Satellite Liaison Blog

GOES-18 has been operating as the operational GOES-West Satellite since 4 Jan 2023. A previous (July) blog post characterized the Barcode Artifact (BA), which is present in GOES-18 Ch07 (3.9 um), and most visibly impacts the appearance of imagery that leverages Ch07 in a band difference, most notably the Fog Difference and Nighttime Microphysics RGB Imagery. To summarize, the BA noise appears as N-S oriented warm and cold stripes and is most apparent in cold scenes. While users may notice the BA in imagery, there is no impact on feature detection and therefore minimal impact to NWS. Since the July blog post, the character of the Barcode Artifact has evolved. This blog post will highlight the history of the GOES-18 Barcode Artifact, including its very recent appearance (as of 3/23/2023).

A Satellite Book Club (SBC) webinar will be presented on April 6 on this subject. Please tune in!

The July blog post exemplified the BA appearance prior to 9/22/2022. On 9/22, the BA became “less visible”, as is shown in Figure 1, which compares the Nighttime Microphysics RGB on 9/17 and 9/24. Notice the vertical striping on the left become much more subtle on the right.

On 12/25/2022, the character of the BA appearance changed again, and is shown in Figure 2. Notice that while the vertical striping is present in both examples, occasional “more narrow/compact” stripes appear in the example after 12/25. The BA has appeared more or less the same since 12/25. Additional examples highlighting the current (as of 3/23/2023) appearance of the BA in a variety of imagery products are shown below.

Figure 3 captures the appearance of BA overnight in March 2023 for three of the most used B07 imagery products, including B07 alone, 10.3 – 3.9 Fog Difference, and Nighttime Microphysics RGB. The BA is barely noticeable in the single channel imagery, but is occasionally apparent across the broad scene in both the Fog Difference (10.3 – 3.9 um) and the Nighttime Microphysics RGB (which leverages the Fog Diff as the “green” component of the RGB). Notice that the vertical striping is most apparent within the high “cold” clouds.

When we focus in on a smaller geographic area, such as a NWS County Warning Area (SEA), the BA becomes even less apparent during the overnight period, as the vertical stripes are few and far between (Fig 4). Although occasionally noticeable, analysis of low clouds near Seattle is not impacted by the BA.

Moving further north into an even colder and cloud-ridden airmass, BA may be slightly more apparent overall, but analysis of any given localized cloud can still be completed (Fig 5 and 6).

The Day Snow Fog RGB is a popular RGB leveraged for daytime cloud analysis, and includes the Fog Difference as the “blue” component of the RGB recipe. Despite including the fog difference, no BA is visible when using this RGB since it is leveraged during the daytime (Fig 7).

Similarly, the Day Convection RGB, which also uses the Fog Difference, does not contain any BA influence (Fig 8).

One may have a (valid) concern about wildfire hot spot detection being impacted by BA in Ch07. This is not the case, as we remember that BA is primarily apparent in cold scenes (in clouds at night) in Band 07 differences. Figure 9 compares Ch07 and the Fire T RGB (which uses ch07 as the “red” component), and confirms no BA influence. Fires can continue to be tracked into the evening in either of these two imagery products, with striping very unlikely to be visible in the scene, as fires are surface (warm) features and use only the single band imagery.

Zooming in on southeast Washington in the Fire Temperature RGB, no artifacts are visible, and the hot spots are diagnosed per usual (Fig 10).

A full PACUS sector overnight Fog Difference example shows the BA most visible in cold high clouds, less visible in cold low clouds and over clear-sky cold airmass like in the western US, and least visible over the warmer airmass around Hawaii (Fig 11).

As has been noted and is shown in these examples, a users’ ability to detect and track clouds across their forecast area using GOES-18 imagery is not significantly impacted by BA. It is important to note that the appearance of BA may continue to change in the future.

Bill Line, NESDIS/STAR

Multispectral Imaging Information

This blog post will explore an experimental RGB “sandwich” product that has shown application in monitoring convection, particularly during the early stages of the convective lifecycle (aka convective initiation). The intended purpose of this revolves around identifying, interrogating, and monitoring these features of interest:

1. Moisture gradients as a source of focused ascent.
2. Early stages of convective lifecycle (i.e. convective initiation).
3. Cloud top structure and movement to glean additional info like stability, shear, and overall convective behavior.

An experimental RGB dubbed “Moisture Gradient Convective RGB” was developed using bands within the Advanced Baseline Imagery (ABI) onboard the current operational GOES satellites.

The Split Window Difference product (10.35 – 12.3 um) has shown utility in identifying low level moisture gradients, and has been shared numerous times on this blog (Just a few examples: here, here, and here). The 1.37 um Cirrus Band as well as the 1.61 um Snow/Ice Band can be useful in monitoring the early stages of the convective lifecycle [1]. And when looking to interrogate cloud top structure and movement, good ole trusty 0.64 um Visible Band is a clear winner.

The Moisture Gradient Convective RGB recipe* is as follows:

• R: 1.37 um Cirrus Band
  • Min – Max: 0 – 10
  • Gamma: 1.90
• G: Split Window Difference product (10.3-12.3 um)
  • Min – Max: 0 – (-6)
  • Gamma: 1.00
• B: 1.61 um Snow/Ice Band
  • Min – Max: 0 – 70
  • Gamma: 0.50

*Note on the RGB recipe: this recipe has not been tested for optimization across different regions and environments. Ranges and gamma values will likely need to be adjusted depending on the moisture and thermal environment.

Here is an example of this RGB:

But wait, where’s the 0.64 um Visible Band to help in interrogating cloud top structure and movement??

This is where the “Sandwich” approach is handy. We simply overlay a semi-transparent 0.64 um Visible Band on top of the RGB to add such desired information:

The RGB Sandwich requires daylight for this application, and is most useful with limited to no higher clouds masking information on moisture gradients and growing, infant convection.

In areas absent of masking cloud cover, greener colors represent relatively greater low level moisture content compared to areas that are bluer. Within clouds, red coloring represents clouds that have grown vertically high enough to extend into a dry air mass aloft while exhibiting glaciation (could either be optically thick cirrus and/or glaciated tops of robust convection), whereas purple-blue clouds represent shallower liquid phased clouds. Clouds that are more yellow-orange represent optically thin cirrus clouds.

Application Example: Southern Plains Severe Convection March 2, 2023

Robust convection was anticipated within central Texas March 2, 2023, initiated along a merging dryline/Pacific front. Identifying these initiating boundaries and how/when convection develops along these boundaries would prove useful in operational forecasting and decision support services.

Near the southern High Plains and Trans Pecos region of Texas, congestus cumulus started to develop between 1700 – 1730 UTC along one of these boundaries: a dryline, particularly near the Midland and Big Springs area. The useful Day Cloud Phase Distinction RGB has a proven track record in monitoring for convective initiation (as seen above), and can show the infant cumulus just starting to sprout.

Supplementing this imagery with automated surface observations and objective analysis can be useful in identifying boundaries suspect of initiating convection. However, there still is some form of interpolation needed when these boundaries don’t have attached clouds to help identify them. This is where adding information on moisture gradients can come in handy.

Comparing the Day Cloud Phase Distinction RGB to the Moisture Gradient Convective RGB Sandwich, can the exact location of the initiating boundary/ies location be identified in between areas of growing cumulus?

The location of the dryline is apparent at this time (orange annotated line), including other boundaries where low level moisture is converging (black annotated lines).

Moving forward with time, we can see cumulus agitate and grow right along this boundaries, particularly near Big Springs where the dryline “bulged” forward and where moisture convergent boundaries intersected. Additionally, one can notice a collection of mesoscale, convergent moisture bands just ahead of the dryline, acting as additional local sources of initiation and moisture pooling.

Other Considerations

While the Moisture Gradient Convective RGB Sandwich can be very applicable in dryline situations, it can be useful in any other convective scenarios where moisture gradients are suspected to be a source of initiation so long as there aren’t any masking clouds to cover moisture information given by the Split Window Difference product. Of course all limitations of any of the RGB components must be considered when utilizing this multispectral imaging.

Important caveats to keep in mind when using the Split Window Difference (SWD) to analyze low-level moisture features include:1) must have clear sky conditions, 2) the SWD values depend on low level moisture content AND low-level lapse rates (see basic graphic below). For example, in the presence of moisture, a steeper positive ll lapse rate (temperature decreasing with height) will result in greater SWD values compared to weaker positive ll lapse rates with the same amount of moisture. A neutral or negative lapse rate (temperature increasing with height) in the presence of low-level moisture will result in SWD values lower or opposite of those with a positive lapse rate. In short, interpretation of this RGB as outlined in this blog post requires a positive low-level lapse rate.

Keep in mind this is an experimental multispectral imaging technique. At the time of this post’s creation, it hasn’t undergone extensive research and application to prove its usefulness and find common pitfalls. Additionally, it may not be optimized for different regions, nor at different times of the year which may have implications on overall moisture content. For example, the SWD range may need to be adjusted during the peak Spring/Summer convective season to account for greater (negative) SWD values.

If you happen to find any interesting or notable uses of the Moisture Gradient Convective RGB Sandwich, as well as any pitfalls, please comment or reach out to either of the authors.

Carl Jones (NWS Grand Forks), with input from Bill Line (NESDIS/STAR)

An active weather pattern across the southern plains resulted in numerous widespread blowing dust events in February-March 2023 (that were observed in NOAA Satellite Imagery), including on Feb 14, 15, 22, 26, 27, 28, and most recently, on Mar 2. As is often the case, the blowing dust event on the 2nd was coincident with a widespread severe weather event (SPC MOD centered over the ArkLaTex region) that resulted in over 100 wind reports, and to a lesser extent, hail and tornadoes. All of the examples in this blog post are created in AWIPS, and can be adapted to any NWS office AWIPS.

The broader forcing for these significant weather phenomena can be diagnosed in GOES-East water vapor imagery, which reveals a compact shortwave quickly advancing east along the SW US/Mexico broader into west Texas throughout the day (Fig 1). Warming on the west/southwest portion of the shortwave represents descending/drying air within the dry conveyor belt of the system, and where downward momentum transfer is aiding the development of strong surface winds and blowing dust. Ahead of this feature, cooling brightness temperatures represent the moist convener belt and where deep moist convection is developing wit the moist/rising air. Overlays of RAP analysis 500 mb height and wind speed help to quantify and trace the location/magnitude of the low and mid-level jet, and aid interpretation of the WV imagery. Over time, such WV+NWP combinations can enhance forecaster confidence in imagery interpretation.

Taking a look at Geocolor+SWD+GLM (or GeoDust+GLM) imagery, we have a easy-to-interpret depiction of weather events during the day, including the widespread blowing dust captured in Geocolor and enhanced by the IR Split Window Difference, and cloud and thunderstorm development shown in Geocolor and GLM FED (Fig 2). Also apparent in the dust portion of the imagery is the broad southwesterly flow lifting the dust from Mexico aloft across southwest Texas, with westerly to northwesterly flow behind a cold front surging east across west Texas. The dust within the southwesterly flow eventually overruns that behind the front.

As has been shared in previous posts, a Color Vision Deficiency (CVD) Dust RGB is being developed, and uses similar ingredients as the traditional Dust RGB (in AWIPS), but in a way that helps Dust to stand out a little better, especially for those who have some degree of CVD. The Dust CVD RGB is compared with the Dust RGB in Fig 3 and 4, respectively. In the CVD version, blowing dust appears as relatively bright yellow compared to an otherwise blue or green background, compared to the pink appearance of dust in a Dust RGB. The Dust CVD RGB also clearly defines the dryline over west Texas as deeper blues within the moist atmosphere to the east, and lighter blues to cyans on the dry side to the west. Convection is observed to develop along that boundary.

This dryline evolution can also be captured in a previously discussed on this blog SWD-IR image combo, which captures the dryline from the SWD (lighter gray is greater low-level moisture), and cloud development in the cold-IR overlay (Fig 5). The advantage of the SWD (raw or in RGBs), is to provide more continuous information about the moisture gradient, both spatially and temporally, as a supplement to the surface obs, which quantify the atmosphere across the boundary. Dust is also apparent as dark gray to black.

One-minute imagery was available across the region to provide forecasters with more continuous satellite information. during this extreme event. Focusing on the development of blowing dust behind the front in west/southwest Texas, GeoDust animations provide excellent detail into the development of the dust plume, in the context of NWS Dust Storm Warning Polygons (Fig 6 and 7).

Further to the east, GOES-East meso-1 and meso-2 overlapped, resulting in a domain of 30-second imagery (Fig 8). A storm developing ahead of the main line of severe storms resulted in large hail falling over north-central Texas. The 30-second storm-relative imagery captures the persistent cooling along the southwest flank of the storm cluster, along with accelerating southeasterly flow in the inflow region as traced by the cumulus field.

Bill Line, NESDIS/STAR

An impressive supercell thunderstorm produced damaging softball sized hail overnight on March 1st-2nd in south Texas around Dilley. The storm developed on the eastern edge of GOES-18 (-West) Meso sector 1, capturing the rapid development of the storm minute-by-minute (Fig 1). IR imagery indicated brightness temperatures dropping rapidly as the storm emerged from beneath a cirrus canopy, cooling from -49C at 0314 UTC to -67C at 0324 UTC. The storm would eventually cool to -85C in the large and long-lived overshooting top per the GOES-West Imagery, similar to what was later sampled from GOES-East. Other significant thunderstorm characteristics exhibited by this storm included a rapid outward expansion of the anvil, an Enhanced V (or cold U), and thermal couplet. An Above Anvil Cirrus Plume is difficult to confirm in this nighttime case.

Five-Minute CONUS sector IR imagery from GOES-East captures the full evolution of the storm (Fig 2), including the above mentioned features. Warming of the cloud top is observed as the storm drifts east and weakens. The animation captures later storm development around San Antonio, which resulted in hail up to 1.75″ in diameter.

One may prefer to overlay cold C13 IR BTs on the Nighttime Microphysics RGB in order to analyze the low cloud situation (boundaries, moisture movement, etc) in conjunction with mature storm motion (Fig 3).

Overlaying GLM Flash Extent Density (FED) on the IR imagery, we diagnose a rapid increase in lightning activity during the storm’s early development, including a jump from 5 to 64 Flashes/5min from 0316 UTC to 0321 UTC, and to 93 flashes in the next 5 minutes (Fig 4). The storm would max out at 272 flashes/5min at 0626 UTC (per GOES-East GLM). Rapid decrease in total lightning activity is observed near the end of the animation, with increasing lightning highlighting the San Antonio storms.

Corresponding GLM Minimum Flash Area (MFA) imagery traces the movement of the updraft core well, as the region of lowest MFA (Fig 5).

We can combine the FED and MFA in an RGB to give us a single image, or experimental “GLM RGB”, that tells us where many flashes are occurring coincident with small flashes (or many small flashes may be occurring), as a signal of exceptionally strong updraft growth/sustainment (Fig 6). In this RGB, yellow indicates high FED and small MFA (many small flashes), red indicates few small flashes (with brighter orange representing increased number of small flashes), and blue represents few large flashes (with brighter cyan representing increased number of large flashes). The main southern storm consistently exhibits yellow within the main updraft region throughout it’s evolution prior to decaying. The northern San Antonio storms show comparatively lower total lightning activity, resulting in RGB appearance of updraft regions with bright oranges (many small flashes, but less than the other storm). This is a testament to the fact that such an RGB may have to be calibrated from event to event as a high lightning rate in one situation may be relatively low in another. Such changes are easily made in AWIPS using the “Composite Options”.

NOAA-20, NOAA-21, and S-NPP VIIRS Imagery were available over the region as the thunderstorm was weakening. However, the VIIRS imagery did capture the development of thunderstorms impacting San Antonio. During this evening, two NOAA-21 swaths sandwiched single swaths of S-NPP and NOAA-20, resulting in a sequence of imagery as follows: N21 (25-min) NPP (50-min) N20 (25-min) N21 (Fig 7). Prior to NOAA-21 becoming available, this scene would have been covered by only two VIIRS (N20 and S-NPP), separated by ~50-minutes. The sequence captures a lack of detail in the initial storm top as it drifts east out of the scene, while also revealing, in detail (375-m) the cooling and cool cloud tops of individual thunderstorms as they advance through northern San Antonio.

Figure 7: 02 Mar 2023 early morning NOAA-20, NOAA-21, and S-NPP VIIRS Band I5 IR Imagery. NOAA-21 VIIRS Imagery is preliminary, non-operational.

A three-satellite (NOAA-21 (25-min) S-NPP (50-min) NOAA-21) sequence is created for the VIIRS Day Night Band/Near Constant Contrast product during the same period over a broader region (Fig 8). The product captures visible-like imagery at night, including cloud details, city lights, and lightning flashes. The decay of the initial thunderstorm is obvious in this imagery, along with the abundant texture associated with the developing San Antonio storm.

Figure 8: 02 Mar 2023 early morning NOAA-20, NOAA-21, and S-NPP VIIRS DNB/NCC Imagery. NOAA-21 VIIRS Imagery is preliminary, non-operational.

Bill Line, NESDIS/STAR