Due to a lack of radar coverage over American Samoa, WSO Pago Pago requested 1-minute Mesoscale Domain Sector coverage over the islands during a period of heavy rainfall risk. GOES-18 (GOES-West) Clean Infrared Window (10.3 µm) images (above) displayed showers and thunderstorms that moved across the American Samoa island of Tutuila (where Pago Pago International Airport NSTU is located) on 24 March 2025 — which produced periods of moderate to heavy rainfall (leading to flash flooding and landslides, prompting the issuance of a Flash Flood Warning; there were local storm reports of up to 4.5″ of rainfall in 3 hours). The coldest cloud-top infrared brightness temperature associated with these thunderstorms was -86ºC (brighter shades of white embedded within dark black regions).

A listing of Pago Pago surface observations is shown below — highlighting the time period displayed by the 1-minute GOES-18 imagery (during which NSTU received 3.72″ of rainfall in 3 hours). Local time in American Samoa is 11 hours behind UTC.

Around the time of onset of the thunderstorms that moved across the island of Tutuila, nearby satellite-derived Total Precipitable Water values were as high as 2.39 in (below). This thunderstorm development was focused along a west-to-east oriented surface trough (Fiji Meteorological Service surface analyses: 2100 UTC | 0000 UTC | 0300 UTC).

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The heavy rains that occurred were within a large region of atmospheric moisture as shown in the MIMIC TPW animation below of Total Precipitable Water. MIIMIC TPW values started decreasing around 0900 UTC on 25 March 2025.

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Staffing issues at a number of WFOs has lately meant gaps in the launching of soundings, either at 0000 UTC or at 1200 UTC. Satellite profiles derived from the GFS model and nudged towards ABI observations are available in AWIPS, and these products can fill in some of that missing information. (This training video will show where the products are in the AWIPS menu — scroll forward to 5 mins 25 seconds). The image below shows the Legacy Atmospheric Profile (LAP) display in AWIPS for a single time, with points that will have — every 30 minutes — a vertical profile of temperature and moisture if clouds are not present. (Click here to see an animation that demonstrates how clouds affect the distribution of valid points with clear sky products).

The point highlighted in central Oklahoma is close to a launch site at Norman. The 0000 and 1200 UTC soundings from KOUN are shown below. There is considerable drying aloft between the two times and, of course, low-level cooling.

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What do the Legacy Profiles show for this span of time? That’s shown in the animation below. The profiles are much smoother than you observe with radisondes, and thin layers of moisture (or dryness) that could be synoptically important are not well-resolved. However, the profiles capture the overall evolution of the atmosphere. A strength of LAP data is monitoring changes, and the edges of gradients. Those gradients might be a lot easier to view by loading Derived Stability Indices (CAPE, Lifted Index, etc) and Total Precipitable Water fields that are derived from the LAP data. (AWIPS note: I’ve been unable to get pop-up SkewTs to work with LAP data. Maybe that’s just my AWIPS however).

The following two toggles directly compare the 0000 UTC and 1200 UTC KOUN soundings with the closest-in-time profiles. There are similarities between the two profiles.

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Of course, if you have clouds (or even if you don’t!), you could also look at NUCAPS profiles that incorporate microwave imagery, albeit at coarser temporal resolutions. On this day, the NOAA overpass occurred in clear skies. The image below shows NUCAPS profiles overlain with LAP data (plotted in coral) at about the same time, and also GOES-East band 13 imagery to approximate the cloud cover.

The Slider Juxtapose below compares somewhat-adjacent NUCAPS and LAP thermodynamic data at 0852 UTC on 24 March. (click here for a toggle).

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These profiles do not include winds. A substitute for the winds could be from ACARS data.

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On March 19, a potent shortwave trough forced the development of a strong surface cyclone and moisture return into central Illinois, with ample surface theta-e and deep-layer shear to sustain surface-based convection.

In the animation below, you can see the quickly developing convection and associated ProbSevere v3 contours evolve. The storm that affected Canton, Illinois produced a damaging wind report at 19Z and a tornado report first at 19:30Z.

Early on the storm’s development, the satellite growth rate in ProbSevere was quite impactful. At 18:18Z, the moderate growth rate was the 5th most-important predictor.

1. Lapse rate 0-3 km (8.9 C/km)
2. Mean wind 1-3 km AGL (43 kt)
3. Effective bulk shear (52 kt)
4. Total lightning flash rate (6 fl/min)
5. Satellite growth rate (2%/min)

Along with all of the other predictors, this generated a probability of severe of 30%. As an experiment, when we artificially made the satellite growth rate 0, the probability fell to 14%. The satellite growth rate has the most impact on storms during the development phase of convection. Once convection is more mature, the deep-learning-based IntenseStormNet predictor (which uses images of ABI and GLM fields as inputs) is the more important satellite feature in the ProbSevere v3 models.

Using the Python SHAP library, we created a “decision” plot to visually see how different predictors in the model affected the final prediction. The bar on the top and bottom is in “log-odds-space”, which allows us to see meaningful deflections of the predictors. That is, the deflections are all proportional to their importance on the final prediction. Rightward deflections increase the probability of severe whereas leftward deflections decrease the final probability. The satellite growth rate was about as important as the flash rate for this storm at this time.

Shortly after 18:18Z, a strong lightning jump also boosted the probability of severe to about 40%. About 35 minutes later, damaging wind was report. Interestingly, the moderate satellite growth rate did not boot the ProbSevere v2 probability, probability because the meager radar and lightning predictors were squashing the probability overall. However, the ProbSevere v3 models are gradient-boosted decision trees, and appear to utilize the satellite data more skillfully (as well as other inputs) than the previous version.

The probability of tornado began ramping up in this storm around 19:10Z, hitting 56% at the time of the first tornado report (19:30Z), which is a very high value for ProbTor v3. In the AWIPS display below, a user’s mouse “hovering” over the ProbSevere object produces the pop-up text. This text provide forecasters the exact probabilities and select predictor values. A time series of the probability values opens up when a user double-clicks on the storm object. These visualization features help forecasters quickly interrogate severe or tornadic threats, which is particularly important during busy severe-weather situations.

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10-minute Full Disk scan GOES-18 (GOES-West) True Color RGB images created using Geo2Grid (above) showed a von Kármán vortex street — created by north-northwesterly winds interacting with the western tip of Nelson Island, Alaska — propagating south across the Bering Sea on 20 March 2025. In addition, through breaks in cloud cover the tidal ebb and flow of sea ice was apparent.

The vortices were also evident in Suomi-NPP Visible images valid at 2202 UTC and 2342 UTC (below).

In a toggle between the 2202 UTC Suomi-NPP VIIRS Visible image and Topography (below), an arc of slightly elevated terrain along the far western tip of Nelson Island (abruptly rising to around 900 ft, darker shades of tan) likely perturbed the northerly flow enough to initiate formation of the von Kármán vortices.

Special thanks to Jason Ahsenmacher (NWS Fairbanks) for bringing this interesting feature to my attention.

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