This recent blog post highlighted an Advanced Microwave Scanning Radiometer (AMSR-2) product showing estimates of Sea Ice concentration at high spatial resolution. This followup post shows the product on a different day in 2022. The MODIS True-Color imagery below, from March 22, 2022, shows ice in the Bering Sea and Arctic Ocean surrounding Alaska. The red arrows highlight a large lead north of Russia, and an area of open water near the coast in Bristol Bay. Note also the irregular edge to the sea ice in the Bering Sea, and shore-fast ice along the northern edge of Kuskoskim bay. (An Alaskan map here (source) might help with geographic names)

Ice Concentration from microwave data from the Advanced Technology Microwave Sounder (ATMS; on Suomi-NPP and NOAA-20 at the time; NOAA-21 now also carries ATMS) and AMSR-2 is shown below. The better resolution from the AMSR-2 imagery allows a much better depiction of the open lead north Russia, the open water over northern Bristol Bay, the ragged southern edge of the ice sheet, and the shore-fast ice. This product continues to be evaluated by the Alaskan Ice Desk.

Thanks to Tom Greenwald, SSEC/CIMSS, for the imagery in this post

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Metop-B and Merop-C overflew the same region of the tropical western Pacific to the east of Guam on 21 August 2023, as shown above (imagery dowloaded from the ‘manati’ website). Metop-C imagery is from 1041 UTC, Metop-B from 1128 UTC. There are two wind maxima in both plots, centered near 13^oN, 156^oE and near 18^oN, 155^oE, and highlighted by the blue arrows in the toggle above. What can you infer from just these plots? The stronger winds are likely associated with convection, and the convection near 18^oN (the northern convection, vs. the southern convection near 13^oN) might be more long-lasting, given its proximity to the shear line (denoted by the red line in the toggle). The 1030 UTC image, below, shows the deep convection associated with these wind events.

Does the southern convection seems less long-lived than the northern convection? Hard to tell from just this two-plus-hour animation below.

Himawari-9 imagery from the Pacific Island 1 sector at this website, from 21 August 2023, below, does show persistent convection near the shear line (the invest 90W according to JTWC); the southern convection is not as long-lived.

The best way to interpret a single satellite data source is to incorporate other satellite data into the analysis!

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GOES-18 Mid-level Water Vapor (6.9 µm) images, with an overlay of Surface Pressure analyses (beige) and 1-hour Precipitation Accumulation (red) [click to play animated GIF | MP4]

GOES-18 (GOES-West) Mid-level Water Vapor (6.9 µm) images (above) included plots of 1-hour Precipitation Accumulation — which showed rainfall associated with the northward spread of moisture across the Southwest US as Tropical Storm Hilary made landfall in Baja California on 20 August 2023. A similar animation with plots of 6-hour Precipitation Accumulation is available here. There were numerous daily rainfall records set, with widespread reports of flash flooding across parts of southern California and southern Nevada.

Hourly images of the MIMIC-TPW product (below) also showed the northward transport of abundant tropical moisture ahead of Hilary.

Hourly MIMIC-TPW product [click to play animated GIF | MP4]

New record maximum Total Precipitable Water (TPW) values were established for 1200 UTC soundings on 20 August at both San Diego, California and Las Vegas, Nevada (below).

Climatology of 1200 UTC sounding Total Precipitable Water (TPW) for San Diego, California– with the TPW value for 20 August 2023 indicated by a gray circle [click to enlarge]

Climatology of 1200 UTC sounding Total Precipitable Water (TPW) for Las Vegas, Nevada — with the TPW value for 20 August 2023 indicated by a gray circle [click to enlarge]

In addition, the all-time record maximum 0000 UTC sounding Total Precipitable Water (TPW) value of 2.38 inches was tied at San Diego, California (below).

Climatology of 0000 UTC sounding Total Precipitable Water (TPW) for San Diego, California– with the TPW value for 21 August 2023 indicated by a gray circle [click to enlarge]

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Polar2Grid is a powerful software package that enables a user to take Sensor Data Record (SDR) files from JPSS satellites (Suomi-NPP, NOAA-20, NOAA-21) and create high-quality georeferenced imagery that can be color-enhanced. (Polar2Grid also works with data from other polar orbiting satellites!) This blog post details how to scale an infrared image to specific brightness temperature bounds that are then shown with a colorbar embedded into the image. This is similar to what is done with ACSPO Sea Surface Temperatures as discussed in this online documentation. Data for this example were downloaded from the CIMSS Direct Broadcast site. I wanted to show I05 VIIRS imagery (11.45 µm) so I downloaded both the SVI05 and GIMGO hdf files on 16 August 2023 covering the times 0832 and 0840 UTC. These data, from NOAA-21, can came from the directory https://bin.ssec.wisc.edu/pub/eosdb/j02/viirs/2023_08_16_228_0828/sdr/ (this directory will be purged on 8/23). You can also get these data from NOAA CLASS, or from online web services such as Amazon Web Services (AWS link for NOAA-21). Before invoking the Polar2Grid commands to create the imagery, you must specify the I05 Brightness Temperatures of interest, done by adding the following snippet of code to the viirs.yaml file that can be found in this directory: $POLAR2GRID_HOME/etc/polar2grid/enhancements/ In the case below, I’m interested initially just in the values between 170 and 330 Kelvin, using a linear stretch.

 I05:
    name: I05
    sensor: viirs
    operations:
      - name: linear_stretch
        method: !!python/name:satpy.enhancements.stretch
        kwargs: {stretch: 'crude', min_stretch: 170., max_stretch: 330.}

Next, run the Polar2Grid commands to specify (optionally) a region of interest, and to generate the tif file of the imagery in that specified domain.

$POLAR2GRID_HOME/bin/p2g_grid_helper.sh Madison -89.0 43.8 375.0 -375.0 1280 960 > $POLAR2GRID_HOME/bin/MSN.yaml

$POLAR2GRID_HOME/bin/polar2grid.sh -r viirs_sdr -w geotiff -p i05 -g Madison --grid-configs $POLAR2GRID_HOME/bin/MSN.yaml -f /path/to/downloaded/SVI05andGIMGOFiles.h5

The commands above create a tif file: noaa21_viirs_i05_20230816_083259_Madison.tif. The first of the two commands below adds a color enhancement to the tif file; the second adds coastlines and a colorbar to the tif file and outputs a png file: noaa21_viirs_i05_20230816_083259_Madison.png . That image, scaled from 170 to 330 K, is shown below.

$POLAR2GRID_HOME/bin/add_colormap.sh $POLAR2GRID_HOME/colormaps/p2g_sst_palette.txt noaa21_viirs_i05_20230816_083259_Madison.tif 

$POLAR2GRID_HOME/bin/add_coastlines.sh --add-coastlines --coastlines-resolution f --add-colorbar noaa21_viirs_i05_20230816_083259_Madison.tif 

It’s apparent above that the range chosen for the image above is too broad. So, edit the I05 definition in the viirs.yaml file shown up top, changing the one line to this: kwargs: {stretch: 'crude', min_stretch: 230., max_stretch: 300.}. Then, rerun the polar2grid, add_colorbar and add_coastlines commands above. The result below shows a toggle between those two results. Note how things change as you might expect.

The image with more color contrast from cold to warm shown above is the same one as shown at the top of the image, but I’ve modified the presentation of the coastlines and colorbar in the add_coastlines command: $POLAR2GRID_HOME/bin/add_coastlines.sh --add-coastlines --coastlines-resolution f --add-colorbar --colorbar-text-size 16 --colorbar-height 32 noaa21_viirs_i05_20230816_083259_Madison.tif

Polar2Grid software can be downloaded from this website; Polar2Grid documentation is here.

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