Author Archives: Scott Lindstrom

Fog and Stratus over the Northern Plains

GOES-R IFR Probability Fields, 0345-1345 UTC on 21 December 2015 (Click to enlarge)

The National Weather Service in Bismarck issued Dense Fog Advisories for a fog and freezing fog early in the morning on December 21 (Happy Solstice!!) 2015. (Link). The half-hourly animation above shows the GOES-R IFR Probability during the overnight hours of 20-21 December 2015. (Here is a faster animation). Several aspects of this animation warrant comment. First, the western edge of the IFR Conditions matches well with the western edge of highest IFR Probabilities over North Dakota. This is true even as high clouds (obvious in the animation of Brightness Temperature Difference, below) move over North Dakota from the west: When this happens, IFR Probabilities decrease (and the field itself becomes more horizontally uniform) because Rapid Refresh Model Data output is the main predictor being used to diagnose the IFR Probability. The edge of the IFR Probability field moves through Dickinson ND (in the southwest part of the state) as the ceilings and visibilities there improve.

In addition, a persistent region of small IFR Probabilities exists over northern Minnesota in a region where IFR conditions are not reported. The Brightness Temperature Difference field there (below) shows a strong signal. (Click here for a faster animation of Brightness Temperature Difference) Thus, GOES-R IFR Probability is better able to differentiate between mid-level stratus and low stratus/fog. Over northern Minnesota, the Satellite data says water-based clouds are present, but the Rapid Refresh data notes little saturation in the lowest 1000 feet of the model. Thus, IFR Probabilities are small there.

GOES-13 Brightness Temperature Difference Fields (10.7 µm – 3.9 µm), 0345-1345 UTC on 21 December 2015 (Click to enlarge)

Fog vs. Stratus over the Pacific Northwest

Brightness Temperature Difference (10.7 µm – 3.9 µm) from GOES highlight regions of water-based clouds: water-based clouds emit 10.7 µm radiation nearly as a blackbody does, but those clouds do not emit 3.9 µm radiation as a blackbody. Thus, the brightness temperature computed from the radiation detected by the satellite (GOES-15 in this case) — a computation that assumes a blackbody emission — is relatively cooler for the 3.9 µm data compared to the 10.7 µm data. A water-based cloud is normally stratus, and the pertinent question for aviation purposes (for example) is: Is the ceiling of that cloud near the surface? (That is: Is the stratus also a fog bank, or is it “just” mid-level stratus?)

GOESIFRP_BTD_15December2015_0500UTCtoggle

GOES-15 Brightness Temperature Difference (10.7 µm – 3.9 µm) and GOES-based GOES-R IFR Probabilities, 0500 UTC 15 December 2015 (Click to enlarge)

The toggles above (0500 UTC) and below (0900 UTC) show how the GOES-R IFR Probability fields capably screen out many regions of mid-level stratus. This is achieved by fusing the brightness temperature difference information with data from the Rapid Refresh Model. If the lowest 1000 feet of the Rapid Refresh Model is not near saturation, probabilities of IFR conditions are reduced.

GOESIFRP_BTD_15December2015_0900UTCtoggle

As above, but at 0900 UTC 15 December 2015 (click to enlarge)

GOESIFRP_BTD_15December2015_1200UTCtoggle

As above, but at 1200 UTC 15 December 2015 (click to enlarge)

Toggles from 1200 UTC (above) and 1400 UTC (below) continue to show IFR Conditions mostly confined to regions near the Willamette Valley in eastern Oregon — banked up against the higher terrain to the east of the Willamette, and also over the higher terrain of northeastern Oregon (Click here for a toggle between the 1400 UTC IFR Probability field and Topography). IFR Conditions are a function of ceilings above ground (not above Mean Sea Level), so it’s important to recognize the influence of topographic features on an IFR Probability field. Fog/Low stratus can bank up against a topographic feature, and/or it can shroud the top of a topographic feature.

Note also how at 1400 UTC high clouds have impinged upon extreme northwest Oregon and coastal western Washington. In these regions IFR conditions nevertheless persist under the high clouds, but satellite data alone does not indicate low cloudiness. In this region, the inclusion of Rapid Refresh data in the GOES-R IFR Probability algorithm allows the IFR Probability field to continue to provide useful information about the presence of fog/low stratus.

GOESIFRP_BTD_15December2015_1400UTCtoggle

As above, but at 1400 UTC 15 December 2015 (click to enlarge)

MODIS and Suomi NPP afforded high-resolution images of the fog/stratus banks over the Pacific Northwest on 15 December. The brightness temperature difference fields and MODIS-based IFR Probability fields from MODIS at 0533 and 0945 UTC, below, support the observations from the coarser-resolution GOES fields above.

MODISIFRP_BTD_15December2015_0533UTCtoggle

As above, but for MODIS data at 0533 UTC 15 December 2015 (click to enlarge)

MODISIFRP_BTD_15December2015_0945UTCtoggle

As above, but for MODIS data at 0945 UTC 15 December 2015 (click to enlarge)

GOES-R IFR Probability fields are not yet computed using data from the Suomi NPP Satellite, but the Day Night band and the Brightness Temperature Difference field give information about the presence of cloudiness. For the case of Suomi NPP data, however, it’s more important to consider surface-based observations to confirm regions of low clouds/fog or mid-level stratus. Note also that December 15 was shortly after a New Moon, and the crescent moon that could give illumination was below the horizon (that is, it had set) at 0918 and 1059 UTC.

Note that Suomi NPP Near-Constant Contrast Day Night Band imagery was scheduled to start flowing in to AWIPS II on 14 December 2015 via the SBN. It should be available in NWS offices now.

SNPPBTD_DNB_15December2015_0918UTCtoggle

Suomi NPP Day Night Band Visible Imagery (0.70 µm) and Brightness Temperature Difference (10.35 µm – 3.74 µm), 0918 UTC 15 December 2015 (Click to enlarge)

SNPPBTD_DNB_15December2015_1059UTCtoggle

Suomi NPP Day Night Band Visible Imagery (0.70 µm) and Brightness Temperature Difference (10.35 µm – 3.74 µm), 1059 UTC 15 December 2015 (Click to enlarge)

Dense Fog over New England

GOES-13 Brightness Temperature Difference Fields (10.7 µm – 3.9 µm), hourly from 0515 through 1315 UTC 11 December 2015 (Click to enlarge)

The brightness temperature difference field (10.7 µm – 3.9 µm), above, over New England during the morning of 11 December 2015 shows extensive cirrus cloud cover (a hole in the high clouds moves over Southern New England just before sunrise). Surface observations of ceilings and visibility show widespread IFR conditions, yet cirrus and mid-level clouds prevent a diagnosis of the low clouds.

GOES-R IFR Probability fields for the same times, below, do show a strong signal (that is, higher probability of IFR conditions) in regions where IFR conditions are observed or where they have recently developed. Because GOES-R IFR Probability fields incorporate information from the Rapid Refresh about low-level saturation. Even if clouds decks obscure the view of near-surface clouds, as in this case, GOES-R IFR Probability fields, because they fuse together satellite data and surface information from the Rapid Refresh model, can provide useful information.

GOES-R IFR Probability Fields, hourly from 0515 through 1315 UTC 11 December 2015 (Click to enlarge)

Central Valley Fog under High Clouds

A potent storm in the Gulf of Alaska (Link to surface map) is allowing high clouds to spread inland over much of the west coast of the United States. Dense fog has formed underneath that cloud deck in the California’s Central Valley, and advisories have been issued (Scroll down to see the screen-grab of the NWS Sacramento Office Website). How can satellite products be used to detect such a fog that is hidden by high clouds?

The toggle below shows the GOES-15 Brightness Temperature Difference fields (with a pattern characteristic of mostly high (ice) clouds with a few breaks in the high cloud allowing the satellite to view lower water-based clouds) and the GOES-R IFR Probability field. IFR Probability is correctly alerting any forecaster to the probability that IFR conditions are occurring in the Central Valley. IFR Probability fuses information from the Satellite (not particularly helpful in this case) and information from the Rapid Refresh Model predictions of low-level saturation. The Rapid Refresh is correctly diagnosing the presence of saturation, and IFR Probabilities are enhanced over the Central Valley.

GOES-15 Brightness Temperature Difference and GOES-R IFR Probability fields, 1115 UTC on 8 December 2015 (Click to enlarge)

A Blend of Fog and Stratus over the Midwest

GOES-13 Brightness Temperature Difference (10.7 µm – 3.9 µm) fields (color enhanced) and GOES-R IFR Probability fields, and surface observations of ceilings and visibilities, 0200 UTC on 4 December 2015 (Click to enlarge)

Consider the toggle above between GOES-13 Brightness Temperature Difference and GOES-R IFR Probability fields at 0200 UTC on 4 December over the Midwest. (A surface map from 1200 UTC on 4 December shows High Pressure stretched across Ohio and Indiana). IFR Conditions are not reported over Ohio, Indiana or Illinois above. Would you expect them to form? And where? The GOES-R IFR Probability product is distinguishing between low stratus (not quite fog) over Indiana/Illinois and mid-level stratus over Ohio. How do things evolve through the night?

The 0500 UTC image, above, shows IFR conditions reports over south-central Illinois as ceilings lower and visibility degrades under the High Pressure System. By 1000 UTC, below, the IFR Conditions over Illinois are more widespread and near-IFR conditions are present over much of Indiana. Meanwhile, in Ohio, mid-level stratus continues.

By 1215 UTC, IFR conditions have developed over Indiana just before sunrise. Note also the development of IFR conditions along the Ohio River, and that low ceilings did not develop in Michigan (despite the high IFR Probabilities) where winds never relaxed. Use the IFR Probability fields in concert with other observations to make a nearcast/forecast. This case is a good example of using IFR Probabilities as an alert to where IFR conditions may be developing (in addition to the discrimination between low stratus/fog and mid-level fog that is frequently discussed on this blog). IFR Probability can be interpreted as a probability that IFR conditions exist at present or will be existing presently.

High Cirrus over west Texas and Fog on the Ground

GOES-based GOES-R IFR Probabilities and GOES-13 Brightness Temperature Differences (10.7 µm – 3.9 µm), 1100 UTC on 30 November 2015 (Click to enlarge)

Extratropical cyclones are accompanied most time with multiple clouds levels. In the example above, a cirrus shield accompanies a subtropical jet over the southern boundary of the United States. That cirrus prevents the satellite from seeing any low clouds that may be present. To detect/diagnose low clouds and fog in such regions, other data sets must be used. For GOES-R IFR Probability fields (shown in the toggle above), that other data set is low-level saturation in the Rapid Refresh model. If the model suggests saturation is present, IFR Probability fields will show a strong signal even where cirrus shields prevent the satellite from viewing water-based clouds near the surface. That is the case above. IFR conditions are widespread in the scene above are are diagnosed quite well by the IFR Probability fields.

Are IFR Conditions Present?

Suomi NPP Visible (0.70 µm) Day Night Band Imagery and Infrared Brightness Temperature Differences (11.45 µm – 3.74 µm), 0731 UTC on 24 November 2015 (Click to enlarge)

Low clouds (with a sharp southern edge) were over northern Wisconsin during the early morning of 24 November 2015. Are IFR Conditions present? Can you tell from the satellite imagery alone? The cloud bank stretched over northern Wisconsin seems thick compared to the bank of clouds over northeastern Wisconsin (centered on southern Green Bay). The city lights of Duluth are not visible in the same way that the city lights of Green Bay are in the Day Night band imagery. Clouds in general are distinct with the near-full moon providing ample illumination.

Both GOES and MODIS Brightness Temperature Difference fields, below, show a signal consistent with low clouds over most of northern WI and adjacent regions. But are there IFR Conditions?

GOES-13 Brightness Temperature Difference (10.7 µm – 3.9 µm) Fields (0730 UTC) and MODIS Brightness Difference Fields (11 µm – 3.9 µm) (0749 UTC)

IFR Probability fields blend the information available from satellite (are water-based clouds present?) with model output to yield a refined diagnostic of IFR Conditions. If there is saturation in the lowest levels (the lowest 1000 feet) of the model, then Probabilities of IFR Conditions are increased. If the lowest levels of the model are relatively dry, in contrast, then IFR Probabilities are reduced. On the morning of 24 November, the latter condition occurred over northern Wisconsin. IFR Probabilities computed from MODIS and GOES-13 satellite values are shown below. Probabilities are very low over most of Wisconsin where mid-level stratus (with varying bases) was present: IFR conditions were not generally observed in the regions where water-based clouds were indicated by the satellite. Mid-level stratus can look, from the top, very similar to fog, but it’s impossible for the satellite alone to discern what’s happening at the cloud base. Model data helps the IFR Probability algorithm screen out regions where mid-level stratus is occurring.

MODIS-based GOES-R IFR Probabilities (0751 UTC), GOES-13-based GOES-R IFR Probabilities (0731 UTC), and GOES-based GOES-R IFR Probabilities with surface observations of ceilings and visibilities (Click to enlarge)

Freezing Fog over Minnesota

GOES-R IFR Probability fields, hourly from 0515 through 1300 UTC on Sunday 22 November 2015 (Click to enlarge)

On Sunday 22 November, fog developed over west-central Minnesota with sub-freezing temperatures on the ground. The animation of the GOES-R IFR Probability fields, above, shows the slow enlarging of highest probabilities in the region around Glenwood and Alexandria where IFR Conditions were observed.

The Brightness Temperature Difference fields, below, show a signal over much of the region. One of the benefits of GOES-R IFR probability fields is that the use of Rapid Refresh model output screens out regions where mid-level stratus is more likely. Only regions in the model that have low-level saturation show the highest IFR Probabilities. GOES-R IFR Probabilities also give a consistent signal for IFR conditions when high clouds move over a surface fog. At the end of the animation above, probabilities decrease somewhat in regions over western Minnesota where high clouds are encroaching. Those high clouds prevent the brightness temperature difference field, below, from detecting surface fog.

GOES-13 Brightness Temperature Difference Fields (10.7µm – 3.9µm), hourly from 0515 through 1300 UTC on Sunday 22 November 2015 (Click to enlarge)

IFR Conditions with a strong extratropical Cyclone

GOES-R IFR Probability Fields (from GOES-13 and the Rapid Refresh Model), 1300 and 1400 UTC on 12 November 2015 (click to enlarge)

Strong Extratropical Cyclones, such as the one affecting the central and eastern United States on 11-12 November 2015 (1200 UTC Map on 12 November is here), generate multiple levels of clouds that make it difficult to detect fog/low stratus from satellite, because intervening cloud layers get in the way. GOES-R IFR Probability fields, however, because they incorporate near-surface information from the Rapid Refresh Model, can yield useful information about the likelihood of IFR Conditions. The toggle above shows data at 1300 and 1400 UTC over the northeast United States. Highest IFR Probabilities are removed from the coastlines of New England — as observations confirm. Note how the Adirondack and Catskill regions have higher probabilities, where terrain is reaching up into the stratus deck. Features in the IFR Probability field are strongly related to surface-based observations of fog and low stratus.

The toggle below shows IFR Probability fields and GOES-13 Brightness Temperature Differences as 1300 UTC. Features in the brightness temperature difference field have no relationship to surface-based observations of fog and low stratus.

GOES-R IFR Probability Fields (from GOES-13 and the Rapid Refresh Model) and GOES-13 Brightness Temperature Difference fields (10.7µm – 3.9µm), 1300 UTC on 12 November 2015 (click to enlarge)

Fog over Kansas

GOES-R IFR Probabilities (Upper left, computed from GOES-13 and lower left, computed from GOES-15), GOES-13 Brightness Temperature Difference fields (10.7 µm – 3.9 µm, Upper right) and GOES-R Cloud Thickness (Lower Right), hourly from 0500 through 1300 UTC 10 November 2015 (Click to enlarge)

Dense Fog Advisories were hoisted over western Kansas in response to the development of dense fog in the early morning on 10 November 2015. The hourly evolution of GOES-R IFR Probabilities (top left, bottom left), GOES-13 Brightness Temperature Difference fields (10.7 µm – 3.9 µm, upper right) and GOES-R Cloud Thickness fields (Bottom right) are shown above.

Both IFR Probability fields show highest probabilities over western Kansas where observations report IFR conditions. Portions of northern, central and eastern Kansas have strong returns in the GOES-13 Brightness Temperature Difference field, but IFR Probabilities are small and IFR conditions are not reported. In these regions, Rapid Refresh Model model output does not show low-level saturation and the IFR Probability algorithm correctly recognizes that IFR conditions are not likely despite the presence of stratus. It is the fusing of data in this way that gives the GOES-R IFR Probability field superior statistics (compared to the Brightness Temperature Difference field) in fog/low cloud detection.

Maximum cloud depth observed is more then 1200 feet. This suggests a long time before fog dissipation unless winds increase over Kansas.

GOES-R IFR Probabilities based on GOES-West show somewhat higher values than those based on GOES-East data; this difference arises because of the very oblique view of Kansas from GOES-15.

GOES-R Fog Product Examples

Fog detection fusing GOES, Terra/Aqua or Suomi/NPP Satellite data with Model output