During the current warm period for GOES-17, when the sun’s position leads to excessive heat build-up on GOES-17 because of the poorly-functioning Loop Heat Pipe, the Set Point temperature has been increased from 92.8 K. This change occurred on 11 April 2022 and it is scheduled to last for one week — the daytime ‘stripiness’ should relax on 19 April when the Set Point temperature changes back to a cooler temperature (90 K). The figure below (from this NESDIS/STAR link) shows Focal Plane Temperatures at different time scales. The Set Point change is apparent in the figure showing the last 10 days; a second Set Point temperature occurred on 9 April, but that one did have such a big effect on imagery. Note how the warmest Focal Plane Temperature has been increasing in the past 10 days.

You might ask: What is the Set Point temperature and why is it affecting these two bands? The cryocooler is a secondary cooling mechanism on GOES-R satellites (the Loop Heat Pipe is another cooling mechanism). Heat from the cryocooler’s operation actually warms up the satellite. So, warming the cryocooler set point decreases that thermal load. That warmer setpoint, however, means the focal plane of the ABI is warmer (as evidenced in the image above), and that warmer focal plane degrades select bands for all 24 hours. The benefit of a warmer cryocooler is that the number of nightly images completely missing related to the Loop Heat Pipe is not quite so long. In other words, for Band 10, all of the daytime images have some degradation, but the number of completely missing night-time images is decreased (compared to what would happen if the Set Point were cooler!). This pdf shows predictions for how warm the Focal Plane Temperature might get over the course of this year; note (on page 5) that the April heating period is the warmest, and that (page 6) Bands 10, 12 and 16 are the most affected bands.

Because Band 10 (and Band 12) data are used in some RGBs — such as the airmass RGB shown above — those RGBs will also be affected for this week.

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Previous posts on the CIMSS Blog (here, here, here) have detailed a modeling system that incorporates thermodynamic information from hyperspectral soundings (CrIS on Suomi/NPP and NOAA-20; IASI on Metop-B/Metop-C) into a version of the Rapid Refresh model. The improved definition of thermodynamic distributions by the hyperspectral data (that is: better spectral resolution) is combined with the better spatial and temporal resolution of the Advanced Baseline Imager (ABI) on GOES-16 to produce 18-h forecasts every hour (model output is available here; a Journal Article describing this data fusion is here). This product is to be demonstrated at the Hazardous Weather Testbed, starting in May of 2022.

Severe weather occurred in the Plains on 12 April (SPC Storm Reports). What did this modeling system show? The animation above shows Convective Available Potential Energy, hourly from 1600 – 0000 UTC on the 12th. The first two frames are analyses, the final frames are part of the 1700 UTC forecast, which should include some IASI input from the morning Metop overpasses (MetopB orbits on 12 April; MetopC orbits on 12 April). Two areas of enhanced CAPE are present: one starts near Kansas City and lifts northeastward into southeastern Minnesota and western Wisconsin before eroding; a second, larger region of stronger CAPE moves from Oklahoma/Kansas into western Iowa by 0000 UTC. Was convection associated with this instability? That is shown below: side-by-side animations of GOES-16 Day Cloud Phase Distinction and PHSnABI CAPE values.

Strong convection develops initially over northeast Iowa/southern Minnesota just north of the eastern diagnosed CAPE maximum. A second round of convection develops over western Iowa in association with the diagnosed CAPE maximum there.

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The model data output are archived at this link. It’s pretty easy to view how forecasts are changing with time as an event approached. For example, the animation below compares forecast CAPE values for 0000 UTC on 13 April — 18-h, 12-h, 9-h and 6-h forecasts from 06, 12, 15, and 18 UTC on 12 April 2022. Note the big change between the forecast initialized at 0600 UTC and the one initialized at 1200 UTC. Between those two times, Suomi-NPP and NOAA-20 will have overflown the central United States and helped the initial fields in the model to represent more accurately the thermodynamics. Forecasts after that concentrate CAPE values over western Iowa.

Changes in the Significant Tornado Parameter (STP) for the same time, from the same model runs, are shown below, and tell the same story. Thermodynamics and wind profiles in the model are most strongly favorable for tornadogenesis over western Iowa.

What did the model precipitation look like? CAPE and STP show a potential. But the convection has to develop and be influenced by the CAPE and STP. Model precipitation is shown below. Only the 1800 UTC model run shows the strong convection that developed over western Iowa by 2200 UTC — and that precipitation is a bit too far west.

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There is also a 3-km version of this model available at the model output link. (This one) The higher-resoluation model run (as might be expected) does a far better job in predicting the onset of convection. Output from the 1800 UTC model run is shown below. Initiation and behavior is very well-matched with observations. The Significant Tornado Parameter from this run (bottom) shows that parameter maximizing over northwest/northcentral Iowa between 2100 UTC on the 12th and 0100 UTC on the 13th. The first tornado per SPC Storm reports occurred shortly after 2300 UTC on the 12th.

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This case demonstrates the power of adding Polar Hyperspectral Sounding information into a model run: An accurate forecast of likely tornadic development resulted. The next generation of Geostationary Satellites (GeoXO) are slated to carry a GXS — a Hyperspectral Sounding in geostationary orbit — that could also supply accurate thermodynamic information to numerical models to enhance forecasts. For more on GeoXO, click here.

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5-minute GOES-16 {GOES-East) True Color RGB images created using Geo2Grid (below) showed widespread blowing dust (shades of tan) and wildfire smoke plumes (brighter shades of white) across much of the central/southern Plains on 12 April 2022. Wind speeds were anomalously strong behind a dryline within the warm sector of an anomalously-deep surface low, which were responsible for the spread of wildfires and blowing dust.

In southeastern Colorado, 1-minute Mesoscale Domain Sector GOES-16 “Red” Visible (0.64 µm) and Shortwave Infrared (3.9 µm) images along with 5-minute Fire Power and Fire Temperature products (below) displayed a smoke plume and thermal signatures of 2 grass fires that rapidly intensified between La Junta (where the peak wind gust was 53 knots) and Lamar. The Fire Temperature and Fire Power derived products are components of the GOES Fire Detection and Characterization Algorithm FDCA.

Farther to the south, 1-minute GOES-16 “Red” Visible (0.64 µm) and “Clean” Infrared Window (10.35 µm) images (below) include plots of time-matched SPC Storm Reports for severe thunderstorms in central Texas — which produced tornadoes and hail as large as 5.50 inches in diameter. Note that 2 of these storms exhibited Above-Anvil Cirrus Plumes (AACP: reference | VISIT training) in the Visible imagery; however, the corresponding “warm AACP” signature was not evident in the Infrared images, as is frequently the case.

The lack of a “warm AACP ” infrared signature was explained by 2000 UTC rawinsonde data (source) from Fort Worth, Texas (below), which indicated that stratospheric temperatures continued to cool with height.

Finally, across the northern Plains within the cold sector of the large surface low, blizzard conditions spread across much of North Dakota (and adjacent portions of eastern Montana, northern South Dakota and northwestern Minnesota) — as shown in 5-minute GOES-16 Mid-level Water Vapor (6.9 um) images with plots of precipitation type (above) and wind barbs/gusts (below).

===== 14 April Update =====

As the Northern Plains blizzard persisted into its third day on 14 April, longer animations of GOES-16 Water Vapor images are shown with plots of precipitation type (above) and wind barbs/gusts (below). Storm total snowfall accumulations included 36 inches in North Dakota, with peak wind gusts of 72 mph in South Dakota (WPC Storm Summary). The 3-day total of 18.3 inches was Bismarck’s largest April snowfall on record.

Here at the office in Bismarck, we had a storm total of 18.1 inches of snow. Here are some of the highest snowfall reports from around western and central North Dakota. #ndwx pic.twitter.com/mIYYavNuHh

— NWS Bismarck (@NWSBismarck) April 15, 2022

===== 15 April Update =====

On the morning of 15 April, GOES-16 Day Snow Fog RGB images (above) revealed the partial extent of new snow cover from the 3-day blizzard (darker shades of red), along with narrow plumes of “river effect snow” (shades of white) streaming southeastward from unfrozen reservoirs along the Missouri River in North Dakota and South Dakota. At one point, a plume passing directly over Hazen, North Dakota (downwind of Lake Sakakawea) was producing light snow that reduced the surface visibility to 4 miles.  

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Typhoon Malakas in the western Pacific is shown above in Himawari-8 infrared imagery between Guam and the Philippines. It is a well-developed storm (albeit asymmetric) with an obvious eye. Level 2 Rain Rate from Himawari-8 is also shown; the heaviest precipitation is diagnosed to the southeast of the eye, and in rain bands to the east of the storm.

For more information on Malakas, refer to the SSEC/CIMSS Tropical Weather Website and the Joint Typhoon Warning Center.

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Himawari imagery is courtesy JMA (Thank you!). Real-time sectorized Himawari imagery from the Meteorological Satellite Center of JMA is also available here.

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