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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Previous blog posts have documented how to display imagery using geo2grid, and how to create new RGB products. (Note: geo2grid v1.1 is now available at this link) This blog post will detail the steps needed to create a brightness temperature difference field. For that to occur, information must be entered into these two files within the geo2grid file structure: $GEO2GRID_HOME/libexec/python_runtime/etc/polar2grid/enhancements/abi.yaml and $GEO2GRID_HOME/libexec/python_runtime/etc/polar2grid/composites/abi.yaml. For this example, I created a Water Vapor Brightness temperature difference field (named ‘wvdif’), as used with the airmass RGB (Here’s a Quick Guide for that RGB). The information added to the $GEO2GRID_HOME/libexec/python_runtime/etc/polar2grid/composites directory in the abi.yaml file (defining the bands used to create the product) is shown below. Indentations are important here; the ‘wvdif’ line is indented two spaces! In plain language, Band 10 (low level water vapor, 7.3 µm) is subtracted from Band 8 (upper level water vapor (6.19 µm).

  wvdif:
    compositor: !!python/name:satpy.composites.DifferenceCompositor
    prerequisites:
      - name: C08
      - name: C10
    standard_name: wvdif

Information added to abi.yaml file in the $GEO2GRID_HOME/libexec/python_runtime/etc/polar2grid/enhancements directory (indentations are important here; the ‘wvdif’ line is indented two spaces) is shown below. This gives the range of values that are of interest; in the RGB, values of the Water Vapor Brightness Temperature difference range from -26.2^oC to 0.6^oC. Note that ‘max_stretch’ and ‘min_stretch’ correspond to values with the greatest and smallest, respectively, amounts of red in the RGB.

  wvdif:
    standard_name: wvdif
    operations:
      - name: stretch
        method: !!python/name:satpy.enhancements.stretch
        kwargs:
          stretch: crude
          min_stretch: -26.2
          max_stretch: 0.6

The geo2grid software calls that creates the temperature difference field, and color-enhances it, and applies coastlines and a latitude/longitude grid are shown below (this geo2grid call also makes the airmass RGB, the RGB that uses the water vapor difference field as the red component of the RGB). Note that because a color bar is not added by the add_coastlines.sh script (as discussed in this blog post), multiple .tif files can be referenced.

$GEO2GRID_HOME/bin/geo2grid.sh -r abi_l1b -w geotiff -p airmass wvdif -f /path/to/ABIdata/L1b/RadC/*s20223430001*

$GEO2GRID_HOME/bin/add_colormap.sh /path/to/enhancements/Red1.txt   GOES-16_ABI_RadC_C13_20221209_000117_GOES-East.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. 10.  --grid-text-size 14 *1209_0001*.tif

The animation at the top shows the airmass RGB, the greyscaled water vapor difference field, and the water vapor difference field enhanced to show how much red will be in the airmass RGB.

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The VIIRS (Visible/Infrared Imaging Radiometer Suite) instrument on-board NOAA-21 (launched in November 2022) is now sending data to Earth. (Here is the NOAA Satellite Tweet announcing this landmark occasion!). Direct Broadcast users can also view NOAA-21 data now; the image above was downloaded and processed using the latest Community Satellite Processing Package (CSPP) at CIMSS. (Users must also update their antenna demodulator to allow receipt of NOAA-21 data!).

The VIIRS instrument has great resolution, as shown in the subsected views below of Long Island (partially hidden by thin cirrus, Florida, and ice-covered Lake Winnipeg. NOAA-21 will be undergoing testing and evaluation over the next months prior to being declared operational.

Direct Broadcast users will note that NOAA-21 and Suomi NPP conflict; that is, users with a single antenna must choose to download data from one or the other.

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The image below, courtesy Kathy Strabala and Liam Gumley, CIMSS, shows an image similar to the NOAA Satellite Tweet. The image below was created with SDR data from NOAA CLASS, and those data were processed with CSPP’s Polar2Grid (v 2.3) software (downloadable here).

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GOES-16 (GOES-East) Nighttime Microphysics RGB and Day Snow-Fog RGB images (above) showed a lake effect fog/stratus plume that was meandering slowly northward from the still-unfrozen Fort Peck Lake in northeastern Montana (just south of Glasgow) on 08 December 2022.

During the hours leading up to sunrise, GOES-16 Nighttime Microphysics RGB images with an overlay of the GOES-16 Cloud Top Phase derived product (below) indicated that the majority of this lake effect fog/stratus plume had tops consisting of supercooled water droplets.

The GOES-16 Cloud Thickness product (above), a component of the Fog/Low Stratus (FLS) suite, showed that this fog/stratus feature was generally 1000 feet thick or less — confined to a strong but shallow low-level temperature inversion, according to plots of rawinsonde data from Glasgow (below).

Once this fog/stratus plume began to move over Glasgow shortly after 1000 UTC, their surface observations revealed frequent fluctuations in the surface visibility, along with periods of freezing fog and occasionally some light snow (below). In addition, these conditions likely had an impact on travel along US Highway 2 (which runs northwest-to-southeast through the Glasgow area).

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