True-color imagery from the CSPP Geosphere site, above, is annotated to identify a wildfire in progress. This is one of several fires over Oregon, as evidenced by the widespread smoke that is present across the region. The animation below, shows the evolution during the day of the fires. Pyrocumulonimbus (PyroCB) clouds — with lightning (see below) — developed over the fires.

Lapse rates derived from NUCAPS profiles, below, show a large region of near-dry adiabatic conditions (between 7 and 9^o C/km) over much of central Oregon where the convection developed. And individual NUCAPS profile, from 44.3^oN, 122^oW, below, shows an atmosphere at that point that will not greatly suppress vertical motions. The Equilibrium Level (EL) is diagnosed to be at the Tropopause.

GOES-18 Derived Stability Index values of CAPE (clear sky only) from 0300 UTC on 8 September 2024, plotted with 3.9 µm brightness temperatures and fire radiative power show instability over eastern Oregon and fire signatures.

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If you know the area you are monitoring has active fires, and satellite data is telling you the overlying atmosphere is nearly unstable, what might you expect from NGFS displays? The RealEarth NGFS display is shown below, at hourly timesteps from 1700 UTC 7 September through 0100 UTC 8 September. (Here is a speedier animation.) Note the presence of LightningCast probability contours (and GLM observations). NGFS detections — in red and orange — show an increase in Fire Radiative Power. Thunderstorms develop to the west of the fire; subsequently a pyroCB develops over the main fire (GLM FED at 0014 UTC shows lightning). This is the kind of information that is useful for Fire Weather Decision Support.

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GOES-18 Visible imagery, above, over the Samoan Islands, shows a variety of cloud structures moving from north to south over the Samoan Islands, especially over the smaller islands of American Samoa (Tutuila, Ofu/Olosega and Ta’u). The animation below, covering about the same time span, shows GREMLIN radar estimates. GREMLIN is a Machine-Learning tool the predicts radar returns based on ABI and GLM observations. Although it was trained on CONUS imagery, it does provide actionable information over the tropical South Pacific.

The view to the east of the Pago Pago airport, above, at 2127 UTC, shows the lower ceilings associated with the heavy rain. GREMLIN did a great job on this day of predicting onset and cessation of rains during a day when Flash Flood Warnings were issued (at 2208 UTC).

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A second Flash Flood warning was issued later in the day, and the run-up to that warning is shown in the animation below, visible imagery from 0050 to 0240 UTC on 7 September, below, and GREMLIN imagery from 0040 to 0230 UTC, at bottom.

The Forecast Office in Pago Pago had a Facebook post (below) that included one of the GREMLIN images above highlighting a Flash Flood warning issued at 0249 UTC on 7 September.

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Thanks to Jane Allen and Dora Meredith, NWS Pago Pago, for the AWIPS imagery!

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The radiosonde profile from the balloon launch just before 0000 UTC 7 September, above, (imagery from the Wyoming Sounding site), shows a very moist airmass, with saturation from the surface up to 400 hPa, and relative dryess above that level. Total Precipitable Water was 63 mm.

NOAA-20, NOAA-21 and Metop-C all provide NUCAPS (NOAA-Unique Combined Atmospheric Processing System) profiles. The Metop-C overpasses near American Samoa at 1842 UTC on 6 September, shown below, include a series of four green points (that is, points where the infrared retrieval converged to a solution) in the westernmost column of profiles just east of the Samoan Islands. The NUCAPS profile below is similar to the observation from Tutuila: very moist (this one had a Precipitable Water value of more than 2″), and a dry region above 400 hPa. NUCAPS profiles can give useful thermodynamic information in regions where conventional data are missing.

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At 0000 UTC on 9 September, the upper-air sounding, below (source), shows a much drier atmosphere. Note, for example, that Total Precipitable Water is 45.7mm on 9 September compared to 63mm on the 7th.

The NUCAPS profile (from Metop-C), at 2054 UTC on 8 September, below, centered on Tutuila (the island on which Pago Pago sits) shows structures that are similar to the rawindsonde above, namely relatively moist from 500-300 mb with dryer air above and below. It is always important to remember that NUCAPS moisture resolution is about 4-6 layers in the troposphere.

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ProbSevere is a collection of nowcasting products for convective hazards. Two such products are LightningCast and IntenseStormNet, which are AI models that use solely satellite data to make predictions. LightningCast predicts the probability of lightning in the next 60 minutes, whereas IntenseStormNet detects the strongest portions of storms, which are likely to produce tornadoes, severe hail, and severe wind gusts. Both use data images from satellite instruments.

Last week, storms erupted on the South Dakota / North Dakota border within the warm sector of a surface low pressure system. The animation below shows the evolution of LightningCast (left) and IntenseStormNet (right) over time.

One important goal of LightningCast is provide actionable lead time to lightning initiation. Using GOES-16 GLM flash-extent density, we see that LightningCast provided about 30 minutes of lead time to the first flash in the southern cells, and then 25 minutes of lead time to the first flash in the later northern cell, when measured from the cyan 25% probability contour. As storms matured, we noticed how the probability contours were more packed to the west, the upstream side of the convection, whereas they were more diffuse in the downstream direction of convection (eastward). The diffuse nature of the eastward contours indicates less certainty on where lightning will be within the next hour, where the storm cores and associated anvil clouds were heading. We believe this is a signal that the LightningCast model learned the approximate motion of storms from a single timestamp of GOES-R ABI images. More research is underway using time sequences of images to see if that can improve implicit motion estimates and lightning predictions.

The northern cell in central North Dakota impacted Bismarck Airport. The lightning dashboard below shows how LightningCast probabilities from both GOES-East and GOES-West increased initially over the airport, then were fairly steady, and then rapidly increased over about 10-15 minutes before the first lightning strikes were detected within 5 miles of the airport by the both GOES-East and GOES-West GLM instruments. These dashboards, available to forecasters at airports, many stadiums, and over wildland fires, help to sync the LightningCast probability information and GLM-observed flashes with potentially vulnerable locations of interest, facilitating the National Weather Service’s decision support for key entities.

Looking again at the animation above, the IntenseStormNet uses images of 0.64-µm reflectance, 10.35-µm brightness temperature, and GLM flash-extent density to predict a probability of “intense” convection. The product really highlights the intense most regions, where strong overshooting tops and “cold-U” signatures reside, often colocated with robust “bubbly” texture from the visible reflectance. Notice the fact that many reported severe weather events werre associated with these features, created by the strong storm updrafts. Nearby pronounced anvil-edge gradients in the ABI channels and a core of GLM flash-extent density are also important features for contributing to higher probabilities.

IntenseStormNet output is a predictor in ProbSevere v3, machine-learning models that combine radar, satellite, lightning, and environmental data to predict the next-hour probability of severe hail, severe wind gusts, and tornadoes. IntenseStormNet can also be used as a stand-alone satellite-only severe-weather nowcasting tool in the absence of radar, such as in parts of the western U.S., in Canada, in oceanic regions, and in parts of Latin America.

LightningCast should be operational at NOAA/NESDIS in early 2025.

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