The latest release of the CSPPGeo software package geo2grid (version 1.1, downloadable here) includes support to display two Level 2 products from GOES-R: Cloud Top Temperature and Cloud Top Height. Cloud Top Temperature, above, created using data ordered and downloaded from the NOAA CLASS site, is at 2-km resolution (in line with the latest Algorithm Theoretical Basis Document — ATBD — for the product), and is created for every time step in the Full Disk and Mesoscale Domains. The commands to create this image are shown below. The ‘SubTrop’ grid used was created as shown in this blog post.

../geo2grid.sh -r abi_l2_nc -w geotiff -p TEMP --grids SubTrop --grid-configs $GEO2GRID_HOME/SubTrop.yaml -f $GEO2GRID_HOME/bin/Level2/CLASSData/OR_ABI-L2-ACHTF-M6_G16_s20223501500*.nc

../add_coastlines.sh -o GOES-16_ABI_TEMP_20221216_150020_SubTropCLASS.png  --add-grid --grid-D 5.0 5.0 --grid-d 5.0 5.0 --add-coastlines --grid-text-size 14 --add-colorbar --colorbar-align right --colorbar-text-size 10 --colorbar-tick-marks 100 GOES-16_ABI_TEMP_20221216_150020_SubTrop.tif

Cloud-top Height is shown below, from 3 data sources: The SBN, NOAA CLASS, and CSPPGeo Algorithm Integration Team (AIT) software. You will note that both SBN and CLASS (produced from the GOES-R Ground System) show (identical) data with 10-km resolution (AWIPS imagery likewise shows 10-km resolution for this field). Only the CSPPGeo AIT output shows the data at 2-km resolution (in agreement with the latest ATBD for this product). This degraded resolution for Cloud Top Height (and other cloud products) is a known issue/risk at NESDIS affecting Clear Sky Radiances that are then assimilated into numerical prediction models. Work continues to update the Ground System to mitigate this risk. The commands to create the imagery from downloaded CLASS data are shown below.

../geo2grid.sh -r abi_l2_nc -w geotiff -p HT --grids SubTrop --grid-configs $GEO2GRID_HOME/SubTrop.yaml -f $GEO2GRID_HOME/bin/Level2/CLASSData/OR_ABI-L2-ACHAF-M6_G16_s20223501500207_e20223501509515_c20223501512366.nc

../add_coastlines.sh -o GOES-16_ABI_HT_20221216_150020_SubTropCLASS.png  --add-grid --grid-D 5.0 5.0 --grid-d 5.0 5.0 --add-coastlines --grid-text-size 14 --add-colorbar --colorbar-align right --colorbar-text-size 10 --colorbar-tick-marks 1500 GOES-16_ABI_HT_20221216_150020_SubTrop.tif

The CIMSS Blog also discussed Level 2 products and geo2grid — with an earlier beta version — here.

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IntenseStormNet is a part of the ProbSevere portfolio; it relates ABI Channels 2 (0.64 µm) and 13 (10.3 µm) and GLM observations of Flash Extent Density (see this past blog post for more information) to the likelihood that a given satellite-detected storm is severe. (The probabilities are created from output of a Convolutional Neural Network) The product is available in a RealEarth instance at this link. The animation above shows several cells identified as most likely to support severe weather (here is the 1630 UTC Convective Outlook from SPC; much of southeastern Louisiana, southern Mississippi, southern Alabama and the western Florida Panhandle is under an enhanced risk of Severe weather; extreme eastern Louisiana and parts of the central Gulf Coast — including New Orleans and Mobile — is under a Moderate risk). The most likely candidate is entering southwest Mississippi at 1601 UTC.

A tornado was actually reported just before the animation started, from that suspect cell, in Ville Platte LA, north-northwest of Lafayette, at 1523 UTC. What did IntenseStormNet look for that storm at that time? That’s shown below. The tornadic storm does indeed have a very high probability! Here’s the ProbSevere (version 3) image for the same time. Read-outs for the ProbSevere output are available for that particular Object Number (#706504), available at this (temporary) link and shown at the bottom. Note the strong increase in ICP before the tornadic event.

A Journal Article on this product is available here.

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GOES-16 ABI spectral band 01-16 and Rocket Plume RGB images [click to play animated GIF | MP4]

A sequence of 1-minute Mesoscale Domain Sector GOES-16 (GOES-East) images from all 16 ABI spectral bands along with Rocket Plume RGB images (above) displayed signatures of the launch of EUMETSAT MTG-I1 from the Guiana Space Centre near Kourou, French Guyana (synoptic station identifier 814030) on 13 December 2022. The Ariane-5 rocket booster’s hot thermal signature was seen in all Near-Infrared and Infrared spectral bands (03-16), while the lower-tropospheric rocket condensation cloud plume signature was seen in all 16 spectral bands (moving southeastward, immediately off the coast). Right after launch at 2030 UTC, the peak 3.9 µm infrared brightness temperature sensed by GOES-16 quickly increased from 51.2ºC in the 2030 image (GOES-16 scanned that feature at 20:30:57 UTC) to 60.8ºC in the 2031 UTC image (GOES-16 scanned that feature at 20:31:55 UTC).

Another animation of Rocket Plume RGB images — created using Geo2Grid — is shown below.

GOES-16 Rocket Plume RGB images (credit: Tim Schmit, NOAA/NESDIS/ASPB) [click to play MP4 animation]

16-panel images showing all GOES-16 ABI spectral bands (below) provided another method of tracking the rocket’s condensation plume cloud southeastward motion in all 16 bands.

16-panel images of all GOES-16 ABI spectral bands [click to play animated GIF | MP4]

GOES-16 “Red” Visible (0.64 µm) images from the CSPP GeoSphere site (below) provided a closer view of the rocket’s condensation plume — its deformation in time offshore was due to changes in wind direction and/or wind speed with height. 

GOES-16 “Red” Visible (0.64 µm) images [click to play MP4 animation]

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As noted in this blog post, version 1.1 of geo2grid (available here!) includes support for reading AHI, AMI and AGRI data (in addition to ABI data) from JMA‘s Himawari-8 (and -9), KMA‘s GEOKOMPSAT-2 and CMA‘s FY4A (and FY4B), respectively. These multispectral imagers are similar — but not identical — as shown at the WMO OSCAR websites for AHI, AMI and AGRI. For example, both AHI and AMI detect energy at 510 nm (0.51 µm) that can be used to create true-color imagery. AGRI has detection at 0.47 µm and 0.65 µm only in the visible, so true color must be created using information from a near-infrared band, Band 3 on AGRI with a central wavelength at 0.825 µm (a slightly shorter wavelength than on NOAA’s GOES-R Satellites, where band 3 is at 0.86 µm). The true-color animation above, over Hainan Island and the Gulf of Tonkin, uses data from the three satellites. The ABI and AMI images look very similar; the AGRI image is a bit too brown, likely a result of atmospheric correction algorithms within geo2grid that remove the effects of scattering. The locations of clouds are somewhat different as well because of different parallax shifts from the satellites: Himawari-8 is over the Equator at 140.7^o E, GEOKOMPSAT-2 is over the Equator at 128.2^o E and FY4A is over the Equator at 104.7^o E (Hainan Island is at 110^oE).

Geo2grid can also create single channel imagery that can be color-enhanced as well. The cleanest window detection on AHI/AMI is near 10.4 µm, and near 10.8 µm on AGRI. AGRI has a nadir resolution of 4 km compared to the 2-km resolution on AMI and AHI, and that difference is stark!

The geo2grid code (and ImageMagick for annotation) is shown below. Note that the $GEO2GRID_HOME/bin/add_coastlines.sh command takes as an input a tif file, and outputs (by default) a png with a similar name.

$GEO2GRID_HOME/bin/geo2grid.sh -r agri_fy4a_l1 -w geotiff -p C13 --grids Haikou --grid-configs $GEO2GRID_HOME/Haikou.yaml -f /data-hdd/AGRI/*20221009*.HDF

$GEO2GRID_HOME/bin/geo2grid.sh -r ahi_hsd  -w geotiff -p B13 --grids Haikou --grid-configs $GEO2GRID_HOME/Haikou.yaml -f /data-hdd/AHI/*

$GEO2GRID_HOME/bin/geo2grid.sh -r ami_l1b -w geotiff -p IR105 --grids Haikou --grid-configs $GEO2GRID_HOME/Haikou.yaml -f /data-hdd/AMI/*

$GEO2GRID_HOME/bin/add_colormap.sh ../../../enhancements/IR13_AWIPSAPPROX.txt FY-4A_AGRI_C13_20221009_050004_Haikou.tif

$GEO2GRID_HOME/bin/add_colormap.sh ../../../enhancements/IR13_AWIPSAPPROX.txt GEO-KOMPSAT-2A_AMI_IR105_20221009_050031_Haikou.tif

$GEO2GRID_HOME/bin/add_colormap.sh ../../../enhancements/IR13_AWIPSAPPROX.txt HIMAWARI-8_AHI_B13_20221009_050000_Haikou.tif

$GEO2GRID_HOME/bin/add_coastlines.sh --add-coastlines --coastlines-resolution f --coastlines-level 5 --add-grid --grid-D 10.0 10.0 --grid-d 10.0 10.0 --grid-text-size 14 --add-colorbar --colorbar-text-color "black" --colorbar-title "FY4A Band 13 Clean Windown Brightness Temperature (K)" --colorbar-tick-marks 20 --colorbar-min 330 --colorbar-max 160 --colorbar-text-size 16 --colorbar-height 36 --colorbar-align bottom FY-4A_AGRI_C13_20221009_050004_Haikou.tif

$GEO2GRID_HOME/bin/add_coastlines.sh --add-coastlines --coastlines-resolution f --coastlines-level 5 --add-grid --grid-D 10.0 10.0 --grid-d 10.0 10.0 --grid-text-size 14 --add-colorbar --colorbar-text-color "black" --colorbar-title "AMI Band 13 Clean Windown Brightness Temperature (K)" --colorbar-tick-marks 20 --colorbar-min 330 --colorbar-max 160 --colorbar-text-size 16 --colorbar-height 36 --colorbar-align bottom GEO-KOMPSAT-2A_AMI_IR105_20221009_050031_Haikou.tif

$GEO2GRID_HOME/bin/add_coastlines.sh --add-coastlines --coastlines-resolution f --coastlines-level 5 --add-grid --grid-D 10.0 10.0 --grid-d 10.0 10.0 --grid-text-size 14 --add-colorbar --colorbar-text-color "black" --colorbar-title "AHI Band 13 Clean Windown Brightness Temperature (K)" --colorbar-tick-marks 20 --colorbar-min 330 --colorbar-max 160 --colorbar-text-size 16 --colorbar-height 36 --colorbar-align bottom HIMAWARI-8_AHI_B13_20221009_050000_Haikou.tif
#  The following commands are ImageMagick/Magick annotation commands
convert GEO-KOMPSAT-2A_AMI_IR105_20221009_050031_Haikou.png -gravity Northwest -fill yellow -pointsize 16 -annotate +12+16 "GEOKOMPSAT-2A Clean Window (10.3 um) 0500 UTC 9 October 2022"  GEO-KOMPSAT-2A_AMI_IR105_20221009_050031_HaikouT.png

convert GEO-KOMPSAT-2A_AMI_IR105_20221009_050031_HaikouT.png CIMSS_logo_web_multicolor_PNG_138x100.png -gravity northwest -geometry +30+30 -composite GEO-KOMPSAT-2A_AMI_IR105_20221009_050031_HaikouTL.png

convert HIMAWARI-8_AHI_B13_20221009_050000_Haikou.png     -gravity Northwest -fill yellow -pointsize 16 -annotate +12+16 "Himawari-8 Clean Window (10.3 um) 0500 UTC 9 October 2022"  HIMAWARI-8_AHI_B13_20221009_050000_HaikouT.png

convert HIMAWARI-8_AHI_B13_20221009_050000_HaikouT.png CIMSS_logo_web_multicolor_PNG_138x100.png -gravity northwest -geometry +30+30 -composite HIMAWARI-8_AHI_B13_20221009_050000_HaikouTL.png

convert FY-4A_AGRI_C13_20221009_050004_Haikou.png         -gravity Northwest -fill yellow -pointsize 16 -annotate +12+16 "FY4A Clean Window (10.8 um) 0500 UTC 9 October 2022"  FY-4A_AGRI_C13_20221009_050004_HaikouT.png

convert FY-4A_AGRI_C13_20221009_050004_HaikouT.png      CIMSS_logo_web_multicolor_PNG_138x100.png -gravity northwest -geometry +30+30 -composite FY-4A_AGRI_C13_20221009_050004_HaikouTL.png

convert -delay 200 -adjoin -loop 0 HIMAWARI-8_AHI_B13_20221009_050000_HaikouTL.png GEO-KOMPSAT-2A_AMI_IR105_20221009_050031_HaikouTL.png FY-4A_AGRI_C13_20221009_050004_HaikouTL.png AMI_AHI_AGRI_CleanWindow_20221009_050004_Haikouanim.gif

Note: When I downloaded the FY4A data this time, I downloaded all FY4A data from 0500 UTC, including the 4-km data. When you do this, geo2grid is able to the atmospheric correction (as opposed to what occurred with this blog post). Also: there is a separate reader (agri_fy4b_l1) for AGRI data from FY4B!

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