Category Archives: Mid-Atlantic

IFR Probabilities over snow

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GOES-R IFR Probabilities from GOES-East and surface observations (Upper Left), MODIS visible imagery (Upper Left), MODIS Brightness Temperature Difference (10.7 µm- 3.9 µm) (Lower Left), MODIS Band 7 (2.2 µm )

GOES-R Cloud Type product from 1545 UTC 18 January 2013

GOES-R IFR Probabilities showed values around 20-25% over the fresh snow cover in south-central Virginia in the Piedmont.  Why?  The GOES-R cloud mask sometimes detects clouds where fresh snowfall is present, as shown in the GOES-R Cloud Type product above, especially if the snow mask is not up to date. The GOES-R cloud type product determines the phase of any pixel detected as cloud by the cloud mask;  clouds were detected, albeit incorrectly, in this area and classified as water clouds. It is unlikely that clouds are present over south-central Virginia because the brightness temperature difference product suggests no water-based clouds in this region — the white areas in the visible over southern Virginia and northern North Carolina have a signature in the 2.2 µm channel (lower right in the 4-panel image) that is strongly indicative of snow on the ground (snow strongly absorbs radiation at that wavelength, so little energy is reflected back to the satellite). The GOES-R FLS product is dependent upon the GOES-R cloud mask during the day and calculates the probability that IFR conditions are present for any detected cloudy pixel.  The presence of clouds in the Cloud Type product for reasons stated above leads to the calculation of an IFR probability where clear sky is likely present.  Although the IFR probabilities are higher over the fresh snow than in other clear sky areas, the probabilities are relatively low, around 20-25%. Probabilities in this range should give forecasters low confidence that IFR conditions are present in this area. Conversely, the small region of relatively high IFR probabilities (>50%) in southwest Virginia — near Wakefield — and extreme southwest Virginia — near Wise — correlates well with a region of eroding IFR conditions. Note that cloud ceilings over the mountains of far western Virginia are very close to or below IFR criteria, giving forecasters higher confidence that IFR conditions are present.

GOES-13 Visible Imagery over the mid-Atlantic showing snow cover over Virginia

The Visible imagery above shows generally clear skies over central Virginia, with some cloud streets developing later in the afternoon. The eroding IFR cloud deck over extreme SW Virginia is difficult to see in visible imagery alone but is evident by the dissipating clouds in western Kentucky.

Two examples from 17 January 2013

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GOES-R IFR Probabilities computed from GOES-East, 1700 UTC on 17 January 2013

 The image above shows how IFR probabilities can maximize over higher terrain where mountains rise up into a somewhat uniform cloud deck.  IFR probabilties are highest over the Laurel Highlands of Pennsylvania southward along the spine of the Appalachian Mountains in West Virginia (and also in the highlands of north-central Pennsylvania).  IFR Conditions are reported at K2G4 in Maryland, which is 890 meters above sea level, and near-IFR conditions are present at Johnstown, PA (KJST) and Elkins, WV (KEKN), two stations above 600 meters above Mean Sea Level.  In contrast, KCBE and KW99, Cumberland Maryland and Petersburg, WV, are both lower than 300 m above sea level, and IFR condition are not present there.

GOES-R IFR Probabilities (Upper Left), GOES-East Visible Imagery (Upper Right), GOES-East Brightness Temperature Difference (Lower Left), Suomi-NPP 1.61 µm Reflectivity (Lower Right)

GOES-R IFR probabilities maximized near the Missouri River Valley in eastern Nebraska around mid-day on 17 January 2013.  IFR conditions were reported.  The largest visibility restrictions appear to occur over a band of snow that extended southwest to northeast, roughly parallel to the N. Platte River, and IFR probabilities are highest in that region. The snow band shows up well in the visible imagery, and as a black swath in the 1.61 reflectivity (snow absorbs radiation at 1.61µm).

Interpreting IFR Probabilities when multiple Cloud Layers exist

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GOES-R IFR Probabilities computed from GOES-East and the Rapid Refresh, 1400 UTC 26 December 2012, and surface observations of ceilings and visibilities.

Large winter-time extratropical storms generate multiple cloud layers, and those many layers make difficult the detection of IFR conditions at the surface, caused by fog and low stratus.  The winter storm moving up the East Coast on December 26th, 2012, is typical of the type of storm that causes these conditions (although its abnormal production of tornadoes is very atypical).  In the figure above, IFR probabilities are high over eastern North Carolina, and those high probabilities are generated solely from Model Data.  Satellite information from GOES-East there is not useful because of multiple cloud layers.  There are regions over western North Carolina — where the GOES-R IFR probability field is less smooth and more pixelated — where GOES data indicate low-level clouds only and both satellite data and model data contribute to the IFR Probability fields.

GOES-R IFR Probabilities (Upper Left), GOES-East Brightness Temperature Difference Field (10.7 µm – 3.9 µm ) (Upper Right), GOES-R Cloud Thickness (Lower Left), GOES-East Visible Imagery (0.62 µm) (Lower Right)

The hourly animation of GOES-R IFR probabilities, Traditional Brightness Temperature Difference, GOES-R Cloud Thickness and Visible Imagery, above, is instructive on several points.  The Traditional Brightness Temperature Difference, because of the abundant high clouds (likely associated with the warm conveyor belt of the extratropical storm), yields little information about low-level conditions.  Note also how Cloud Thickness field is computed in one region:  the region where multiple cloud layers do not exist, and where twilight conditions are not present.  There are also differences in the GOES-R IFR Probability field between day and night that reflect the different predictors (and different predictor weights) that are used during those two times.

IFR conditions under high clouds in the Northeast

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GOES-R IFR Probabilities computed using GOES-East (Upper Left), GOES-East Brightness Temperature Difference (10.7 µm- 3.9 µm, The ‘traditional’ fog detection product) (Upper Right), GOES-R Cloud Thickness computed using GOES-East (Lower Left), GOES-East Window Channel (10.7 µm) Brightness Temperature (Lower Right)

When high clouds overspread an area, the traditional brightness temperature difference product cannot be used to highlight areas of fog and low stratus because radiation emissions are originating from high clouds, not from the water-based low clouds.  In this example from Monday morning, 17 December 2012, IFR conditions, causing airport flight delays, are commons from Washington DC to New York, and the GOES-R IFR probability product highlights the area where IFR (and near-IFR) conditions prevail.  Modest values (around 50%) occur where the satellite predictors do not provide a fog/low stratus signal;  however, the Rapid Refresh model data does show high probability of fog and low stratus.  Where the Satellite does contribute to the product (that is, in Pennsylvania north and east of the high cloud deck), IFR probabilities are very high.

Note also that the GOES-R Cloud Thickness product (bottom left), is computed only for the highest water-based cloud (in non-twilight conditions).  It is therefore not shown under the cirrus canopy, over southern New Jersey, Delaware, and Chesapeake Bay.

Marine Stratus, Day 2

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GOES-R IFR Probability (Upper Left), GOES-R Cloud Thickness (Upper Right), GOES-East Brightness Temperature Difference (10.8 µm – 3.9 µm) (Lower Left), GOES-East Visible Imagery (Lower Right) at 0800 UTC 26 October 2012

The marine stratus over the mid-atlantic on Oct 25th (Link) has continued to spread southwestward into North Carolina, and higher values in the IFR probability fields continue to overlap nicely with observed IFR conditions in the Piedmont of North Carolina.  The image above at 0800 UTC, and below at 1100 UTC, show deteriorating flight conditions as the high probabilities ooze southwestward.  Note that the traditional brightness temperature difference field does show a signature of the cirrus outflow from Hurricane Sandy off the coast of the Carolinas, in the extreme southeast part of the images, both at 0800 UTC and 1100 UTC.

GOES-R IFR Probability (Upper Left), GOES-R Cloud Thickness (Upper Right), GOES-East Brightness Temperature Difference (10.8 µm – 3.9 µm) Lower Left), GOES-East Visible Imagery (Lower Right) at 1100 UTC 26 October 2012
GOES-R IFR Probability (Upper Left), GOES-R Cloud Thickness (Upper Right), GOES-East Brightness Temperature Difference (10.8 µm – 3.9 µm) Lower Left), GOES-East Visible Imagery (Lower Right) at 1600 UTC 26 October 2012

By 1600 UTC, the cirrus canopy from Sandy has overspread most of eastern North Carolina.  This makes satellite data less useful in computing IFR probabilities, and Model Data comparatively more important, and the character of the IFR probability field does change, with a smoother field overall.  At 1600 UTC the probabilities have decreased; the temporal evolution of the field (not shown) is still giving important information, especially in concert with the surface visibility/ceiling observations.  The decrease in probabilities is gradual as the Sun slowly works to warm the boundary layer.

Marine Stratus in the Mid-Atlantic States

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GOES-R IFR Probabilities computed from GOES-East (upper left), GOES-R Cloud Thickness in ft (upper right), Brightness Temperature Difference (10.8 µm – 3.74 µm) computed from Suomi/NPP VIIRS data, Brightness Temperature Difference (10.8 µm– 3.9 µm) computed from GOES East, all valid about 0700 UTC 25 October 2012

Marine Stratus has moved inland over Maryland and surrounding states overnight, and the GOES-R IFR probabilities capture the visibility restrictions that have accompanied it.  The imagery above includes the traditional brightness temperature difference fields computed from Suomi/NPP (horizontal resolution:  1 km at nadir) and from GOES (nominal horizontal resolution:  4 km at nadir).  The distinct leading edge of the marine layer is readily apparent in the Susquehanna River Valley.  Note, however, that the strong returns over the Hudson River Valley do not correlate well with reduced visibilities. The GOES-R IFR probabilities do a good job depicting the marine layer in the Susquehanna River Valley (shown by the relatively high probabilities), but return much lower probabilities over the Hudson River Valley where surface observations indicate hazardous low clouds are not present.  Again, this is a benefit of using a fused product.

GOES-R IFR Probabilities (Upper Left) and Cloud Thickness (Upper Right), Suomi/NPP Day/Night Band (Lower left) and MSAS-derived Dewpoint depression on top of Visible imagery.  Times as indicated

The temporal resolution of GOES-R IFR products allow for continuous monitoring of an evolving situation, making up for the relatively poor horizontal resolution (compared to polar orbiting platforms like Suomi/NPP or Terra/Aqua).  The IFR probability field neatly captured the relentless inland push of the marine stratus air, and as the probabilities increase at locations, IFR conditions become more likely.  The loop above includes a Day/Night band image that is reproduced below.  The day/night band, even in low lunar light cases, can distinguish between clear sky and clouds over ocean.  Over land, however, the interpretation is complicated by city lights shining through clouds.  Nevertheless, the cloudy region can be discerned over parts of eastern Pennsylvania and Maryland, where the light signal is more diffuse.

GOES-R Probabilities evolve as the night progresses

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GOES-R IFR Probabilities computed from GOES-14 (upper left), GOES-14 heritage brightness temperature difference product (upper right), VIIRS heritage brightness temperature difference product (lower left), MODIS heritage brightness temperature difference product (lower right), all from near 0700 UTC.

MODIS and VIIRS yield satellite information that can be used to detect fog/low stratus at high spatial resolution.  In the exa,ple above, the VIIRS brightness temperature difference product highlights many river valleys as possibly cloud-filled over eastern Kentucky, southern Ohio and southwestern West Virginia.  The coarser resolution of the GOES satellite pixel precludes such fine-scale detection.  Note, however, that both satellite platforms detect the presence of stratiform water clouds over north-central Ohio where surface observations show only mid-level cloudiness.  IFR probabilities are confined to the spine of the Appalachians from the Laurel Mountains near Johnstown (PA) southward towards southern West Virginia.  How do things evolve with time?

As above, but from near 0800 UTC

As above, but from near 0915 UTC

As above, but from near 1000 UTC

As above, but from near 1100 UTC

The power of GOES imagery in this case is to show the evolution of the fog/low stratus field.  Even at this only-hourly timestep, the development of regions of IFR conditions is evident, and those developing conditions occur in tandem with increasing probabilities in the GOES-R IFR Probability field.  Throughout the night, the GOES brightness temperature difference field flags the unimportant (from an aviation standpoint) stratus deck over northcentral Ohio, and the IFR probability field, which field also uses Rapid Refresh Model data, discounts the satellite signal.  By 1100 UTC, the river valley signal has strengthened enough in the GOES imagery to appear, and a corresponding increase in IFR probability occurs.

IFR Probability can also be computed using MODIS data (below). The 0739 UTC MODIS data, shown at the top of this blog post, highlights — as does GOES — the stratus deck over northern Ohio.  The MODIS-based IFR probabilities, however, do not highlight that cloud-deck, by design.  Note also that the higher-resolution MODIS imagery, because it detects river valley fogs at 0739 UTC, also has a strong IFR probability signal there.  Pixel resolution on GOES-R will be intermediate between MODIS and present GOES.

As at top, for near 0800 UTC, but with MODIS-based IFR probabilities in the lower right

IFR Probabilities in a large-scale rain event

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GOES-R IFR Probabilities over Pennsylvania and surroundings hourly from 1300 to 1700 UTC on 18 September 2012, with ceiling and visibility plots overlain.

The traditional method for identifying fog and low stratus, the brightness temperature difference between the 10.7 µm and 3.9 µm channels, cannot work in cases with multiple cloud layers, or in cases with cirrus.  Such a cloud environment is increasingly common in cooler weather months as extratropical cyclones and frontogenetic events cause large-scale ascent.  It is still important to have a way to identify regions of low clouds/fog, and the fused product that considers both satellite data and rapid refresh model data accomplishes that task.

When only model data are used in the fused product, IFR probabilities will peak around 55% — the dark orange shading that is comon over much of central Pennsylvania — to 67% — the isolated pockets of darker red/orange over western Centre County.  Higher values — such as the red values over the lower Susquehanna Valley — exceeding 75% require both a satellite and model estimate (there is likely a gap in the high-level cloudiness here that allows the satellite to view the lowest clouds).

As the thick overcast over Pennsylvania breaks apart during the course of the morning in this animation, the IFR probability field takes on a more pixelation aspect and regions of high IFR probability appear.  Again, highest probabilities occur in regions where both satellite and model suggest IFR conditions are present.  When satellite data are not available, IFR probabilities will not be so high.

Note in this animation that southeast Pennsylvania and New Jersey, where visibilities/ceilings exceed IFR thresholds, are regions where IFR probabilities correctly remain low.  This suggests that the Rapid Refresh model is accurately simulating the evolution of the weather system.

Fog and low Stratus Chances near Philadelphia

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The National Weather Service in Philadelphia/Mt. Holly NJ noted the possibility of fog formation in the moist airmass that supported showers and thundershowers over Pennsylvania on late Thursday.  From the forecast discussion issued at 0059 UTC on 7 September:

000
FXUS61 KPHI 070059
AFDPHI

AREA FORECAST DISCUSSION
NATIONAL WEATHER SERVICE MOUNT HOLLY NJ
859 PM EDT THU SEP 6 2012 
.... 
 
.NEAR TERM /UNTIL 6 AM FRIDAY MORNING/...

-- Changed Discussion --

DENSE GROUND FOG CONTINUES TO BE POTENTIAL PROBLEM OF THE NIGHT.
PUBLIC PRODUCTS UPDATED AT 555PM HAVE INCLUDED PATCHY DENSE FOG
IN MANY OF THE ZONES AND THE SHOWERS HAVE ENDED IN DE.

LIGHT WIND...CLEARING SKIES IN THE WAKE OF THE SHOWERS/SPRINKLES
EARLIER TODAY AND DEWPOINTS IN THE UPPER 60S TO AROUND 70 IN WHAT
SHOULD BE A MOSTLY CLEAR - NO WIND NIGHT WITH WEAK HIGH PRES IN PA
SPELLS TROUBLE...ESPECIALLY SINCE PATCHY LOW CIGS HAVE DEVELOPED
VCNTY KACY SINCE ABOUT 19Z...FIRST ALERT TO A BIGGER FOG/LOW CIG
PROBLEM.

GEOCAT SATELLITE AND SREF PROBS ARE NOT INDICATING MUCH FOG/LOW
CIG CHANCE AND MOST OF THE MET AND MAVMOS GUIDANCE IS NOT INTERESTED
IN FOG/LOW CIGS...YET THE MASS FIELDS OF BL AND SFC RH SEEM TO BE
MORE PLAUSIBLE. WE SHOULD KNOW BY 02Z AS A FEW OF THE TEMP/DEWS
START GETTING TO 100 PCT RH IN S NJ/DE. 
 
 
The possibility of fog remained a concern through the night, as noted in the forecast discussion from 0747 UTC:
000
FXUS61 KPHI 070747
AFDPHI

AREA FORECAST DISCUSSION
NATIONAL WEATHER SERVICE MOUNT HOLLY NJ
347 AM EDT FRI SEP 7 2012

........

-- End Changed Discussion --

&&

.NEAR TERM /UNTIL 6 PM THIS EVENING/...

-- Changed Discussion --

.....
WORTHWHILE FOG HAS NOT BEEN DEVELOPING OVERNIGHT. STEPPING OUTSIDE
WHILE IT IS CONSIDERABLY MURKIER THAN LAST NIGHT, ITS AS IF THE DEW
DEPOSITION (WHICH IS QUITE HEAVIER) IS TAKING AWAY FROM THE FOG.
GEOCAT IFR PROBS REMAIN LOW. WE STILL HAVE A COUPLE OF MORE HOURS
TO GO, WE WILL JUST KEEP THE MENTION OF SOME PATCHY/AREAS OF FOG IN
THE GRIDS, BUT STOP THERE. 
 
The GOES-R IFR Probability product, shown below at hourly intervals starting at 0315 UTC,  shows modest probabilities of fog over the Delaware Valley,  and higher probabilities over the Pine Barrens of central New Jersey, justifying the forecast mention of patchy fog.  
GOES-R IFR Probabilities from GOES-East (Upper Left), Traditional Brightness Temperature Difference Product (Upper Right), enhanced window channel (Lower Left), GOES-R IFR Probabilities from MODIS (Lower left)
MODIS data can be used to compute IFR probabilities.  One comparison scene exists at the beginning of the hourly loop, and the finer detail over the valleys of southeast Pennsylvania is evident in the 0322 UTC image.  The MODIS image at 0739 UTC shows (below) similar fine-scale structures that can help a forecaster fine-tune the forecast.  IFR probabilities in the MODIS images definitely jump over central New Jersey between 0322 UTC and 0733 UTC.  Such a notable change is a tool for a forecaster to be alert to the possibility of fog/low stratus and IFR conditions.  Several stations in central New Jersey, including McGuire Air Force base (KWRI), Belmar/Farmingdale (KBLM) and Mill Valley (KMIV) did report borderline IFR conditions between 0700 and 1000 UTC.
GOES-R IFR Probabilities from GOES-East (Upper Left), Traditional Brightness Temperature Difference Product (Upper Right), enhanced window channel (Lower Left), GOES-R IFR Probabilities from MODIS (Lower left) from ca. 0730 UTC

Excellent example of the importance of model data

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GOES-R IFR Probabilities computed using GOES-East data (Upper Left), GOES-R IFR Probabilities computed using MODIS data (Upper Right), Surface Observations and Cloud Ceilings Above Ground level (Lower Left), Suomi-NPP VIIRS Brightness Temperature Difference field, 10.8  µm – 3.74 µm (Lower Right).  Times as indicated.

Three different satellite sensors — the GOES Imager on GOES-East, MODIS on Aqua, and VIIRS on Suomi/NPP — viewed data from the occurrence of Valley Fog over the Appalachians (and surroundings) early in the morning of 21 August.  A shortcoming of the Brightness Temperature Difference field in the lower left is immediately apparent:  no fog/low stratus is indicated where high clouds exist, even though observations do show IFR conditions.  In contrast, the fused product does show heightened probabilities underneath that high cloud deck.  Probabilities are not as high as they are where both satellite and model predictors can be used to evaluate the presence of fog and low stratus, and the resolution of the field is different, obviously limited to the horizontal resolution of the Rapid Refresh, meaning that small river valleys, that are very obvious in the regions where satellite data are used (and even much more obvious when high-resolution MODIS or VIIRS data are used).  Note also how GOES-R IFR Probabilities de-emphasize the signal over western Ohio, where IFR conditions are not reported.  Brightness temperature difference fields from MODIS and from GOES both see a signal there, as also shown in the VIIRS field, but these stratus clouds are not obstructing visibility.

Bottom line:  MODIS data’s higher resolution observes the big differences between river valleys and adjacent cloud-free ridge tops.  GOES-East has difficulty in resolving those differences.  So MODIS IFR fields better highlight river fog.  Model data can help discern between fog on the ground, and stratus that is off the ground.