The incorporation of MetopC NUCAPS files into AWIPS also means that MetopC Gridded NUCAPS fields are available for forecasters to help diagnose the state of the atmosphere. The toggle above shows two swaths of data, one from MetopC over China, and one from NOAA-20 over the western Pacific. The imagery also includes estimates of the 850-500 mb lapse rates in two regions (that I accessed through AWIPS’ Product Browser). Those are viewed a bit more closely below.

The time of the MetopC and NOAA-20 overpasses was near 0140 UTC on 19 March. Himawari-9 Band 13 (Clean Window infrared, 10.4 µm) and Air Mass RGB imagery (taken from Real Earth) show evidence of a polar front over China. Much of the West Pacific is in a tropical airmass.

MetopC Gridded NUCAPS fields, below, show the very cold (ca. -40^oC) 500-mb temperatures and steep lapse rates associated with the upper level front over China.

At about the same time, NOAA-20 saw very steep lapse rates each of Japan, but relatively warmer 500-mb temperatures (i.e., the lower levels were likely warmer).

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Use gridded NUCAPS fields to determine what’s going on in the troposphere in regions where other sources of data are scarce, and also over data-rich regions where more thermodynamic information will be useful.

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10-minute JMA Himawari-9 AHI “Red” Visible (0.64 µm), Shortwave Infrared (3.9 µm) and “Clean” Infrared Window (10.4 µm) images (above) showed the formation of 2 pyrocumulonimbus (pyroCb) clouds spawned by a wildfire in Sichuan Province, China on 16 March 2024. The initial (smaller, shorter-lived) pyroCb developed at 0820 UTC — exhibiting cloud-top 10.4 µm infrared brightness temperatures of -40ºC and colder, denoted by the shades of blue — with the second (larger, somewhat longer-lived) pyroCb developing at 0910 UTC. The wildfire began to make a rapid northeastward run during the ~5 hour period shown in the animation. The fire environment across that region became more favorable as wind speeds increased with the approach of a deepening surface cyclone, as shown in surface analyses (the pyroCb-producing wildfire was located near 30º N latitude, 131º E longitude).

Himawari-9 True Color RGB images created using Geo2Grid (below) showed the east-northeast transport of the wildfire smoke plume, with its embedded pyroCb cloud.

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It’s spring time on the Great Plains, which means strong dynamical systems that often bring blizzards as well as severe thunderstorms. A long-wave trough with an embedded 850-500mb jet streak created cyclogenesis in western Oklahoma and southwest Kansas on March 13, with associated low-level moisture return into eastern Kansas.

The strong instability and excellent wind shear spawned rapidly growing thunderstorms (some of which are highlighted in this blog post). ProbSevere LightningCast, which is a deep-learning model that uses GOES ABI to predict next-hour lightning, showed high probabilities on this convection 20-30 minutes before the first flashes.

While LightningCast is scheduled to become operational in NOAA in later 2024, new enhancements will be evaluated in NOAA’s Hazardous Weather Testbed in 2024, including the probability of >=10 flashes in the next 60 min, and a GOES-West-only model (trained on GOES-18 data). One important aspect that will be evaluated are lightning dashboards. These time series of the probability of lightning and observed GLM flashes can serve meteorologists providing impacts-based decision support for large venues like stadiums, concerts, fairs, and amusement parks. The dashboard below shows the progression of LightningCast probabilities and GOES-16 Geostationary Lightning Mapper (GLM) flashes near Kansas City International Airport as storms approached.

As storms became severe, the Kansas City metro region got hammered with hailstones up to 3″ in diameter, while tornadoes touched down between Manhattan and Topeka.

The ProbSevere v3 models track developing thunderstorms and use use radar, satellite, lightning data, and near-term near-storm environment data from the HRRR model to predict next-hour severe weather probabilities of hail, wind, and tornado. This guidance improves confidence for forecasters in their warning-decision making and helps provide enhanced situational awareness of how storms are evolving. Scientists are exploring methods to exploit polarimetric radar data and the important spatial aspects of radar and satellite data, to further improve the models’ accuracy.

This method of data fusion and probabilistic guidance is especially useful in busy situations with numerous rapidly evolving storms with multiple threats (see below, in eastern Kansas). The quick-look probabilities, cursor read-out, and time series functionality help forecasters make more efficient and effective warning decisions.

Another machine-learning model developed at CIMSS is the IntenseStormNet, which uses GOES-R ABI and GLM images to detect “intense” convection, as viewed from a geostationary satellite perspective. This model excels at isolating the most intense parts of storms in developing and mature convection using a computer-vision approach, which holistically uses features like strong overshooting tops, above-anvil cirrus plumes, cold-U signatures, and strong anvil-edge gradients to predict probabilities.

IntenseStormNet is particularly valuable when radar coverage is diminished, but still adds value to ProbSevere v3 models even in the presence of good radar coverage. The final movie shows a zoomed-out view of IntenseStormNet applied to all of the convection in the central U.S. on March 14.

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1-minute Mesoscale Domain  Sector GOES-16 (GOES-East) images from all 16 of the ABI spectral bands plus a Rocket Plume RGB (above) displayed signatures of the SpaceX Starship 3 rocket that was launched from the Starbase facility in Boca Chica Beach, Texas at 1325 UTC on 14 March 2024. During the first 4 minutes post-launch, the Stage 1 rocket booster’s condensation cloud was evident in images from all 16 spectral bands, as it began to drift slowly eastward away from the Texas coast — and the ascending rocket booster’s thermal signature was seen in Near-Infrared and Infrared spectral bands 04-16, as well as the Rocket Plume RGB.

In Band 8 (Upper-level Water Vapor) imagery, note the change in exhaust plume shape with time and atmospheric layer: at early altitudes of 20-50 km (where the Stratosphere had more density, and therefore higher ambient pressure), the Stage 1 booster plume was more linear — but after the 1328 UTC “hot stage separation” as the Stage 2 rocket reached higher altitudes of 70-80 km (where the Mesosphere was much less dense, with lower ambient pressure) the plume was able to expand outward into more of a curved “boomerang” shape beginning at 1329 UTC.

A close-up view using a sequence of three 16-panel displays of all GOES-16 ABI spectral bands (below) showed that a warm thermal signature of the hot stage separation process was apparent at 1328 UTC in Near-Infrared bands 04-06 and Infrared bands 07-16 (just to the right of center in each image panel).

A larger-scale view using interleaved GOES-16 Mesoscale Sector and CONUS Sector Upper-level Water Vapor (6.2 µm) images (above) allowed the Stage 2 rocket exhaust signature to be followed for about 7 minutes post-launch as it moved eastward across the Gulf of Mexico.

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