The recent bouts of severe weather (See this blog post about the 31 March outbreak, or this one about the 4 April outbreak) over the central United States mean an opportunity to compare Numerical Model output from models that are initialized with temperature/moisture profiles derived from Polar Hyperspectral Soundings (using both infrared and microwave data from CrIS/ATMS or IASI/AMSU/MHS) to models that have not assimilated such data. Does the addition of the observations of temperature and moisture profiles observed by NOAA-20/NOAA-21 or MetopB/MetopC lead to a better prediction of convective weather? As happened in 2022, this Polar Hyperspectral Modeling System (PHSnMWnABI, or just PHS for short) will be demonstrated at SPC’s Hazardous Weather Testbed. The blog post will show a few examples of differences between PHS-enhanced modeling output, and a separate modeling system not so enhanced.

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Significant Tornado Parameter (STP) can be computed from HRRR model output and from PHS/WRF model output, and that field, overlain with severe weather reports, is shown below at hourly intervals for the 31 March – 1 April severe weather event. There is good correpondence between the severe weather reports and the STP fields, moreso especially with PHS-enhanced WRF model over Iowa and Illinois at 2100, 2200, 2300, 0000 and 0100 UTC. (These fields show average values of 9 separate forecasts valid at the time shown, that is, the average of a 1-h forecast, a 2-h forecast, a 3-h forecast…, and a 9-h forecast valid at the time shown).

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Consider the toggle below that compares HRRR model output (without PHS input) and WRF model output (with PHS input). There is a pronounced difference in the predicted radar reflectivity in this 3-h forecast to the west of Chicago (NWS WFO outlines are shown on that map). The 1700 UTC radar, below (source), shows better agreement with the PHS model, although an argument could be made that the PHS model is overpredicting the precipitation on this day.

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A comparison of the average STP from different forecasts enhanced by PHS observations and forecasts that do not assimilate PHS data is shown below for the same event, but at 0000 UTC on 5 April 2023. (Here’s the same figure for 1500 UTC on the 4th, and 0900 UTC on the 5th). In general, STP values are greater in the WRF run that starts with assimilated moisture and temperature observations from Hyperspectral Soundings.

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More results from this modeling system will be shown in the coming weeks. Imagery in this blog post is courtesy Qi Zhang, CIMSS. Model output from this system is available online here.

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Himawari-9 Airmass RGB imagery, below, from 0000 on 4 April through 1200 UTC on 6 April 2023 (created using geo2grid) show a transition from a deep tropical airmass (deep green in the RGB with embedded clouds that are white) over the southern Marianas islands to one that is a bit dryer (more orange in the RGB). A meteorogram for the A. B. Won Pat International Airport on Guam, below, shows the transition that started around 1800 UTC on 4 April. In particular, the pressure increased from 1008 mb to around 1010 mb; winds shifted to northeast and then east (and strengthened); dewpoint temperatures dropped a couple degrees (^oF). Guam is at 13.4° N; this airmass penetrated very deep into the tropics.

What other satellite products showed this change? The Night Microphysics RGB, below, also shows a boundary moving south over the southern Marianas islands. As with the airmass RGB above, the boundary does not appear to move very far south of Guam.

Advanced Scatterometer (ASCAT) imagery from MetopB and MetopC (originally from this website, and combined into one image at this website that shows the most recent 1-week animation) also shows the expansion southward of strong northeasterly winds. On 3 April 2023, winds around Guam are light from the east or southeast. By 5 April 2023, strong northeasterly winds have expanded southward over the Marianas Islands.

ASCAT winds ca. 1200 UTC on 6 April 2023, shown below, indicate strong convergence over Guam.

Gridded NUCAPS fields (available at this site) also show the stark differences across the Marianas Islands from north to south. The animation below shows 850-700 mb lapse rates (more stable over the northern Marianas), 400-200 mb lapse rates (more stable over the northern Marianas), Total Precipitable water (dryer over the northern Marianas) and 850-mb Temperatures (cooler over the northern Marianas). NUCAPS data can give very useful information within data voids (like the Western Pacific Ocean!)

MIMIC Total Precipitable Water fields over the western Pacific Ocean (from this site and archived here), below, from 0000 UTC on 1 April through 1200 UTC 6 April, show the dramatic southward motion of dry air over the northern Marianas that extend northeastward from Guam (at 13.4° N, 144.8° E).

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Sandwich product imagery from this JMA website (scraped daily), below, shows parts of the western Pacific from 0000 UTC on 1 April through 5 April 2023. The storm responsible for dragging a front across the Marianas is apparent in the imagery starting around 3 April.

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The 3-panel animation above shows the 3 “Water Vapor” channels on GOES-R Satellites — Bands 8, 9 and 10 that sense emitted radiation centered at 6.19 µm, 6.95 µm and 7.34 µm, respectively. The date of these images is 24 May 2022, when SPC suggested a modest risk of severe weather over parts of west Texas, shown below (link).

Weighting functions for a USA Standard Atmosphere, below, for the three water vapor channels (from this website; you can find real-time weighting functions here), show that Band 10, at 7.34 µm receives energy from closer to the surface than Band 9 (6.95 µm), or Band 8 (6.19 µm).

GeoXO, the follow-on mission to GOES-R, will include a few more channels on the planned Imager (GXI), including one to sense radiation at 5.1 µm; water vapor absorbs energy at this wavelength, although its weighting function peaks much closer to the surface. This previous blog post shows weighting functions for 5.1 µm, and also the spectral response function.

Data Fusion is a technique (see this paper by Elisabeth Weisz and Paul Menzel for information on this particular case and for references on the technique) that marries the dense spectral information available on IASI or CrIS to the dense spatio-temporal resolution information (for infrared channels) available on ABI in a way that allows the Sounder information from the Low Earth Orbit (LEO) satellite to be tracked with time. Briefly, relationships between the LEO Sounder Observations and ABI infrared observations (Bands 8-16, at a degraded resolution (“LORES”) similar to the LEO footprints) are established via a K-D Search Tree. Then, high-resolution ABI observations at subsequent times are matched to the 5 closest LORES profiles, and the 5 LEO profiles at those LORES points are averaged to produce the fusion data. This procedure is transferring CrIS (or IASI) retrieval products to ABI spatial resolution by using ABI observations coincident with the CrIS (or IASI) overpass; the image (now at high spatial resolution) is then transferred to preceding or succeeding ABI measurement times to create a time sequence of hyperspectral sounder data products. The animation below, courtesy Elisabeth Weisz, shows ABI plus IASI Data Fusion 5.15 µm imagery from 1600-1900 UTC on 24 May 2022, coincident with the animations shown above. IASI data from the 1700 UTC Metop-B overpass is first convolved to 5.15 µm and then transferred to high spatial as well as high temporal resolution dictated by the ABI radiance information (collected every 10 minutes). The proposed GeoXO 5.15 µm band will provide valuable low level moisture information that is not offered by the current ABI bands. An animation of that field is shown below.

A comparison of the 5.15 µm animation above with the 10.35 µm Data Fusion imagery is shown below. In particular, consider the west-southwest to east-northeast boundary that moves through El Paso TX during the animation in the 5.15 µm imagery, but not the 10.35 µm imagery (nor in the 6.19 µm – 7.35 µm imagery shown at the top of this blog post). Such a low-level moisture gradient detected in the lowest-level water vapor imagery could serve as a focusing mechanism for subsequent convection.

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As it happened, 1600-1900 UTC on 24 May 2022 is an (unwelcome!!) data gap for GOES-16/GOES-17 data at the NOAA CLASS Data Repository because of a PDA issue. However, the SSEC Data Center did save the L1b files from other sources. Many thanks to that facility for its data. This event was also the subject of a blog post, with animations starting after 1900 UTC, here. GOES-16 Meso-sector 2 was positioned to view the event.

This blog post benefited enormously from Elisabeth Weisz’s input. Thank you!

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1-minute Mesoscale Domain Sector GOES-16 (GOES-East) Visible/Infrared Sandwich RGB images from 1257-1950 UTC on 04 April 2023  (above) showed thunderstorms that produced hail up to 4.0 inches in diameter in Iowa and a wind gust to 90 mph in Illinois (along with a brief tornado) (SPC Storm Reports).

1-minute GOES-16 Visible/Infrared Sandwich RGB images with an overlay of GLM Flash Extent Density (below) revealed several lightning jumps as the storms moved eastward during that time period.

The Sandwich RGB images helped to highlight the presence of Above-Anvil Cirrus Plumes (reference | VISIT training) — and one of the more prominent AACP examples is shown in a toggle between GOES-16 “Clean” Infrared Window (10.3 µm) and “Red” Visible (0.64 µm) images at 1727 UTC (above). With the northernmost storm, the coldest cloud-top 10.3 µm infrared brightness temperature in the overshooting top area was -71ºC (darker shades of red), in contrast to the warmer downwind plume where infrared brightness temperatures were around -59 to -60ºC (brighter shades of yellow).

According to a plot (source) of 1800 UTC rawinsonde data from Quad Cities, Iowa (below), the -71ºC infrared brightness temperature corresponded to a Most Unstable (MU) air parcel overshoot of about 1 km from its 200 hPa Equilibrium Level (EL), while the -60ºC AACP infrared brightness temperature was close to those seen in the stratospheric portion of the sounding.

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