Metop-B and Metop-C both overflew Tropical Storm Mal as it approached the island of Fiji on 14 November. The toggle above shows the two wind plots from this website, MetopC from 0933 UTC and MetopB from 1013 UTC. The two swaths show the center of the storm moving southeast, skirting the main islands of Fiji. A shortcoming of ASCAT winds in tropical cyclones occurs when winds exceed 40 knots; the wind (and rain) perturbs the ocean surface sufficiently at those speeds to change the backscatter of microwave radiation back to the satellite. Still, ASCAT gives a good overall view of the outer wind fields, including where gales are occurring and where the circulation center sits.

RCM-1 (Radar Constellation Mission-1) overflew Mal at 0637 UTC on 14 November, and the Synthetic Aperture Radar (SAR) wind field from that is shown below (source). The wind analysis from the SAR data (here) suggests that the SW quadrant of the storm has the weakest winds. The blocking effect of the terrain from both Viti Levu (the largest island in the Republic of Fiji) and the Kadavu Islands is apparent in the imagery below, with weaker east-southeast winds in the lee of the islands.

The toggle below compares the SAR winds with the GOES-18 Clean Window infrared (Band 13, 10.35 µm) imagery. There is a significant parallax shift in the infrared imagery; the Republic of Fiji is just east of the dateline, and GOES-West is overhead at the Equator at 137.2^oW. The SAR-derived storm center is likely nearer to the center of the very cold clouds.

Satellite-derived winds are available hourly from GOES-18, and they are shown below. In the vicinity of Mal, only high-level winds can be generated, because only high-level cloud features can be tracked. The structure of Mal is acting as a blocking feature, and upper-level winds are diverted around it. In addition, a poleward outflow jet is apparent to the east and southeast of the storm. Note also the very strong shear at the southern edge of the domain. Low-level winds (in blue) are flowing in an opposite direction to the upper-level winds (in white).

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A second SAR observation, this time from RCM-3, occurred at 1757 UTC. The toggle below shows the change in the infrared imagery between the two SAR observation times, one at 0640, one at 1750 UTC. The development of outer bands in the storm is most notable, as is the appearance of an eye-like structure at 1750 UTC.

By 1750 UTC, SAR winds show a significantly strengthened system southwest of Fiji. A circular eye that is more symmetric is apparent in the SAR imagery, and hints of an eye are starting to develop in the GOES-18 imagery. Note that the GOES-18 Visible imagery has been brightened (0-30 vs. the default 0-130) in this near-sunrise image. (Here is a toggle of the RCM-1/RCM-2 SAR Winds).

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MIMIC Total Precipitable Water fields over the south Pacific near Fiji and Australia, above (source), show the development of a cyclonic circulation in between the ITCZ and SPCZ that moves southward as Cyclone Mal. Some dry air is diagnosed to impinge on the northern part of the storm at the end of the animation.

Himawari-9 Clean Window infrared (10.4) imagery, below, shows the development of a very cold Central Dense Overcast (CDO) by 1600 UTC, with brightness temperatures (violet in the enhancement used) between -85^oC and -90^oC.

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A closer look at 10-minute Himawari-9 Infrared images (below) revealed that cloud-top 10.4 µm brightness temperatures within the CDO were as cold as -96ºC (darker gray pixels embedded within the interior yellow-enhanced region) at 1450 UTC.

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What are shear values like around Mal? The animation below, taken from the SSEC/CIMSS Tropical Weather website (direct link) shows modest amounts of shear over the storm, with significantly more shear to the south.

Morphed microwave imagery (source), below, shows a slow organization of the storm with vigorous convection surrounding about half the eye by 1900 UTC.

The AMSU 89-GHz field at 0952 UTC on 13 November, below (source), also shows evidence of strong convection (i.e., cold brightness temperatures caused by strong scattering of 89 GHz energy by ice) near the storm center.

For more information on Mal, refer to the CIMSS Tropical Website for this storm (link), or to the Fiji RSMC. The forecast for the storm from JTWC (here), shows intensification through 1200 UTC 14 November, and a path that takes the storm very close to Fiji. The forecast graphic from Fiji is shown below, showing something similar to the JTWC graph. Note the times on the graphic below are Fiji Standard time, i.e., UTC + 12.

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Users can view Mal using RealEarth such as in the example above, provided by Alexa Ross, SSEC/CIMSS, that shows true color imagery and Band 9 mid-level water vapor infrared (6.95 µm) imagery from Japan’s Advanced Himawari Imager (AHI).

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10-minute Full Disk GOES-16 (GOES-East) “Red” Visible (0.64 µm), Shortwave Infrared (3.9 µm) and “Clean” Infrared Window (10.3 µm) images (above) showed that a wildfire complex in southern Brazil produced a series of 4-5 pyrocumulonimbus (pyroCb) clouds on 13 November 2023. The coldest pyroCb cloud-top 10.3 µm brightness temperature was -74.4ºC at 1530 UTC.

Regarding the wildfire complex that produced those pyroCb clouds, the 4 components of the GOES-16 Fire Detection and Characterization Algorithm (FDCA) are shown above — and a larger-scale view of the Fire Mask component is shown below.

A blend of GOES-16 Shortwave Infrared and “Clean” Infrared Window images with an overlay of GLM Group Points — created using RealEarth — revealed that there were periods of significant lightning activity associated with the largest pyroCb cloud as it drifted southward away from the large wildfire complex.

This is likely the fourth confirmed case of a South American pyroCb — in addition, it’s one of the very few pyroCb events documented so far in the tropics.

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CIMSS provides (free of charge) CSPPGeo software that can create (and plot) gridded GLM data from GLM Level 2 LCFA files. The data from those files can then be plotted by geo2grid on top of ABI data to give an idea of how much lightning is occurring each minute. On 6 November, severe hail was reported over lower Michigan as documented in this blog post. What did the gridded GLM fields look like on that day?

To discern this, visible imagery fields at 1436 and 1441 UTC on 6 November (near the times when severe hail was being reported) were first created using geo2grid over a specific domain, using the commands below (the results are shown above). The first command shown just below (p2g_grid_helper.sh) creates a 960×720 grid (‘GRR’) centered at 43.0^oN, 86.0^oW, with 500-m resolution in the E-W and N-S direction, and redirects the created grid parameters to the file ‘GRR2.yaml’. Then geo2grid is invoked to extract C02 (GOES-16 Band 2, visible imagery centered at 0.64 µm) on that grid at 1436 and 1441 UTC on 6 November 2023 (Day 310).

$GEO2GRID_HOME/bin/p2g_grid_helper.sh GRR -86.0 43.0 500.0 -500.0 960 720 > $GEO2GRID_HOME/GRR2.yaml

$GEO2GRID_HOME/bin/geo2grid.sh -r abi_l1b -w geotiff -p C02 -g GRR --grid-configs $GEO2GRID_HOME/GRR2.yaml -f /path_to_G16ABIdata/L1b/RadC/*M6C02*s20233101436*

$GEO2GRID_HOME/bin/geo2grid.sh -r abi_l1b -w geotiff -p C02 -g GRR --grid-configs $GEO2GRID_HOME/GRR2.yaml -f /path_to_G16ABIdata/L1b/RadC/*M6C02*s20233101441*

The commands above create two files: GOES-16_ABI_RadC_C02_20231106_143617_GRR.tif and GOES-16_ABI_RadC_C02_20231106_144117_GRR.tif.

Next, CSPPGeo software gridded GLM software is used to create minute-by-minute files of Gridded GLM, in this case from 1431 to 1440 UTC on 6 November 2023 (Day 310). These data will be overlain on the 14346 and 1441 UTC visible images created above.

sh ./cspp-geo-gglm.sh /path_to_G16GLMdata/glm/L2/LCFA/OR_GLM-L2-LCFA_G16_s20233101431*.nc
sh ./cspp-geo-gglm.sh /path_to_G16GLMdata/glm/L2/LCFA/OR_GLM-L2-LCFA_G16_s20233101432*.nc
sh ./cspp-geo-gglm.sh /path_to_G16GLMdata/glm/L2/LCFA/OR_GLM-L2-LCFA_G16_s20233101433*.nc
....
sh ./cspp-geo-gglm.sh /path_to_G16GLMdata/glm/L2/LCFA/OR_GLM-L2-LCFA_G16_s20233101440*.nc

Then, geo2grid was used to create GLM imagery (in this case Total Optical Energy fields) at the 10 times. Recall that the --list-products-all flag can be added to the geo2grid call to see which products can be produced given the input netCDF fields.

./geo2grid.sh -r glm_l2 -w geotiff -p total_energy -g GRR --grid-configs $GEO2GRID_HOME/GRR2.yaml -f /path_to_griddedGLMFields/CG_GLM-L2-GLMF-M3_G16_s20233101431000*.nc

./geo2grid.sh -r glm_l2 -w geotiff -p total_energy -g GRR --grid-configs $GEO2GRID_HOME/GRR2.yaml -f /path_to_griddedGLMFields/CG_GLM-L2-GLMF-M3_G16_s20233101432000*.nc

./geo2grid.sh -r glm_l2 -w geotiff -p total_energy -g GRR --grid-configs $GEO2GRID_HOME/GRR2.yaml -f /path_to_griddedGLMFields/CG_GLM-L2-GLMF-M3_G16_s20233101433000*.nc

....

./geo2grid.sh -r glm_l2 -w geotiff -p total_energy -g GRR --grid-configs $GEO2GRID_HOME/GRR2.yaml -f /path_to_griddedGLMFields/CG_GLM-L2-GLMF-M3_G16_s20233101440000*.nc

At this point, we have tif files that have the C02 (Band 2) fields, and tif fields that have Total Optical Energy fields at 1-minute intervals. Next, we color-enhance the total optical energy fields using geo2grid’s add_colormap.sh, and then add maps to both the Band 2 images and the Total Optical Energy fields, resulting in png files that have state and lake borders added. Those commands are shown below.

$GEO2GRID_HOME/bin/add_colormap.sh ../../enhancements/glm_energy_colortable.txt *GOES16*energy*.tif

./add_coastlines.sh --add-coastlines --coastlines-resolution f --add-borders --borders-resolution f GOES*16*flash*.tif

./add_coastlines.sh --add-coastlines --coastlines-resolution f --add-borders --borders-resolution f GOES*16*C02*.tif

All that remains is to annotate the Band 2 imagery, and overlay the Total Optical Energy (TOE) fields on top. This is done (not shown) using ImageMagick commands. The two Band 2 images are shown above, and the same two fields with 5 TOE fields overlain on each are shown below.

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