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

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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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GOES-16 (GOES-East) “Red” Visible (0.64 µm) images (above) include plots of GOES-16 Derived Motion Winds (DMW) within the 775-900 hPa and the 900 hPa-Surface layers — which displayed a rapidly-intensifying area of low pressure (surface analyses) over the West Atlantic Ocean (south of Nova Scotia, Canada) on 12 December 2022. Note the area of haziness just east and southeast of the lobe of deep convection in the center of the satellite scene — this milky/hazy appearance was due to the enhanced diffuse reflection of light off very rough seas (likely accompanied by abundant sea spray) resulting from a burst of strong surface winds across that particular area. Several nearby DMW vectors within the 900 hPa-Surface layer exhibited speeds of 50 knots or higher, including 62 knots at 1446 UTC and 59 knots at 1746 UTC. In addition, GCOM-W1 AMSR2 surface winds (source) in the vicinity of the diffuse reflection signature were around 60 knots at 1813 UTC.

This region of enhanced diffuse reflection was further highlighted in GOES-16 True Color RGB images from the CSPP GeoSphere site (below).

The corresponding GOES-16 Low-level Water Vapor (7.3 µm) images (below) showed an area of orange enhancement that likely represented rapidly-descending (and hence warming/drying, via adiabatic compression) air within the lower troposphere, which was rotating around the southeastern and eastern edge of the lobe of deep convection.

A sequence of Suomi-NPP VIIRS Visible (0.64 µm), Near-Infrared “Vegetation” (0.87 µm), Near-Infrared “Snow/Ice” (1.61 µm), Shortwave Infrared (3.74 µm), Infrared Window (11.45 µm), True Color RGB and False Color RGB images — along with the corresponding GOES-16 Derived Motion Winds near that time (below) provided a more detailed view of the area of enhanced diffuse reflection. Also apparent at that time was the hook-like shape along the southeastern edge of the lobe of deep convection, somewhat resembling a “scorpion tail” that is frequently seen in cases of a sting jet (Monthly Weather Review | Wikipedia).

The aforementioned satellite signatures in this case resemble those seen with another rapidly-intensifying low off the coast of North Carolina in April 2019, which also featured a sting jet.

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[Added, 14 December: geo2grid v 1.1 is now available at this link!] The true color animation toggle above, over Taiwan, shows True-Color imagery over Taiwan shortly after 0000 UTC on 8 December using FY4A and Himawari-9 data; readers for data from those satellites are included in version 1.1 of geo2grid. Data from Himawari-9 (HSD level 1b files) are supplied courtesy of JMA, the Japan Meteorological Agency. FY4A data from CMA are available at this link (free registration is required to download the data). At that site (shown below), you can choose AGRI data from FY4A, and the download link is available on a separate page that becomes available after choosing the day and time. (In the screen capture, the 500-m resolution checked is only Channel 2, whereas the file used for this blog post is the topmost one — with a size of 355 Mbytes; this file took some time to download).

First, you can user –list-products to determine what can be created from the hdf file:

$GEO2GRID_HOME/bin/geo2grid.sh -r agri_fy4a_l1 -w geotiff --list-products -f /data-hdd/AGRI/FY4A-_AGRI--_N_DISK_1047E_L1-_FDI-_MULT_NOM_20221208001500_20221208002959_1000M_V0001.HDF

The output showed the following possibilities: C01, C02, C03, true_color. This WMO website ( https://space.oscar.wmo.int/instruments/view/agri ) shows that C01-C03 on the AGRI instrument correspond to wavelengths of 0.47 µm, 0.65 µm and 0.83 µm. Two commands are run as shown below; the first one creates a small mapped region (a similar restriction to how much data to process could be achieved using the –ll-box keyword in geo2grid), the second creates the image over that domain:

$GEO2GRID_HOME/bin//p2g_grid_helper.sh Taiwan 121.0 24.0 1000 -1000 960 720 > $GEO2GRID_HOME/Taiwan.yaml

$GEO2GRID_HOME/bin/geo2grid.sh -r agri_fy4a_l1 -w geotiff -p true_color --grids Taiwan --grid-configs $GEO2GRID_HOME/Taiwan.yaml -f /data-hdd/AGRI/FY4A-_AGRI--_N_DISK_1047E_L1-_FDI-_MULT_NOM_20221208001500_20221208002959_1000M_V0001.HDF

The geo2grid.sh invocation here does not have access to all the information that is needed, and the output notes that solar zenith angle correction in the true color will not occur.

INFO     : Sorting and reading input files...
INFO     : Loading product metadata from files...
WARNING  : Required file type 'agri_l1_4000m_geo' not found or loaded for 'satellite_azimuth_angle'
WARNING  : Required file type 'agri_l1_4000m_geo' not found or loaded for 'solar_zenith_angle'
WARNING  : Required file type 'agri_l1_4000m_geo' not found or loaded for 'solar_azimuth_angle'
WARNING  : Required file type 'agri_l1_4000m_geo' not found or loaded for 'satellite_zenith_angle'
INFO     : Checking products for sufficient output grid coverage (grid: 'Taiwan')...
INFO     : Resampling to 'Taiwan' using 'nearest' resampling...
INFO     : Computing products and saving data to writers...
INFO     : SUCCESS

The invocation of geo2grid to read the Himawari data (that does include information for the solar zenith angle correction) and the output from that call is shown below.

$GEO2GRID_HOME/bin/geo2grid.sh -r ahi_hsd -w geotiff -p true_color --grids Taiwan --grid-configs $GEO2GRID_HOME/Taiwan.yaml -f /path/to/data/himawari09/2022/2022_12_08_342/0020/*FLDK*.DAT
INFO     : Sorting and reading input files...
INFO     : Loading product metadata from files...
INFO     : Checking products for sufficient output grid coverage (grid: 'Taiwan')...
INFO     : Resampling to 'Taiwan' using 'nearest' resampling...
INFO     : Computing products and saving data to writers...
INFO     : SUCCESS

You will note a slight shift in the imagery in the toggle above, suggesting different navigations for the two satellites.

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GOES-16 (GOES-East) Air Mass RGB images (above) showed the signature of dry air (brighter shades of orange-red, which also indicate the presence of a lower tropopause with higher levels of stratospheric ozone within the atmospheric column) wrapping into the circulation of an anomalously-deep Hurricane Force low pressure system — which had recently rapidly intensified over the North Atlantic Ocean — during the 09 December – 10 December 2022 period (surface analyses).

A closer view of GOES-16 Air Mass RGB images (below) includes plots of land-based surface reports — and as the system slowly weakened to a Storm Force low about 200 miles NW of the Azores at 12 UTC on 10 December, a wind gust to 55 knots (63 mph) was recorded at Flores Airport in the far NW part of that island chain (RGB image | plot of surface data).

GOES-16 Mid-level Water Vapor (6.9 µm) images (below) exhibited a similarly-striking appearance, with the ribbon of dry air wrapping into the center of the storm’s circulation having 6.9 µm infrared brightness temperatures as warm as +4 to +5ºC (darker shades of orange). 

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