratus clouds are being observed by satellite and both satellite and model data can be used to estimate regions of significantly reduced ceilings and visibilities.

Consider the Brightness Temperature Difference shown below. The 10.3 µm – 3.9 µm product is typically used to identify stratus and radiation fog, and it does detect those low clouds over North Dakota, and over Kansas, Missouri and southern Iowa, and over Ontario.  However, the dense clouds associated with the storm over much of Minnesota and Wisconsin meant that this brightness temperature difference field, and also the NightTime Microphysics Red Green Blue Product (which is sometimes used to detect fog), could not ‘see’ the fog over the upper midwest.

Know the limitations, strengths and weaknesses of your products as you use them!  On 22 January, High Clouds underscored limitations in the Brightness Temperature Difference product, and in the NightTime Microphysics product that relies on the Brightness Tempearature Difference product for fog detection.  That limitation meant the product was not useful in identifying IFR conditions in parts of the Upper Midwest.

GOES-16 “Night Fog” Brightness Temperature Difference (10.3 µm – 3.9 µm) at 1152 UTC on 22 January 2018. Surface reports of ceilings and visibilities at 1200 UTC are also plotted (Click to enlarge)