The Japan Meteorological Agency (JMA) maintains a website that has imagery in various sectors under Himawari-8’s gaze. This blog post will describe how to automatically access those data. This is useful if you want to create and maintain a long archive of imagery. The front page of the website is shown here. At the top of the image you’ll see Full Disk thumbnails that you can click on, and if you scroll down, you’ll see subsected regions, such as Australia, various Pacific Island groups, regions of southeast Asia, etc. Note especially that each sector has a Filelist link you can click — more on that later.

If you click (for example) on Southeast Asia 1, you will see a website (below) that includes drop-down menus, and an imagery window, as shown below, with and without annotations. You can choose a different area, a different time (within the past 24 hours) to display, control animation length (1, 3, 6, 12, 18 or 23 hours), and choose which Band to display.

The Bands to display are shown below. The individual bands are grey-scaled. The RGBs available are discussed at this JMA site — this is also the link shown right above the Band Drop-down Menu (“RGB Training Library (JMA Website)“)

The Filelist link will take you to the directory (here is the one for Southeast Asia 1, here’s the one for Pacific Islands 1) where the images that are displayed on the website are stored. This is a 24-hour archive of subsected imagery. The imagery is not generally full-resolution, although there are small sectors that do show full-resolution: over the Solomon Islands, over Vanuatu, and over Fiji. In general, resolution is sacrificed for ease of access.

Because the files for each sectors are always in the same place (the same url), it is straightforward to write up a unix cron job to access the imagery and save it. A shell script to use is shown below. wget calls access the data — in this case Pacific Island Group 1 (pi1) — and move it to your local machine for images separated by 10 minutes. Then a directory is created into which the data are then moved. I have a shell script like this that runs every day just before 0000 UTC to gather the 142 files created over the course of the day. The animation created from the imagery (Sandwich Product — the snd in the file name! — over Pacific Island Region 1, which region includes Guam) for 17 March 2022 is shown at the top of this blog post. (Here’s a similar animation for 16 March 2022). One could accumulate data over a small region every day and create a very long animation.

#!/bin/sh/
cd /home/scottl/JMA/
wget -r https://www.data.jma.go.jp/mscweb/data/himawari/img/pi1/pi1_snd_0000.jpg .
wget -r https://www.data.jma.go.jp/mscweb/data/himawari/img/pi1/pi1_snd_0010.jpg .
.
.
.
wget -r https://www.data.jma.go.jp/mscweb/data/himawari/img/pi1/pi1_snd_2350.jpg .
DIRNAME=`date '+PI1SND%m%d%y'`
mkdir $DIRNAME
FILENAME=`date '+pil_snd_0000_%m%d%y'.gif`
out=`mv /home/scottl/JMA/www.data.jma.go.jp/mscweb/data/himawari/img/pi1/pi1_snd_0000.jpg /home/scottl/JMA/$DIRNAME/$FILENAME`
FILENAME=`date '+pil_snd_0010_%m%d%y'.gif`
out=`mv /home/scottl/JMA/www.data.jma.go.jp/mscweb/data/himawari/img/pi1/pi1_snd_0010.jpg /home/scottl/JMA/$DIRNAME/$FILENAME`
.
.
.
FILENAME=`date '+pil_snd_2350_%m%d%y'.gif`
out=`mv /home/scottl/JMA/www.data.jma.go.jp/mscweb/data/himawari/img/pi1/pi1_snd_2350.jpg /home/scottl/JMA/$DIRNAME/$FILENAME`
rm -rf www.data.jma.go.jp/

Be mindful that you are using an image created by someone else! It’s always a good idea to include attribution, in this case back to JMA, when you show the imagery.

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GOES-16 Dust RGB images [click to play animated GIF | MP4]

GOES-16 (GOES-East) Dust RGB images (above) highlighted the development of widespread plumes of blowing dust (brighter shades of pink/magenta) across parts of New Mexico and Texas on 17 March 2022. Surface visibility was reduced to 1.5 miles at some locations, with wind gusts in the 40-50 knot range (a peak wind of 56 knots was recorded at Dalhart in the Texas Panhandle) . 

GOES-16 True Color RGB images created using Geo2Grid (below) provided another view of the blowing dust plumes (shades of tan to light brown), as well as a few narrow plumes of smoke (dull shades of white) from wildfires that spread quickly due to the strong winds.

GOES-16 True Color RGB images [click to play animated GIF | MP4]

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GOES-16 “Red” Visible (0.64 µm, top left), Shortwave Infrared (3.9 µm, top right), Fire Power (bottom left) and Fire Temperature (bottom right) products [click to play animated GIF | MP4]

GOES-16 (GOES-East) “Red” Visible (0.64 µm), Shortwave Infrared (3.9 µm). Fire Power and Fire Temperature products (above) displayed signatures of a fire at the Walmart Distribution Center in Plainfield, Indiana on 16 March 2022. The fire was first detected at 1646 UTC, and an hour later the 3.9 µm Shortwave Infrared brightness temperature reached 74.1ºC at 1746 UTC — the maximum derived Fire Temperature value was 580.74 K, and Fire Power values peaked at 433.72 MW (the Fire Temperature and Fire Power derived products are components of the GOES Fire Detection and Characterization Algorithm FDCA).

GOES-16 True Color RGB images from the CSPP GeoSphere site are shown below; the initial cloud of dark black smoke began to move across the Indiana/Ohio border around 23 UTC.

GOES-16 True Color RGB images [click to play animated GIF | MP4]

A sequence of VIIRS True Color RGB, False Color RGB and Shortwave Infrared (3.74 µm) images from NOAA-20 and Suomi-NPP are shown below. These VIIRS images were acquired and processed by the Direct Broadcast ground station at SSEC/CIMSS — and are available for display in AWIPS via a Unidata LDM subscription.

VIIRS True Color RGB, False Color RGB and Shortwave Infrared (3.74 µm) images from NOAA-20 and Suomi-NPP [click to enlarge]

The eastern edge of the smoke plume passed over Indianapolis Eagle Creek Airport (KEYE), located about 5 miles north-northeast of the fire — since the smoke had been lofted to altitudes of 7,000-10,000 feet, it did not affect the surface visibility at that site.

Time series of surface observation data from Indianapolis Eagle Creek Airport [click to enlarge]

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Ice coverage on Lake Superior has reached a seasonal peak. The image above shows VIIRS true-color imagery from Suomi-NPP (taken from the VIIRS Today website). Mostly clear skies over most of Superior on 14 March allowed for better estimates of ice cover on that day from VIIRS (more clouds were present on 15 March).

Ice-cover mapping from NOAA’s GLERL (The Great Lakes Environmental Research Laboratory), shown below (from this website) also shows extensive ice cover over Lake Superior. (Blue regions indicate open water.)

The analysis below (also from the GLERL site, at this link) shows how the ice cover has varied over the course of the winter over Superior. The present maximum is the largest ice extent of the season — and the ice cover is greater than normal. Ice cover over Superior typically peaks in early March.

When clouds are present (and when they are not!), Synthetic Aperture Radar (SAR) imagery (available in near-real time at this website) gives very high-resolution information about ice formation on Lakes. The image below shows the Normalized Radar Cross Section (NRCS) from 15 March 2022 just before 1200 UTC. Open water is indicated (flat black surfaces) just east of the Keewenaw Peninsula, just east of Isle Royale, in a strip along the western shore of the lake, and in a large region in central Lake Superior to the east of the tip of the Keewenaw Peninsula.

NOAA/STAR does have a Great-Lakes specific SAR website that includes imagery mapped to all 5 Great Lakes. (Link). The mp4 animation below, using images from that website, shows the 11 most recent Lake Superior images of NRCS, ending at ca. 1200 UTC on 15 March. A lot of the views include Duluth Harbor.

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