During the evening of April 21, 2020, several supercells developed in the Texas Panhandle into western Oklahoma producing hail resulting in numerous reports. Not only was the size of hail large, the amount of hail that fell was significant as noted by reports of accumulated hail of several inches deep. As storms snailed away from their deposited hail swaths, GOES-16 was there to view these swaths. This post will showcase how forecasters can view freshly deposited hail swaths using multispectral imagery at night.
Figure 1 depicts the Nighttime Microphysics RGB with the “clean” longwave infrared band (Band 13, 10.3 um) overlaid while making any temperatures warmer than -25 C transparent. This allows for cloud layer and phase information to be provided within the Nighttime Microphysics RGB while also monitoring very cold cloud top temperatures associated with severe storms as well as overshooting tops denoting an updraft penetrating into the tropopause. As the convective clouds and overshooting tops pull away from the border of the Texas Panhandle and western Oklahoma, notice one to three subtle, magenta-colored lines oriented northwest to southeast as skies clear (see annotated images here and here). These lines correlate well with highest reflectivities that had passed over previously in time as well as with storm reports of hail. These lines are a result of altered environmental and ground temperatures (in this case cooling) from the copious amounts of hail left behind their parent storms.
While the default composition ranges of the Nighttime Microphysics RGB within AWIPS-2 allow for just subtle signatures within the imagery, there is room for adjustment to enhance this signal. A good place to start is by looking at a 4 panel display of the RGB (Figure 2) being discussed and each of the its components set to a black to white scale with the RGB’s default ranges.
Sample the signal in question within each of the RGB’s components and adjust the range within the components until there is good contrast between the signal and background. Once the component’s ranges are adjusted to your liking, adjust them within the RGB itself. In this case, there was room for improvement mainly within the red component (the Split Window Difference, 10.3-12.3 um) and the blue component (“Clean” IR, Band 13, 10.3 um). However when adjusting the red component, the RGB itself became too saturated in red coloring. Therefore we can tone down the saturation of red by lowering the red component’s gamma. Figure 3 is what the new composition looks like now (click here for actual recipe values).
Do you think the hail swaths show up better in the adjustments as shown in Figure 4? Making an adjustment on the fly works in this case, but might not for all cases. Thus adjustments to RGBs are advised to only be made on a case by case basis, especially with those having a large dependency on infrared temperatures. It is also worth noting that this approach of using multispectral satellite imagery to observe accumulated hail swaths is dependent on cloud-free skies as well as enough hail to actually make an alteration to the ambient environmental and ground temperatures.
So how does this apply to IDSS? Well besides increasing overall situational awareness, noting hail swaths in near real time lends confidence in derived products like MRMS MESH tracks through observations. This could also allow forecasters to help core partners like DOT maintenance crews target areas for hail removal should they request it. Additionally, this could also provide an opportunity for target LSR intel gathering, or even safety messaging as accumulated hail can produce hazardous travel conditions through slick roadways and reduced visibility should hail fog form (which by the way is also detectable in this approach through the use of the 3.9-10.3 um “Fog/Low Stratus” Brightness Temperature Difference as the Nighttime Microphysics RGB’s green component).
NWS Grand Forks