Category Archives: Deep South

Identifying regions of fog under cirrus

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GOES-R IFR Probabilities computed from GOES-13 and GOES-East Brightness Temperature Differences (10.7 µm – 3.9 µm) at 0500 UTC on 5 March 2014 (click to enlarge)

Fog developed overnight over Tennessee on March 5th, but Cirrus clouds prevented the traditional brightness temperature difference product from observing low-level water-based clouds. It is for events like this that the IFR Probability fields (that incorporate surface-based information by way of the Rapid Refresh Model) is important. The IFR Probability fields use predictors from the Rapid Refresh model to showcase where low ceilings and reduced visibilities are most likely. Satellite predictors are unavailable where cirrus clouds are present and the probability field shows lower values. So when you see low values, make sure you understand why the values are low: is it because cirrus clouds are present?

A side-by-side animation of the IFR Probabilities and the Brightness Temperature Difference Field is presented below. The effects of cirrus on the Probability field is obvious.

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GOES-R IFR Probabilities computed from GOES-East (left) and GOES-East Brightness Temperature Differences (10.7 µm – 3.9 µm) (right), hourly from 0500 UTC through 1515 UTC on 5 March 2014 (click to enlarge)

IFR Probability Fields are an early-alert for Developing Fog

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GOES-R IFR Probabilities from 0400 through 1400 UTC on 14 February 2014 (click image to enlarge)

Fog and Low clouds resulted in IFR conditions along a long swath of the western Gulf Coast today. IFR Probability fields warned of the development of these conditions long before a strong signal appeared in the traditional brightness temperature difference fields. The animation above, of hourly GOES-R IFR Probability fields (and surface observations of ceiling and visibility). There are indications by 0615 and 0702 that fog/low stratus is developing, and those indications are matched by some observations of IFR conditions. By 0915 UTC, widespread IFR conditions are present from southwest Louisiana southwestward through coastal Texas.

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GOES-R IFR Probabilities, MODIS IFR Probabilities, and MODIS Brightness Temperature Difference fields, all from ~0845 UTC 14 February 2014 (click image to enlarge)

MODIS data can be used to generate IFR Probabilities as well, as shown above. The MODIS-based and GOES-based fields both generally overlap regions with developing IFR conditions. The MODIS-based Brightness temperature difference product (called MODIS FOG in the image annotation) shows little signal in central Louisiana/east Texas (near Lufkin, for example) or southwest of Houston, two places where near-IFR conditions are developing (and where the IFR Probability fields have a signal).

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GOES-R IFR Probabilities, MODIS IFR Probabilities, and MODIS Brightness Temperature Difference fields, all from ~0845 UTC 14 February 2014 (click image to enlarge)

Suomi/NPP data (Brightness Temperature Difference fields, and the Day/Night band) from the same hour (0822 UTC) as the MODIS data similarly underpredicts the areal extend of the developing IFR conditions.

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GOES-Based GOES-R IFR Probabilities (Upper Left), GOES-East Brightness Temperature Difference Fields (Upper Right), GOES-R Cloud Thickness (Lower Left), GOES-East Visible Imagery (Lower Right), hourly from 0400 UTC through 1600 UTC 14 February 2014 (click image to enlarge)

The animation above shows hourly views of GOES-R IFR Probability and GOES-East Brightness Temperature Difference fields. There is little discernible signal in the brightness temperature difference field until about 0915 UTC (several hours after the IFR Probability field has been suggesting fog development). Thus the GOES-R IFR Probability field is giving better lead time is diagnosing where visibility restrictions might occur/be occurring. In addition, the GOES-R Cloud Thickness product shows that the thickest fog/stratus field just before sunrise is just east of Austin/San Antonio, and that is the last region to clear out after sunrise.

The presence of high clouds has an effect on both the IFR Probability fields and the brightness temperature difference field. When high clouds are present (in the brightness temperature difference enhancement used, high clouds are dark), IFR Probabilities drop in value and the field becomes flatter because satellite data cannot be used in the computation of the IFR Probability Field.

IFR Probabilities can identify frontal zones

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Hourly images of GOES-East IFR Probabilities and surface plots of visibilities/ceilings as well as 3-hourly HPC depictions of frontal positions, 0701 – 1515 UTC on 21 January 2014(click image to enlarge)

Frontal zones are often accompanies by lower visibilities, and the image above shows how IFR Probabilities march steadily eastward as a front marches eastward across the southern Gulf states. Thus, the IFR Probabilities can, at times, serve as a proxy for a frontal zone.

A Reminder about Co-Registration Errors

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GOES-R IFR Probabilities from GOES-13, times as indicated on 27 November 2013 (click image to enlarge)

The GOES-R IFR Probability field showed enhanced probabilities surrounding lakes and rivers in Louisiana and Texas overnight. This is in large part due to a strong signal in the Brightness Temperature Difference field. There is a co-registration error between the 10.7 µm and 3.9 µm detectors on the GOES Imager. This means that the pixel locations for the two channels are not aligned, and at times the mis-alignment is large enough that a fog signal is produced. In the present case, one of the detectors sees the warm waters of a lake, and the second detector sees the adjacent (much cooler) shoreline, but the navigation misalignment is such that both pixels are believed to be co-located. Thus a difference in the brightness temperature occurs not because of emissivity difference properties in clouds (which also makes the 3.9 micron brightness temperature appear cooler) but because of a co-registration error. The brightness temperature difference field from 0802 UTC is below (the 0745 UTC image is very similar). Note how the enhanced brightness temperature difference field appears to have a shadow just to its west. It is possible for this to occur if a cloud is forming downwind of a warm lake. However, in the present case, winds were primarily northerly, not westerly.

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GOES-13 Brightness Temperature Difference Product (10.7 µm – 3.9 µm) 0802 UTC 27 November 2013 (click image to enlarge)

Polar Orbiting satellites viewed this region contemporaneously. Aqua, carrying the MODIS instrument, passed overhead at 0745 UTC, and Suomi/NPP at 0802. What did they see? The 3.9 µm channel from MODIS, below, highlights the warm lake waters over eastern Texas and Louisiana. There is little indication in this image of clouds near the lakes.

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MODIS Brightness temperature at ~3.9 µm 0802 UTC 27 November 2013 (click image to enlarge)

The brightness temperature difference product from MODIS, below, and the MODIS-based IFR Probabilities also show no indication of fog/low stratus near the bodies of water in east Texas/Louisiana.

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MODIS Brightness temperature difference (11.0 µm – 3.9 µm) and MODIS-based IFR Probabilities at 0746 UTC 27 November 2013 (click image to enlarge)

Suomi/NPP data are shown below. The Brightness Temperature Difference (10.35 µm – 3.74 µm) Field, the 3.74 µm field and the Day/Night band all are consistent with clear skies near the water bodies of east Texas and western Louisiana.

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Suomi/NPP VIIRS Brightness Temperature Difference (10.35 µm – 3.74 µm) and Day/Night band at 0802 UTC 27 November 2013 (click image to enlarge)

Be cautious when interpreting the brightness temperature difference from GOES (and IFR Probabilities that are computed using the satellite signal) along land/water boundaries. GOES Engineers continue to investigate methods of mitigating this co-registration error.

Fog development over the lower Mississippi River valley as viewed by different satellites

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GOES-R IFR Probabilities computed from GOES-East (Upper Left), GOES-East Brightness Temperature Difference (10.7 µm – 3.9 µm) (Upper Right), GOES-R Cloud Thickness (Lower Left), GOES-East Visible Imagery (Lower Right), all images hourly from 0415 UTC through 1415 UTC 19 July 2013

Hourly imagery of GOES-R IFR Probabilities show the development of high probabilities in a region where low clouds and fog develop to cause IFR and near-IFR conditions in and around the lower Mississippi River Valley.  The traditional method of detecting low stratus will be hampered by an abundance of high and mid-level clouds (as evidenced in the brightness temperature difference product, above, and in the day/night band imagery, below).  Different polar-orbiting satellites can give snapshots at high spatial resolution that describe the fog/low cloud fields.  The Suomi/NPP overpass at  0715 UTC (early in the night for radiation fog development), shows the abundance of high clouds over the western part of the domain, for example, that are illuminated by the setting half-moon.  It is difficult to discern low clouds in regions where IFR probabilities are high.

As above, but with Suomi/NPP Day/Night Band (Bottom Right), 0715 UTC.

 MODIS data are used to produce IFR probabilities, and those images are shown below.  The later of the images matches the time of the Suomi/NPP band shown above.

As above, but with MODIS-based GOES-R IFR Probabilities (Lower Right), at 0445 and 0715 UTC 19 July 2013

MODIS-based IFR probabilities are higher than GOES-based probabilities over the west-central part of Mississippi where satellite data are included in the predictors.  This occurs when the MODIS-based satellite signal of low clouds is stronger than that from GOES, which difference in signal can occur because of the finer resolution of the MODIS data.  In central Arkansas and northern Louisiana, however, where high clouds are present (and therefore where Satellite data are not used in the computation of the IFR Probability), the GOES-based and MODIS-based fields are nearly identical.

AVHRR data (below) can also be used to compute brightness temperature differences, but those data are not yet incorporated into the GOES-R algorithms.  However, the trend of the brightness temperature difference field can be used to monitor trends in low clouds/fog.  High clouds will obscure the view, however.  It is very difficult to infer a change in the amount of fog, and the concomitant decreases in visibility, based on the brightness temperature difference changes displayed below.

As above, but with the AVHRR Brightness Temperature Difference (10.8 – 3.74), bottom right, at 0654 UTC, 0837 UTC and 1051 UTC on 19 July 2013.

Low clouds over Louisiana

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GOES-R IFR Probabilities computed from GOES-East (Upper Left), GOES-East Brightness Temperature Difference (Upper Right), GOES-R IFR Probabilities computed from MODIS data (Lower Left), GOES-R Cloud Thickness computed from GOES-East (Lower Right), every half hour from 0015 UTC to 1615 UTC on June 7 2013

GOES-R IFR Probabilities are shown for northwest Louisiana and surrounding states.  At the beginning of the animation, GOES-R fields are mostly model-based over much of Louisiana — the north-south oriented edge of high clouds is plain in the brightness temperature difference field starting around 0315 UTC, and the GOES-R IFR Probability field over Louisiana has the characteristic flat look of a field produced from mostly model (Rapid Refresh) data.  Note also that the Cloud Thickness product is not shown when high clouds are present.  It is computed only for low clouds in non-twilight conditions.

As the high and mid-level clouds move to the east, two things happen to the GOES-R fields. One, the Cloud Thickness field starts to show values.  And second, the GOES-R IFR Probability field starts to acquire the pixelated character that is common when satellite data are part of the field.

The are of high IFR probabilities is smaller than the region of enhanced brightness temperature difference, which at 0900 UTC covers much of Louisiana and Arkansas.  Over Arkansas, however, model data are de-emphasizing the possibility of reduced surface visibilities.  The low clouds there are stratus, off the ground, not fog.  Thus the IFR probability field gives a more accurate representation of where visibility restrictions at the surface are possible.  This is an important consideration in aviation forecasting.

As above, but for 0400 UTC (top) and 0815 UTC (bottom)

IFR Probabilities computed from MODIS data (lower left) show very similar areal coverage compared to the GOES-Based IFR probability fields, but small-scale variations in the field are much more evident, as should be expected given the difference in pixel footprint between the two satellites.

Fog Dissiplation over western Tennessee

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Late-in-the-day rains followed by clearing skies and light winds set the stage for radiation fog over much of western Tennessee early on April 5th.  The GOES-R Cloud Thickness product allows forecasters to estimate when radiation fog will burn off.

GOES-R IFR Probabilities computed with GOES-East data (Upper left), GOES-East traditional brightness temperature difference (Upper right), GOES-R Cloud Thickness Product (Lower Left), GOES-R IFR Probabilities computed with MODIS data (Lower right), hourly from 0415 UTC through 1115 UTC on April 5th 2013.

The animation above shows the retreat of rain clouds to the south and east, and the development of radiation fog.  The IFR Probabilities around 0815 UTC — both GOES and MODIS — suggest a separation between the low stratus that is over Mississippi and Alabama and the fog over western Tennessee (the stratus shifts eastward and the radiation fog quickly develops).

GOES-R Cloud Thickness can be used to predict when a radiation fog will burn off, using this chart and the final pre-twilight cloud thickness field (Cloud thickness is not computed during twilight conditions).  The last cloud thickness field image produced is shown below:

GOES-R Cloud Thickness, Friday 5 April 2013 at 1132 UTC

Fog/Cloud Thickness is greatest, a bit more than 1100 feet, in Fayette County just east of Memphis and in Henderson and Chester Counties a bit farther to the east and north.  Scatterplot points on the chart suggest that the fog could burn off in 3 or so hours after the 1132 UTC image above.  The visible loop animation, below, shows fog has cleared by 1432.

Visible imagery animation, 1232-1432 UTC on April 5 2013

Fog/Low Stratus Examples on both Coasts

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Two different systems — one approaching California, and one in the Gulf of Mexico — provide examples of how the GOES-R Fog/Low Stratus algorithm give information about visibilities and ceilings in regions where high clouds obscure the satellite view of low levels.

GOES-R IFR Probabilities computed from GOES-West, hourly, from 0700 through 1700 UTC 4 April 2013

The first case, off the West Coast, starts with a deck of high clouds over the coast associated with a landfalling cyclone.  IFR Probabilities over the Pacific near the California coast are initially derived solely from Rapid Refresh model data.  Consequently, IFR probabilities are not high.  As the cirrus shield pushes inland, low clouds become visible to the satellite, and when both satellite and model predictors are used to compute IFR Probabilities, higher probabilities are a result.  In addition, small-scale variability that is inherent in a satellite image (and perhaps not so inherent in model output) changes the character of the IFR Probability field from a flat field at the start to a more pixelated field later in the animation.  As the low clouds push onshore, associated moisture and precipitation helps to generate near-IFR and IFR conditions in regions where the IFR Probabilities are depicted to be high.

The second case, below, over the deep South, shows a region of fog/low clouds moving over Georgia as mostly model-based IFR Probabilities also move over the state.  Strong convection over the Gulf of Mexico produced abundant high-level cloudiness;  thus, IFR Probabilities could only be computed using Rapid Refresh Data over Georgia  — but the computed IFR Probabilities both outline the region of lowest ceilings/visibilities and match their slow spread to the north and east into South Carolina.  The IFR Probability field over Mississippi has a more pixelated look to it, and shows higher values, because satellite data are also used to diagnose the IFR Probability:  IFR Probabilities are highest only where both predictors (model and satellite) are used.

GOES-R IFR Probabilities computed from GOES-East, hourly, from 0702 UTC through 1745 UTC, 4 April 2013

IFR conditions with multiple clouds layers over the southeast US

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GOES-R IFR Probabilities from GOES-East (Upper Left), GOES-East Brightness Temperature Differences (Upper Right), GOES-R Cloud Thickness (Lower Left), Surface Observations of Ceilings and Visibility (Lower Right), all at 1000 UTC on 16 January 2013

A slowly-moving weather system brought extensive cloudiness and IFR and near-IFR conditions over the southeast part of the United States again on January 16, and provided a good example of how the fused nature of the GOES-R Fog/Low Stratus product — combining both satellite and model information — yields a better signal (than is available from the traditional brightness temperature difference product) of where fog and low stratus are most likely.  The imagery from 1000 UTC, which is characteristic of the entire event, shows a brightness temperature difference signal over the southest that is consistent with the observed multiple cloud layers.  Such a cloud configuration makes it very difficult to relate the brightness temperature difference signal to surface observations.  in contrast, the IFR Probability field show a widespread region of high probabilities, overlapping the regions of near-IFR and IFR observations over Tennessee, and points south.  Cloud thickness, which is computed only where single water-cloud layers are detected from satellite, indicates cloud thicknesses around 1000 feet.  Note that where the cloud thickness is diagnosed, in general, IFR probabilities are relatively larger.  This is because IFR probabilities combine satellite predictors and model predictors.  If the satellite predictors cannot be generated because of multiple cloud layers and/or a single high cirrus deck, then only the model predictors are driving the IFR probability value, and the probability will therefore be lower.  This is the case over western Tennessee and central Georgia.

The impact of higher clouds

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GOES-R IFR Probabilities computed from GOES-East (Upper Left), GOES-East Brightness Temperature Difference (10.7 µm – 3.9 µm) (Upper Right), GOES-R Cloud Thickness (Lower Left), GOES-East 10.7 µm Imagery (Lower Right) at 0700 UTC on 6 December 2012.

Upper-level clouds, such as those apparent in both the 10.7 µm imagery and the brightness temperature difference imagery, above, lower right and upper right, respectively, have an impact on the GOES-R IFR Probability and GOES-R Cloud Thickness products.  The most obvious impact is in the Cloud Thickness product (lower left), which product is not computed in regions where high clouds are present.  The GOES-R IFR Probabilities are computed underneath high clouds, using mostly Rapid Refresh model data to determine the probability of fog and low stratus.  However, because cloud predictors are not used, IFR probabilities are somewhat lower.  In addition, the character of the field is flatter, reflecting the smoother fields that are present in the model.  This is especially obvious over northeast Louisiana and extreme east Texas in the IFR Probability image above.  Thus, the heritage product, the brightness temperature difference, gives no information from southwest Louisiana northward into southern Arkansas, but the fused GOES-R IFR Probabilities do suggest enhanced possibilities of IFR conditions in regions where reduced visibilities are reported:  central and northeast Louisiana and east Texas.  IFR Probabilities are much lower over southwest Louisiana where IFR conditions are not reported.

As above, but for 1245 UTC on 6 December 2012.

By 1245 UTC, the high clouds have lifted northeast and dissipated somewhat, so the heritage brightness temperature difference product gives information over the entire lower Mississippi River valley and over east Texas, where IFR conditions were widespread underneath very high GOES-R IFR Probabilities.  The GOES-R Cloud Thickness product indicates cloud thicknesses up to near 1200 feet, suggesting a burn-off time for radiation fog of around 5 hours.

Day/Night Band (from Suomi/NPP) imagery over Louisiana and East Texas, 0733 UTC on 6 December 2012. 

 The Day/Night band image derived from data from Suomi/NPP from 0733 UTC on 6 December, above, shows the higher and lower clouds over Texas and Louisiana.  The clouds between Houston and Dallas/Ft. Worth are low clouds, but the high clouds over Louisiana inhibit the detection of low clouds.  In addition, although the Day/Night band can give a good outline of where the clouds are, it does not show where the visibility restrictions consistent with IFR conditions are.

Visible Imagery from 2000 UTC

Visible imagery from 2000 UTC, above, shows that, although the fog has lifted, it has not burned off in 5 hours as predicted by the thickness/burn-off time relationship (here).  This may be related to the very low sun angle in December.

(Added:  This image loop shows how thin cirrus can show up in the brightness temperature difference product at night (this example is from Suomi/NPP even when fog-bound valleys are plainly evident in the Day/Night band at the same time!)