Extensive wildfires (well-forecast by the Storm Prediction Center) occurred over the southern Plains on Thursday 18 February 2016, while GOES-14 was operating in SRSO-R mode. A comparison of 1-minute GOES-14 Visible (0.63 µm) and Shortwave Infrared (3.9 µm) images (above; also available as a large 112 Mbyte animated GIF) showed the broad areal coverage of smoke plumes and fire hot spots (dark black to yellow to red pixels) during the day over eastern Oklahoma.

Of particular interest was a rapidly-intensifying and fast-moving grass fire over northwestern Oklahoma, in Harper County just west-northwest of the town of Buffalo, which burned 17,280 acres (media report). Note the warm air temperatures as seen in the surface plots — the high of 90º F at Gage OK (KGAG, south of the fire) tied for the warmest February temperature on record at that site. A closer view of the Buffalo fire is shown above — county outlines are shown as dashed white lines, while US and State highways are plotted in violet (also available as a large 63 Mbyte animated GIF). The shortwave infrared images revealed the initial appearance of a color-enhanced fire hot spot (exhibiting an IR brightness temperature of 327.5 K) at 2045 UTC; three minutes later (at 2048 UTC), the IR brightness temperature had already increased to 341.2 K (red enhancement) which is the saturation temperature of the GOES-14 shortwave IR detectors. The hot spots could also be seen racing northeastward toward the Oklahoma/Kansas border, with the fire eventually crossing US Highway 183 (which runs south-to-north through Buffalo and across the Kansas border). The early detection and subsequent accurate tracking of such rapid fire intensification and propagation could only have been possible using 1-minute imagery.

The two plots below show GOES-14 pixel values of 3.9 µm IR brightness temperature at the initial Buffalo fire site (top plot, at 36:51º N, 99:48º W) and at a site just to the northeast (bottom plot, at 36:54º N, 99:43º W) through which the moving fire propagated. The blue line shows every value, nominally at 1-minute intervals. The red dots show points sampled every five minutes. Very small temporal scale changes in the fire cannot be captured with a 5-minute sampling interval.

 

For the Buffalo fire, a three-satellite comparison of Shortwave Infrared (3.9 µm) images from GOES-15 (operational GOES-West), GOES-14, and GOES-13 (operational GOES-East) is shown for the initial 30-minute time period 2030-2100 UTC (above). The images are displayed in the native projection of each satellite. In terms of the first unambiguous fire hot spot detection (via a hot color-enhanced image pixel) during that initial period, it would appear from the image time stamps that both GOES-14 and GOES-13 detected the fire at 2045 UTC — however, because GOES-14 was scanning a much smaller sector, it did indeed scan the fire at 20:45 UTC (while GOES-13 scanned the fire at 2049 UTC, 4 minutes after its larger scan sector began in southern Canada). Also note that there were no GOES-15 images during that 30-minue period between 2030 and 2100 UTC, due to the satellite having to perform various “housekeeping” activities — so if a NWS forecast office AWIPS were localized to use GOES-15, initial fire detection would not have been posible until reception of the 2100 UTC image (which actually scanned the fire at 2104 UTC).

A faster animation covering a longer 2.5-hour period from 2030-2300 UTC is shown below. Again, a true sense of the fast northeastward speed of fire propagation could only be gained using 1-minute imagery.

The animation above shows another view of 1-minute GOES-14 Shortwave Infrared (3.9 µm) imagery, centered over northeastern Oklahoma — in these images, the hottest fire pixels are darkest black. Time series of infrared brightness temperature values at two individual fire pixels (shown here) are plotted below. The Blue lines show the 1-minute data; Red dots show how 5-minute monitoring would have adequately captured the events. Pixel Brightness Temperature changes that occur on the order of 1 or 2 minutes are common, and peak values can be missed with 5-minute granularity.

In the GOES-R era, Fire Products will be produced every 5 minutes. Individual NWS Forecast Offices will be able to request Rapid-Scan Imagery (1-minute intervals) over a 1000 km x 1000 km mesoscale sector.

===== 19 February Update =====

Seen below are RealEarth comparisons of Aqua MODIS and Suomi NPP VIIRS true-color Red/Green/Blue (RGB) images from the early afternoon of 18 February (before the Buffalo OK fire) and 19 February (after the Buffalo OK fire), which revealed the long southwest-to-northeast oriented burn scar. As seen on the GOES-14 animation above, the fire crossed US Highway 183 just to the north of Buffalo (that portion of the highway was closed for several hours).

In addition, a comparison of Suomi NPP VIIRS true-color and false-color images (below) helps to discriminate between the darker burn scar and the cloud shadows seen on the true-color image — the Buffalo fire burn scar appears as varying shades of brown in both the true-color and the false-color images.

===== 27 February Update =====

A comparison of 30-meter resolution Landsat-8 false-color (created using OLI bands 6/5/4) RGB images from 18 February (about 3.5 hours prior to the start of the Buffalo OK fire) and 27 February (several days after the fire) provided a very detailed view of the burn scar. Note that a few green fields remained within the burn scar, and also appeared to prevent the spread of the fire along portions of its perimeter — this is a result of the vast difference between the very low moisture content of the dry grassland (which burned quickly and easily) and the high moisture content of the well-irrigated fields of winter wheat, alfalfa, and canola crops.

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GOES-13 Visible (0.63 µm, 1-km resolution) images (above) showed the development of lake effect snow bands across the Great Lakes region following the passage of a strong arctic cold front on 12 February 2016. As a result of the atmospheric instability (due to the advection of very cold air aloft), several distinct convective elements could be seen developing within a few of the lake effect bands —  especially over Lower Michigan where moderate to heavy snow was reported at some locations during brief snow squalls.

Many of these lake effect snow bands could also be seen on the corresponding GOES-13 Water Vapor (6.5 µm, 4-km resolution) images (below).

A comparison of 1-km resolution Aqua MODIS Visible (0.65 µm) and Water Vapor (6.7 µm) images at 1854 UTC (below) revealed much better detail of the lake effect cloud band features in the water vapor image.

Conventional wisdom states that water vapor imagery generally portrays features located within the middle to upper troposphere, due to the altitude of the peak of the water vapor channel weighting function calculated using a relatively warm and moist “US Standard Atmosphere” (plot). However, in air masses that are very cold and/or very dry, the altitude of the water vapor channel weighting function peak is shifted to much lower altitudes, allowing a look at features that are located in (or at least rooted within) the lower to middle troposphere. Such was the case on this day, with the flow of very cold and dry arctic air behind the cold front. A comparison of the GOES-13 imager* water vapor channel weighting function plots at 12 UTC for Green Bay WI (behind the cold front) and Detroit MI (ahead of the cold front) showed the dramatic drop in the peak altitude over Green Bay (below).

Similarly, a comparison of GOES-13 imager water vapor channel weighting function plots for Detroit MI at 12 UTC (before the passage of the cold front) and 00 UTC on 13 February (after the passage of the cold front) showed a sharp drop in the altitude of the weighting function peak. This allowed radiation emitted from the tops of the more pronounced and vertically-developed lake effect cloud bands to reach the water vapor detectors on the satellite.

*Note: there are also 3 unique water vapor channels on the GOES sounder instrument (6.5 µm, 7.0 µm, and 7.4 µm) — however, due to an ongoing problem with the GOES-13 sounder, said water vapor imagery was not available (as it was for this example). However, the ABI instrument on GOES-R will provide imagery from 3 separate water vapor channels that are similar to those found on the current-generation sounder (but at much higher spatial and temporal resolution).

Hat tip to @turnageweather for the suggestion to blog about this case!

Hey @CIMSS_Satellite, ystdy aftn very shallow lake effect clouds over Lower MI clearly seen on WV channel. Willing to blog on this? #miwx

— T.J. Turnage (@turnageweather) February 13, 2016

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Wheeler Lake is a reservoir along the Tennessee River in northern Alabama. The Aqua MODIS Sea Surface Temperature product (above) showed that water temperatures along the axis of the lake were as warm as the lower 50s F (cyan color enhancement) on 07 February 2016.

Following the passage of a strong cold front on 08 February, the northwesterly flow of air with surface temperatures in the 30s F on 09 February allowed for a narrow “lake effect” (or in this case, river effect) snow band to form over Wheeler Lake, which created accumulating snowfall to the southeast (downwind) of the lake. This lake effect snow band could be seen in a RealEarth composite of Suomi NPP VIIRS / Aqua MODIS true-color Red/Green/Blue (RGB) images and radar reflectivity (below). The lake effect plume began to shift northward during the afternoon hours, as surface winds briefly backed to a more westerly direction.

On 10 February, the northwesterly flow of cold air was less pronounced, but was still enough to allow for a narrow lake effect plume to be seen early in the day on 1-minute interval GOES-14 Super Rapid Scan Operations for GOES-R (SRSO-R) images (below; also available as a large 89 Mbyte animated GIF). As the clouds cleared during the afternoon hours, small patches of white snow cover could be seen just southeast of Wheeler Lake.

In a comparison of Terra MODIS true-color and false-color RGB images (below), the presence of snow cover (cyan in the false-color image) could be seen between the lines of cumulus clouds.

Data from NOHRSC (below) showed that as much as 3.0 inches of total snowfall was measured downwind of Wheeler Lake (in the higher elevation of the Union Hill area) during the 09-11 February period, and the snow depth on the morning of 10 February was 2.5 inches at that location (enough to be seen on the GOES-14 visible images above).

Additional information and images of this event can be found here.

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1-minute interval GOES-14 Super Rapid Scan Operations for GOES-R (SRSO-R) Visible (0.63 µm) images (above; also available as a large 71 Mbyte animated GIF) revealed the formation of clusters of aircraft “hole punch clouds” over central North and South Carolina on the morning of 09 February 2016. These types of cloud features form when aircraft fly through a layer of clouds composed of supercooled water droplets; cooling from wake turbulence (reference) and/or the particles from the jet engine exhaust which may act as ice condensation nuclei cause the small water droplets to turn into larger ice crystals (which then often fall from the cloud layer, creating “fall streak holes“). Similar features have been discussed in previous blog posts.

A comparison of GOES-14 Visible (0.63 µm, 1-km resolution) and Shortwave Infrared (3.9 µm, 4-km resolution) images (below; also available as a large 71 Mbyte animated GIF) offered evidence that the cloud material within each “hole punch” was composed of ice crystals, which exhibited colder (lighter gray) IR brightness temperatures than the surrounding supercooled water droplet clouds. It is likely that many of the hole punch features were caused by aircraft ascending from or descending to the Charlotte Douglas International Airport in North Carolina (KCLT).

In a comparison 1-km resolution POES AVHRR Visible (0.86 µm) and Infrared (12.0 µm) images (below), the cloud-top IR brightness temperatures in the vicinity of the hole punch features were only as cold as -20 to -24º C (cyan to blue color enhancement), which again is supportive of the cloud layer being composed of supercooled water droplets.

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