Category Archives: Suomi/NPP

Post-thunderstorm Fog over Mississippi

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GOES-R IFR Probability Fields, ~hourly, from 0300 through 1200 UTC on 19 May 2015 (Click to enlarge)

Thunderstorms moved through Mississippi (See this animation — from this Blog Post — of SRSO-R 1-minute imagery from 18 May), and the low-level moisture left behind allowed Dense Fog to form, and Dense Fog advisories were issued.

Multiple cloud decks — shown in the toggle, below, of Suomi NPP Day Night Band and Brightness Temperature Difference (11.45 µm – 3.74 µm) — prevented the traditional brightness temperature difference product from providing useful information. GOES-R IFR Probabilities, shown ~hourly in an animation above do highlight the region of developing IFR conditions. Low ceilings and reduced visibilities are commonplace in regions where IFR Probabilities are increasing over night. The predictors that are included to compute the IFR Probabilities are mostly model-based because of the multiple cloud layers that are present, and the IFR Probability field is somewhat flat as a result. Note that GOES-R IFR probabilities increase at the very end of the animation; when daytime predictors are used, probabilities are a bit higher than when nighttime predictors are used.

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Suomi NPP Day Night Band visible imagery and Brightness Temperature Difference (11.45 µm – 3.74 µm) at 0818 UTC, 19 May 2015 (Click to enlarge)

Fog along the East Coast

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GOES-R IFR Probability Fields computed from GOES-East and Rapid Refresh Data, hourly from 2300 7 May through 1200 8 May, and surface observations of ceilings/visibility (Click to enlarge)

GOES-R IFR Probability Fields showed large values at sunset over the Atlantic Ocean east of New Jersey and the Delmarva Peninsula. As night progressed, that fog penetrated inland. The IFR Probability field accurately depicts the region where visibilities due to fog were reduced. The 0400 UTC image in the animation above (reproduced below), has qualities that highlight the benefit of a fused product. The Ocean to the east of the southern Delmarva peninsula is overlain with multiple cloud layers that make satellite detection of low clouds/fog problematic. In this region, satellite data cannot be used as a predictor and the GOES-R IFR Probability field is a flat field. Because the GOES-R IFR Probability product includes information from the Rapid Refresh model (2-3 hour model forecasts, typically) and because saturation is indicated in the lowest 1000 feet of the model, IFR Probabilities over the ocean are high in a region where satellite data cannot be used as a predictor.

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As above, but for 0400 UTC 8 May 2015 only (Click to enlarge)

GOES-R IFR Probabilities can also be computed using MODIS data, which data has better spatial resolution than GOES (1-km vs. nominal 4-km). The toggle below of the MODIS brightness temperature difference and the GOES-R IFR Probability shows a very sharp edge to the expanding fog field over New Jersey.

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MODIS Brightness Temperature Difference (11µm – 3.9µm) and MODIS-based GOES-R IFR Probabilities, ~0250 UTC on 8 May, 2015 (Click to enlarge)

The Gulf Stream is apparent in the Brightness Temperature Difference field above and IFR Probabilities are high over the ocean between the coast and the Gulf Stream. In the absence of observations, how much should those high IFR Probabilities be believed. There is high dewpoint air (mid-50s Fahrenheit) along the East Coast at this time, and advection fog could be occurring, for example. Suomi NPP also overflew the region shortly after midnight. The toggle below, of brightness temperature difference and the Day Night Band confirms the presence of (presumably) low clouds over the cold Shelf Water of the mid-Atlantic bight.

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Suomi NPP Brightness Temperature Difference (11.35 µm – 3.74 µm) and Suomi NPP Day Night Band Visible Imagery (0.70 µm) at night, 0643 UTC on 8 May, 2015

Dense Fog over the Red River of the North

Dense Fog advisories were issued by the National Weather Service in Grand Forks as visibilities in the WFO dropped to near zero. How did the IFR Probability Fields and traditional Brightness Temperature Difference Fields capture this event? The animation below shows the brightness temperature difference field (10.7 µm – 3.9 µm) from GOES-13. Initially, a swath of mid-level and upper-level clouds covered the Red River Valley (this system had produced very light rains on Monday the 27th), but the clouds moved east and dense fog quickly developed (Cavalier, ND, for example, showed reduced visibility already at 0400 UTC).

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GOES-13 Brightness Temperature Difference (10.7 µm – 3.9 µm) hourly from 0315 to 1115 UTC on 28 April 2015, along with surface plots of ceilings and visibility (Click to enlarge)

The IFR Probability fields for the same time, below, better capture the horizontal extent of the fog.  For example, the strong signal in the Brightness Temperature Difference field over South Dakota at the end of the animation, above, is not present in the IFR Probability fields.  IFR Conditions are not occurring over South Dakota.  The good match between the developing IFR Probability fields and the developing fog testifies to the satellite view of the fog and the accurate simulation of this event by the Rapid Refresh model.

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GOES-R IFR Probability Fields hourly from 0315 to 1115 UTC on 28 April 2015, along with surface plots of ceilings and visibility (Click to enlarge)

Geostationary GOES fields give good temporal resolution to the evolving field. Polar orbiting satellites, such as Suomi NPP (carrying the VIIRS instrument) and Terra/Aqua (each carrying MODIS) each gave snapshot views of the developing fog. At 0355, IFR Probabilities are low, and the Red River valley is mostly obscured by higher clouds. Four hours later, at 0805 UTC, dense fog has developed and IFR probabilities are large.

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Terra MODIS Brightness Temperature Difference (11µm – 3.9µm) and IFR Probability fields, ~0355 UTC on 28 April 2015 (Click to enlarge)

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Aqua MODIS Brightness Temperature Difference (11µm – 3.9µm) and IFR Probability fields, ~0805 UTC on 28 April 2015 (Click to enlarge)

Suomi NPP also viewed the fog field. The toggle between the Day Night Band and the Brightness Temperature Difference field (11.45µm – 3.74µm), below, shows evidence of fog in the visible Day Night band imagery.  The lights of western North Dakota’s oil shale fields are also evident.

Polar-orbiting satellites give excellent high-resolution imagery of fog fields. When used in concert with the excellent time resolution of GOES imagery, a complete picture of the evolving fog field can be drawn.

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Toggle between Day Night Band (0.70 µm) and Brightness Temperature Difference (11.45µm – 3.74µm) field from VIIRS on Suomi NPP at 0815 UTC (Click to enlarge)

Fog over the High Plains of Texas

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GOES-R IFR Probability Fields, hourly from 0400 through 1000 UTC on 3 March 2015 (Click to enlarge)

Persistent fog has shrouded the High Plains of Texas for the past couple days.  GOES-R IFR Probability fields, above, from 0400 to 1000 UTC on 3 March, show the widespread nature of the fog.  There are regions in the animation (north and west of San Angelo at the start of the loop and north and west of Midland at the end of the loop) where the character of the IFR Probability field (a uniform value with a flat field and orange color) suggests high clouds are present and that fog detection with the product is relying on Rapid Refresh model output.  That the GOES-R IFR Probability fields align well with observations of IFR or near-IFR conditions is testimony to the accuracy of the Rapid Refresh Model. In the southern part of the domain, where GOES-R IFR Probability values are larger (the field is red), satellite data are also used in the computation of the IFR Probability field. Because satellite predictors can also be used there, confidence that fog/low stratus exists is greater, and the IFR Probability field values are larger. Note that the IFR Probability field there is also pixelated, reflecting the small pixel size (nominally 4 km) of the GOES Imager.

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Suomi NPP Brightness Temperature Difference Field (11.35 µm – 3.74 µm) and Day Night Band (0.70 µm) at 0905 UTC on 3 March 2015 (Click to enlarge)

Suomi NPP and Aqua both overflew the region around 0900 UTC on 3 March, and the high-resolution snapshots from Suomi NPP (above) and MODIS (below) show scenes that agree with the GOES Imagery. The Brightness Temperature Difference Fields show middle and high clouds over the Texas Panhandle. The Day Night band shows clouds over most of Texas — but it is difficult to distinguish high clouds and low clouds from the imagery. Shadows can be used to infer differences in cloud height — but that requires a knowledge of where the Moon sits in the sky relative to Texas at this time: to the east, or to the west?

The MODIS-based GOES-R IFR Probability field at ~0900 UTC, below, again shows how model data is helpful in filling in regions where high clouds or mid-level clouds obscure the satellite-view of low clouds/stratus.

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MODIS-based GOES-R IFR Probability and Aqua Brightness Temperature Difference Fields (11 µm – 3.9 µm) at 0855 UTC, 03 March 2015 (Click to enlarge)

Fog in the Pecos River valley of New Mexico

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GOES-R IFR Probabilities computed from GOES-13 and Rapid Refresh Data, 0700-1300 UTC, 6 February 2015 (Click to enlarge)

Fog developed over the Pecos River valley in southeastern New Mexico early on the morning of 6 February. This small-scale feature was captured well by the GOES-R IFR Probability fields, shown above. Probabilities increased quickly between 0745 and 0800 UTC. In contrast, the brightness temperature difference product, below, showed little signal until around 1000 UTC. GOES-R IFR Probability fields responded more quickly to the possible development of fog and in this case could have alerted any forecaster to its imminent formation. IFR conditions were present at Carlsbad (KCNM), Artesia (KATS) and Roswell (KROW) by 1100 UTC.

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GOES-13 Brightness Temperature Difference fields, 0700 through 1300 UTC, 6 February 2015 (Click to enlarge)

MODIS data from Terra and Aqua, and VIIRS data from Suomi NPP give occasional snapshots (at high resolution) of conditions. Terra (just before 0500 UTC) and Aqua (around 0900 UTC) data were used to compute IFR Probabilities, and the high resolution data, below, is consistent with the development of fog over night. The 0900 UTC image especially suggests the possibility of fog.

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MODIS IFR Probability from Terra (0448 UTC) and Aqua (0901) UTC on 6 February 2015 (Click to enlarge)

Suomi NPP data are not yet used to compute IFR Probabilities. The toggle, below, of the Day Night Band and the Brightness Temperature Difference at 0835 UTC does not show convincing evidence of fog at that time. The Day Night Band is very crisp because of the near Full Moon that provided ample lunar illumination.

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Suomi NPP Day Night Band and Brightness Temperature Difference, 0835 UTC, 6 February 2015 (Click to enlarge)

The imagery above all suggest that the presence of model data — from the Rapid Refresh — enhanced the satellite data as far as suggesting IFR conditions.

South Texas Fog and low stratus

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GOES-R IFR Probabilities, half-hourly from 0045 UTC to 1215 UTC on 4 February 2015, along wtih surface reports of ceilings and visibilities (Click to enlarge)

Fog developed over south Texas during the morning of 4 February. How did the GOES-R IFR Probability Products perform for this example, and what can be learned from them? There are at least two distinct regions in the animation above. Over much of southeast Texas, the IFR Probability field suggests multiple cloud layers are present. IFR Probabilities are smaller here because satellite-based cloud information cannot be used in the algorithm in regions where high/mid-level clouds preclude a satellite’s view of low stratus and fog. It is important to interpret the IFR Probability fields with knowledge of the cloud levels that are present. Towards the middle of the loop, fog develops in/around Midland over the high Plains. IFR Probabilities are large there because satellite data are used as a predictor because high clouds are not impeding the satellite’s view of the developing region of fog/stratus. Brightness Temperature Difference Fields from GOES, below, show the difficulty in using that field to detect fog/low stratus in regions where multiple cloud layers exist. There are many stations underneath high clouds that have undetectable (via satellite) IFR conditions.

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GOES-13 Brightness Temperature Difference (10.7µm – 3.9µm), 0245 – 1215 UTC 4 February 2015 (Click to enlarge)

 

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Toggle between GOES-based and MODIS-based IFR Probabilities at 0915 UTC on 4 February 2015 (Click to enlarge)

MODIS data from Aqua can also be used to compute IFR Probabilities, as shown above. In general, there is very good agreement between GOES and MODIS-based fields, but there are some very interesting differences along the limb of the MODIS scan in central TX where GOES data shows smaller values of IFR Probabilities than is shown in the MODIS fields — for example at San Angelo (KSJT), Kirksville (KCOM) and Brady (KBBD). This occurs in a region where limited observations show near-IFR conditions. The higher values along the limb of the MODIS scan are likely due to limb brightening that arises because the radiation being detected comes from a path that traverses more of the (colder) upper atmosphere. The affect is wavelength-dependent, and thus will show up in a brightness temperature difference field as a stronger signal, and that stronger signal will influence the IFR Probability fields. In short: interpret MODIS IFR Probability fields along the edge of the MODIS swath with this knowledge of limb effects.

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Brightness Temperature Difference (11.35 µm – 3.74 µm) from Suomi NPP at 0729 and 0910 UTC (Click to enlarge)

Suomi NPP also viewed the evolving fog/stratus field over Texas, and two brightness temperature difference fields, from sequential overpasses, are shown above. Brightness Temperature Difference fields can only give information about the top of the cloud, not the cloud base, and the cloud base is the important piece of information needed for fog detection. There are regions under the high clouds, for example, with IFR conditions. The eye is drawn by the enhancement to regions of low clouds/stratus, but important visibility restrictions are occurring elsewhere as well. The high resolution imagery of Suomi NPP does show compelling structures in the cloud fields, however. Note also the presence of limb brightening: Compare the brightness temperature fields west of Midland during the two times.

The Day Night Band from the morning of 4 February — near Full Moon — showed excellent structure in the cloud features, all made visible by ample lunar illumination as shown below. It is difficult, however, to use cloud-top information from the Day Night band to infer the presence of IFR conditions.

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Day Night Band (0/70 µm) from Suomi NPP at 0729 and 0910 UTC (Click to enlarge)

Fog over the Northern Plains

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Brightness Temperature Difference (10.7µm – 3.9µm) field from GOES-13, half-hourly from 0315 through 1445 UTC, 28 January 2015, along with surface observations of ceiling and visibility (Click to enlarge)

The traditional method of detecting fog/low stratus is the brightness temperature difference between the shortwave (3.9 µm) and longwave (10.7 µm) infrared channels on GOES. This identification scheme is based on the fact that water droplets do not emit shortwave radiation (3.9 µm) as a blackbody; because of that, the amount of shortwave radiation detected by the satellite is less than it would be if blackboard emissivity were occurring, and the inferred temperature (computed assuming blackboard emission) of the emitting cloud is therefore colder. Water droplets do emit longwave radiation more like a blackbody, so the 10.7 µm brightness temperature is warmer. If the satellite view of low clouds is blocked by cirrus, as above, or by mid-level clouds, then satellite detection of low clouds/fog is hampered or impossible. In the animation above, there are many regions of near-IFR or IFR conditions — low ceilings and reduced visibility — where the Brightness Temperature Difference Product gives no indication that fog/low stratus exists.

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GOES-R IFR Probability fields from GOES-13, half-hourly from 0315 through 1415 UTC, 28 January 2015, along with surface observations of ceiling and visibility (Click to enlarge)

GOES-R IFR Probability fields, above, better capture the horizontal extent of the low ceilings and reduced visibilities. This is because surface data is incorporated into the fields via output from the Rapid Refresh Model output. IFR Probabilities are heightened where the Rapid Refresh Model shows saturation (or near saturation) near the surface, and that includes regions under high/middle clouds, such as the Red River Valley between Minnesota and North Dakota. That model data are controlling the value of the IFR Probability field in those regions is apparent because of two things: (1) The field is horizontally uniform, and not pixelated as it is in regions where higher-resolution satellite data can be used; (2) IFR probability values are smaller because there is less certainty that low clouds are present because the satellite cannot detect them. A well-trained user of this product, then, will interpret IFR Probability values of around 50-60 percent differently in regions of high clouds vs. in regions where low clouds only are present. Note the obvious line in the fields at 1415 UTC — the last image in the animation. This is the boundary between night-time predictors (to the north and west) and daytime predictors (to the south and east). Generally, IFR Probabilities increase as the sun rises because visible satellite data can be used to distinguish between clear and cloudy skies. If there is more certainty that clouds exist, then IFR Probabilities will be greater.

MODIS and Suomi NPP overflew this region and provided information about the clouds. GOES-R IFR Probability is not yet computed using Suomi NPP data; the brightness temperature difference product (11.35 – 3.74), below, shows the widespread cirrus over the region during two sequential overpasses. Scattered breaks allow identification of low clouds. As with any brightness temperature difference product, however, the information is about the top of the cloud, not necessarily the cloud base.

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Brightness Temperature Difference (11.35 µm – 3.74 µm) field from Suomi NPP at 0800 and 0941 UTC 28 January 2015, along with surface observations of ceiling and visibility (Click to enlarge)

Aqua MODIS estimates of fog are shown below at 0728 and 0907 UTC. Detection using the Brightness Temperature Difference field is hampered by cirrus clouds. IFR Probability fields identify regions under cirrus that show IFR conditions.

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MODIS Brightness Temperature Difference field and MODIS-based GOES-R IFR Probabilities, 0728 UTC 28 January, with surface observations of ceilings and visibility (Click to enlarge)

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MODIS Brightness Temperature Difference field and MODIS-based GOES-R IFR Probabilities, 0907 UTC 28 January, with surface observations of ceilings and visibility (Click to enlarge)

Traffic-snarling fog in Huntsville, Alabama

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Dense fog developed over the Tennessee River Valley during the morning hours of 16 January 2015, causing crashes and traffic and school delays. The screenshot above (from this link), from WHNT in Huntsville, shows the conditions.

IFR Probability Fields, below, show a large stratus deck moving southward over Alabama, moving south of Hunstville by 0700 UTC. Clear skies allowed additional cooling and a radiation fog developed. The fog impeded transportation in and around Huntsville. IFR Probabilities increased around Huntsville after the large-scale stratus deck moved out, and remained high until around 1500 UTC when all fog dissipated. IFR Probability fields are computed using both satellite data and Rapid Refresh Model data. That IFR Probability is high over Huntsville and surroundings as the fog develops says that satellite data suggests water cloud development and that model data suggests near-surface saturation.

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GOES-R IFR Probabilities, half-hourly imagery, 0415-1645 UTC, 16 January 2015 (Click to enlarge)

The fog was also diagnosed using traditional detection methods, such as the brightness temperature difference field from GOES-13 shown below. Brightness Temperature Difference fields detect both fog and elevated stratus, and it’s difficult for satellite data-only products to distinguish between the two cloud types because no surface information is included in a simple brightness temperature difference field.

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GOES-13 Brightness Temperature Differences (10.7µm – 3.9µm), half-hourly imagery, 0410-1645 UTC, 16 January 2015 (Click to enlarge)

For a small-scale event such as this, polar orbiting satellites can give sufficient horizontal resolution to give important information. MODIS data from Terra or Aqua can be used to compute IFR Probabilities, and a toggle between the MODIS brightness temperature difference field, and the MODIS-based IFR Probabilities at 0704 UTC is below; unfortunately, Terra and Aqua were not overhead when the fog was at its most dense, but a thin filament of fog/High IFR Probability is developing south of Huntsville in a river valley.

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MODIS Brightness Temperature Difference and MODIS-based IFR Probabilities at 0704 UTC on 16 January 2015 (Click to enlarge)

Suomi NPP was positioned such that northern Alabama was viewed on two successive orbits, and the toggle below shows the brightness temperature difference field (11.35 – 3.74). Similar to GOES, Suomi NPP Brightness Temperature Difference fields show the development of water-based clouds in/around Huntsville.

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Suomi NPP Brightness Temperature Difference fields at 0645 and 0828 UTC, 16 January 2015 (Click to enlarge)

Sharp edge to Fog/Low Stratus over east Texas

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Brightness Temperature Difference Fields (10.7µm – 3.9µm) and surface observations of ceilings and visibilities, Hourly from 0200 through ~1400 UTC [Click to enlarge].

Traditional method of fog/low stratus detection revealed a sharp edge to clouds over east Texas during the morning of 29 December 2014. The animation above reveals several difficulties inherent in using brightness temperature difference fields in diagnosing fog/low stratus. Where multiple cloud layers are present — such as along the coast at 0500-0600 UTC — the brightness temperature difference product cannot view the low clouds. At sunrise, increasing amounts of solar 3.9µm radiation causes the brightness temperature difference product to flip sign. The signal for low clouds is still there, however.

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GOES-R IFR Probabilities and surface observations of ceilings and visibilities, Hourly from 0200 through ~1400 UTC [Click to enlarge]

The animation of GOES-R IFR Probabilities, above, created from GOES-13 data and Rapid Refresh Model data, shows high IFR Probabilities over east Texas where low ceilings and reduced visibilities prevailed, including metropolitan Houston. The algorithm suggests the likelihood of fog/low stratus underneath the cirrus debris that is over the coast around 0500-0600 UTC as well, because the Rapid Refresh model output in that region strongly suggests low-level saturation. In addition, the fields show only minor changes through sunrise (the effect of the terminator is present in the final image in the loop).

MODIS data from either Terra or Aqua can be used to produce IFR Probabilities. The data below is from 0442 UTC. Polar orbiter data is infrequent, however, so temporal monitoring of the fog/low clouds is more easily achieved using GOES data.  MODIS data, like the GOES data above, shows the effects of cirrus clouds on Brightness Temperature Difference fields and on IFR Probabilities.  Cloud predictors of low clouds/fog from satellite cannot be used in regions of cirrus, so IFR Probabilities are smaller in regions where multiple cloud layers exist, which regions are where only Rapid Refresh Data can be used as predictors.

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0442 UTC MODIS-based brightness temperature difference and IFR Probability fields (Click to enlarge)

 

Brightness Temperature Difference fields can also be created from Suomi/NPP data and the orbital geometry on 29 December meant that eastern Texas was viewed on two sequential overpasses.  IFR Probabilities are not quite yet computed using Suomi NPP data, but the brightness temperature difference fields can be used to show where water-based clouds exist. They show a very sharp western edge to the clouds.

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Brightness Temperature Difference Fields (11.35µm – 3.74µm) from Suomi NPP at 0723 and 0904 UTC on 29 December 2014 (Click to enlarge)

The Day Night Band on Suomi NPP produces visible imagery at night. When lunar illumination is strong, it can provide compelling imagery. On 29 December 2014, however, the moon set around 0600 UTC, so no lunar illumination was available, and fog/low clouds are very difficult to discern in the toggle below between the Day Night Band and the brightness temperature difference field at 0723 UTC.

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Day Night Band and Brightness Temperature Difference Fields (11.35µm – 3.74µm) from Suomi NPP at 0723 on 29 December 2014 (Click to enlarge)

 

Fog over the Southern Plains

Fog developed over Texas, Oklahoma and Arkansas early in the morning of 9 December 2014. Multiple cloud layers made traditional satellite detection (that is, using brightness temperature difference field (10.7µm – 3.9µm)) problematic. How did the fused product, GOES-R IFR Probability perform? The animation below shows the hourly evolution of IFR Probability from 0215 UTC through 1415 UTC.

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GOES-R IFR Probabilities, hourly from 0215 through 1415 UTC on 9 December 2014, along with surface plots of ceilings and visibilities (Click to enlarge)

There are widespread reports of IFR conditions over southeast Oklahoma and northern Texas, as well as over Arkansas in the Arkansas River Valley. IFR Probability fields generally overlap the region of reduced ceilings and visibilities.

Note that the probabilities increased over west Texas between 1315 and 1415 UTC. The boundary between day and night predictors is also apparent at 1415 UTC as a SW to NE line over the Texas Panhandle. Probabilities change as night switches to day because different combinations of satellite predictors can be used. In particular, the use of visible imagery improves cloud clearing and therefore IFR Probabilities increase in regions where low clouds exist (because the possibility of clouds being present is more easily detected).

The toggles below show data from 0615, 1115 and 1415 UTC and demonstrate why a fused product can give better information than a satellite-only product. Intermittent high clouds over the southern Plains prevented GOES-13 from identifying regions of low clouds (Cirrus clouds in the enhancement below appear as dark regions). IFR Probabilities can give valid information in these regions because the Rapid Refresh Model gives information about the possibility of low-level saturation. There are large regions at 1415 UTC over west Texas that are covered by cirrus clouds; despite the inability of the satellite to detect low clouds, IFR Probability maintains a strong signal there where IFR Conditions are occurring. The 1415 Brightness Temperature Difference field, in contrast to the IFR Probability field, gives very little information because increasing amounts of solar radiation are changing the relationship between 10.7µm and 3.9µm radiation at 1415 UTC.

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GOES-R IFR Probabilities and GOES-13 Brightness Temperature Difference Fields (10.7µm – 3.9µm), 0615 UTC on 9 December 2014, along with surface observations of ceilings and visibilities (Click to enlarge)

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As above, but at 1115 UTC (Click to enlarge)

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As above, but at 1415 UTC (Click to enlarge)

A near-Full Moon on 9 December means that the Day Night Visible imagery from Suomi NPP produced great imagery of the clouds over the southern Plains. The toggle below shows the Day Night band, the brightness temperaure difference field (11.35µm – 3.74µm) and the topography. Very narrow fog banks are apparent over southeast Oklahoma and over Arkansas, nestled into narrow valleys. The Brightness Temperature Difference field distinguishes between water-based clouds (presumably low stratus or fog) in orange and ice clouds (cirrus) in black.

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Suomi NPP Brightness Temperature Difference (11.35µm – 3.74µm) fields, Day Night band imagery and Color-shaded topography, 0839 UTC 9 December 2014 (Click to enlarge)

The fog event over Dallas was photographed from the air: Link.