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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Polar2Grid version 3.0 (released earlier this year; see this blog post, and this one on displaying individual VIIRS channels) has the capability (like earlier versions) to create imagery from selected individual ATMS (Advanced Technology Microwave Sounder) channels, and for some derived products as well. In this example, I would like to create imagery on February 3rd and 4th around the Hawai’ian Islands. The ATMS is an instrument on board Suomi-NPP, NOAA-20, and NOAA-21. When, during those two days (I’m most interested in early morning on the 4th), did these Low Earth Orbit satellites view the Hawai’ian Island chain? The SSEC Polar Orbit Track website answers that question. Orbits are shown below from the ‘Hawaii’ sector at that website for Suomi NPP (3 February, 4 February), NOAA-20 (3 February, 4 February) and NOAA-21 (3 February, 4 February) are shown below. Overpass times of interest are, for NOAA-20, 23:30-23:35 on 3 February and 12:00-12:05 on 4 February; for Suomi-NPP, 12:50-12:55 on 4 February; for NOAA-21, 23:55-23:59 on 3 February and 12:23-12:30 on 4 February.

Polar2Grid software expects data of a certain type. When ordering the data from NOAA-CLASS, select JPSS Sounder Products as shown below, and then click GO:

After clicking ‘GO’ you will see the order page, as shown below. The one below is filled out for NOAA-20 data between 12:00 and 12:05 on 4 February. The Datatype is ‘MIRS Precipitation and Surface Products’ — and the NOAA-20 Satellite is checked. (Note that for this date/time, NOAA-21 data are not available, as data were still provisional; once data become operational, a ‘NOAA-21’ selection will be available). You will also note that a map is available, and one could order data based on latitude/longitude bounds on the map, but I find ordering specific times simpler.

When you click on ‘Search’, one file is returned, as shown below. Order it!

The file supplied by NOAA CLASS, below, is a tar file and contains data from 1158 though 1208 UTC. Download the file from NOAA CLASS and un-tar it on your local machine.

NPR-MIRS-IMG_v11r8_n20_s202302041158026_e202302041208103_c202302041230480.tar

Note that only IMG files are recognized by Polar2Grid; if have instead a SND file by mistake, go back and re-order! The expanded tar file included 19 separate files, each holding about 30 seconds’ worth of data. I put the data into a single directory, and used Polar2Grid’s –list-products-all in conjunction with the ‘mirs‘ reader to see what kind of data and products were available, that is:

./polar2grid.sh -r mirs -w geotiff --list-products-all -f /path_to_data/WFOHNL/MIRS/N201/*.nc .

Many different individual channels and products are available, as shown below, in a list I’ve modified from the Polar2Grid output (which gives one per line!).

Next — after downloading other days/times from Suomi-NPP — I created a mapping region for the data using the p2g_grid_helper shell scripts that sits within the Polar2Grid bin directory. The p2g_grid_helper command I used is below. The grid (‘HNL’) — with a grid spacing of 750 x 750 m — is centered, roughly, on Honolulu, has 1440 elements and 1200 lines, and the created attributes are stored in the named yaml file. (The grid resolution is much greater than the ATMS microwave resolution, which for 31 GHz is at best 75 km!)

I want to create images for 31 and 88 GHz data, and also the MIRS Total Precipitable Water product. The Polar2Grid call, using the mirs reader and the geotiff writer, is shown below; the -p (for product) flag is followed by the list of fields to create, and the fields are gridded onto the HNL grid that has specifications within the yaml file specified with the –grid-configs flag.

./polar2grid.sh -r mirs -w geotiff -p btemp_88v btemp_31v tpw -g HNL --grid-configs $POLAR2GRID_HOME/HNL.yaml -f /path_to_data/WFOHNL/MIRS/N201/NPR-MIRS-IMG_v11r8_*.nc

The Polar2Grid command above created three files: noaa20_atms_btemp_88v_20230204_115802_HNL.tif, noaa20_atms_btemp_31v_20230204_115802_HNL.tif and noaa20_atms_tpw_20230204_115802_HNL.tif. I did a similar command with Suomi NPP data from NOAA CLASS.

Polar2Grid supplies software to add information to these files. For example, the grey-scaled .tif files can be color-enhanced using the add_colorbar script:

./add_colormap.sh /home/scottl/Polar2Grid/polar2grid_v_2_3/colormaps/amsr2_36h.cmap n*atms*_HNL.tif

The command above transforms all the .tif files that match the wildcarded name — including both noaa20 and npp imagery — to .tif files that are color enhanced. Next, I used ./add_coastlines.sh to add the Hawai’ian islands, and a colorbar to all of the .tif images matching the wildcarded filename. A png file for each matching .tif file was created.

./add_coastlines.sh –add-coastlines –coastlines-resolution f –add-colorbar –colorbar-height 32 –colorbar-text-size 16 –colorbar-tick-marks 25 n*_HNL.tif

I added annotation to the images, using ImageMagick. Results are shown at top (for 31 GHz) and below (for 88 GHz and MIRS total precipitable water (TPW)).

The 31 GHz imagery at the top shows a region south of Oahu where nominally warmer brightness temperatures (lighter blue surrounded by darker blue (see this annotated image — focus between the two arrows)) What might happen as this region moves over the islands?

Microwave data can also reveal wind structures that might effect convective development. ASCAT imagery from MetopB and MetopC, below, do show an expansion of stronger winds and the development of shear between the ascending (left in the image below) and descending (right in the image below) passes.

GOES-18 Visible (below) and Infrared (at bottom) imagery both show the development of convection starting along the north shore of Oahu and developing westward across the entire island. An interesting question is: Did the faint feature apparent in the microwave imagery affect the convective development?

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Sentinel-1A overflew the western Hawai’ian islands late on 4 April 2023, observing surface winds around the islands of Kaua’i and Ni’ihau. The image above shows the winds overlain on top of a GOES-18 infrared image. A pronounced region of light winds extends downwind of both islands — the region in purple shows winds of 5 knots or less.

MetopB overflew the Hawai’ian island chain about 3 hours after Sentinel-1A did (link), and its overpass was also bookended by two MetopC overpasses (shown here). Those two wind plots are shown below (from this website). Neither satellite gave information where the SAR Winds occurred, and the slack winds in the lee of the islands would likely not be resolved by ASCAT’s 25-km footprint.

A GOES-18 animation of visible imagery before and through the SAR overpass is shown below. It is very difficult to identify a region of slack winds around the islands from the visible imagery. Modest convection forms in the lee of Ni’ihau as the sun sets. The Band 13 animation at bottom shows the convection to be short-lived.

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Sentinel-1A SAR winds are available at this NOAA/NESDIS/STAR website. The toggle below shows the winds and the Normalized Radar Cross Section field at 0446 UTC on 4 April from that site.

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