1-minute Mesoscale Domain Sector GOES-16 (GOES-East) Shortwave Infrared (3.9 µm), “Red” Visible (0.64 µm) and “Clean” Infrared Window (10.35 µm) images (above) showed that the Calf Canyon Fire in New Mexico produced a pyrocumulonimbus (pyroCb) cloud on 22 April 2022. This large fire burned very hot, with 3.9 µm Shortwave Infrared brightness temperatures reaching 138.71ºC — the saturation temperature of ABI Band 7 detectors. Very strong winds contributed to the rapid intensification and spread of this wildfire — the peak wind gust at nearby Las Vegas (KLVS) was 74 mph (NWS Albuqueque PNS).

10.35 µm images indicated that the pyrocumulus cloud-top infrared brightness temperatures first reached the -40ºC pyroCb threshold at 2334 UTC (below).

Cloud-top infrared brightness temperatures subsequently cooled to a minimum of -53ºC around 0022 UTC — which corresponded to an altitude of around 11.7 km according to rawinsonde data from Albuquerque (below).

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1-minute Mesoscale Domain Sector GOES-16 (GOES-East) Day Snow-Fog RGB and Near-Infrared “Snow/Ice” (1.61 µm) images (above) showed subtle signatures of a swath of hail covering the ground (initial storm report) — shades of red in the RGB images. and darker shades of gray in the 1.61 µm images — in the wake of a severe thunderstorm that was moving northeastward across western South Dakota late in the day on 22 April 2022. The combination of fading daylight and high clouds (and their shadows) passing overhead restricted the amount of time that this hail swath signature could be seen.

A slightly modified version of the Day Snow-Fog RGB — created using Geo2Grid — provided more contrast, making the hail swath a bit easier to see (below).

The corresponding 1-minute GOES-16 “Red” Visible (0.64 µm) and “Clean” Infrared Window (10.35 µm) images (below) revealed that this severe thunderstorm exhibited a prominent Above-Anvil Cirrus Plume (reference | VISIT training).

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A dryline over the United States High Plains will serve as a focus for convective development later in the day on 22 April. (Click here for the 1300 UTC Convective Outlook). What tools are available to view gradients of Total Precipitable Water, and how do they compare? The toggle above compares Gridded NUCAPS fields of TPW and roughly coincident GOES-16 derived Total Precipitable Water. (TPW can be viewed online here). A zoomed-in version of the image above is shown below (including an image showing NUCAPS Sounding Availability points). Note that NUCAPS gives values in regions of clouds. GOES-R has a higher spatial resolution. A user might use both to take advantage of the strengths of both sensors.

Of course, a benefit of GOES-R over NUCAPS values is that GOES-R estimates can animate. The 2-hour animation below shows a relatively stationary gradient over the High Plains from Texas northward through Kansas.

SPC Mesoanalyses at 0800 and 1000 UTC, below, similarly show a relatively stationary gradient. Perhaps the strength of the gradient is different in the analysis below compared to the satellite-based esimates above, but the different enhancements and map projections makes it difficult to make a direct comparison!

The NAM-12 image of TPW below also shows a tight gradient over the High Plains.

Gridded NUCAPS fields of TPW are also available at this RealEarth-driven site, and at this SPoRT site. The RealEarth field is shown below.

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The GOES-16 Total Precipitable Water at 1716 UTC, above, is a bit less concentrated over western Kansas. The image is also toggling with the Split Window Difference (10.3 µm- 12.3 µm) enhanced such that dark regions have more moisture. No appreciable gradient in moisture that might focus convection is apparent. (The 1630 UTC Convective Outlook has not appreciably changed from 1300 UTC). Note below how well the surface dewpoint gradients and TPW gradient match!

Continue to monitor the evolving moisture distribution using the resources above as the afternoon progresses.

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The Tunnel Fire north of Flagstaff offers an excellent example of why knowledge of Parallax with satellite features is important. In the animations above, note how the location of the warmest pixels are shifted: GOES-17 has the warmest pixels very close to US Highway 89 leading northeast away from Flagstaff; GOES-16 has the warmest pixels just to the west of that road! Which is correct?

Even with surface-based features such as fires, parallax (see other blog posts dealing with parallax here, here, here and here) is an issue with GOES imagery. (Click here to see parallax with lakes) The perceived location is shifted away from the sub-satellite point. So for this example, the true fire location might be somewhere between the satellite-indicated locations. Note also that the FDCA values from GOES-17 differ from those GOES-16; for this fire, GOES-17 values were warmer.

NOAA-20 overflew this fire at 20:50, 20:30 and 20:10 on 19, 20 and 21 April, and imagery from the NASA Worldview site is shown below (Click here for a direct link to the 20 April scene) VIIRS imagery typically has smaller parallax shifts than GOES (and in fact, as detailed here, considerable effort has gone into better georeferencing of VIIRS imagery, as discussed in this blog post and shown in this toggle), and the fire location is therefore more accurate. The 20 April view from NOAA-20 occurred shortly after the end of the animation above, and shows a fire straddling the highway.

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