Severe weather outbreak across eastern Texas and the Deep South

April 13th, 2019 |

GOES-16

GOES-16 “Red” Visible (0.64 µm) images, with SPC storm reports plotted in red [click to play MP4 animation]

An outbreak of severe weather began in eastern Texas on the morning of 13 April 2019, where thunderstorms produced hail up to 3.0 inches in diameter, tornadoes and damaging winds (SPC storm reports). 1-minute Mesoscale Domain Sector GOES-16 “Red” Visible (0.64 µm) images (above) showed the clusters of thunderstorms that developed as a surface low and associated frontal boundaries moved eastward (surface analyses). The corresponding GOES-16 “Clean” Infrared Window (10.3 µm) images (below) revealed numerous overshooting tops with infrared brightness temperatures as cold as -70 to -75ºC. In addition, the storm producing 3.0-inch hail and damaging winds at 1428 UTC exhibited an Above-Anvil Cirrus Plume (Visible/Infrared toggle).

GOES-16 "Clean" Infrared Window (10.3 µm) images, with SPC storm reports plotted in purple [click to play MP4 animation]

GOES-16 “Clean” Infrared Window (10.3 µm) images, with SPC storm reports plotted in purple [click to play MP4 animation]

A comparison of Terra MODIS Visible (0.65 µm) and Infrared Window (11.0 µm) images at 1650 UTC is shown below.

Terra MODIS Visible (0.65 µm) and Infrared Window (11.0 µm) images [click to enlarge]

Terra MODIS Visible (0.65 µm) and Infrared Window (11.0 µm) images [click to enlarge]

Later in the day, the thunderstorms continued to produce a variety of severe weather as they moved eastward across Louisiana and Mississippi, as shown by GOES-16 Visible and Infrared images (below).

GOES-16 "Red" Visible (0.64 µm) images, with SPC storm reports plotted in red [click to play MP4 animation]

GOES-16 “Red” Visible (0.64 µm) images, with SPC storm reports plotted in red [click to play MP4 animation]

GOES-16 "Clean" Infrared Window (10.3 µm) images, with SPC storm reports plotted in cyan [click to play MP4 animation]

GOES-16 “Clean” Infrared Window (10.3 µm) images, with SPC storm reports plotted in cyan [click to play MP4 animation]

After sunset, the thunderstorms continued to move eastward, spreading more serve weather across Mississippi into Alabama and far southern Tennessee (below).

GOES-16 "Clean" Infrared Window (10.3 µm) images, with SPC storm reports plotted in cyan [click to play MP4 animation]

GOES-16 “Clean” Infrared Window (10.3 µm) images, with SPC storm reports plotted in cyan [click to play MP4 animation]

VIIRS Day/Night Band (0.7 µm) and Infrared Window (11.45 µm) images from NOAA-20 and Suomi NPP (below) provided additional views of the storms as they were moving across Mississippi and Alabama. Several bright lightning streaks were evident on the Day/Night Band images. Note: the NOAA-20 image (downloaded and processed from the Direct Broadcast ground station at CIMSS) is incorrectly labeled as Suomi NPP.

VIIRS Day/Night Band (0.7 µm) and Infrared Window (11.45 µm) images from Suomi NPP and NOAA-20 [click to enlarge]

VIIRS Day/Night Band (0.7 µm) and Infrared Window (11.45 µm) images from NOAA-20 at 0645 UTC and Suomi NPP at 0734 UTC [click to enlarge]

On a NOAA-20 VIIRS Day/Night Band (0.7 µm) image at 0825 UTC (below), an impressively-long (~400 mile) dark “post-saturation recovery streak” extended southeastward from where the detector sensed an area of very intense/bright lightning activity northeast of Mobile, Alabama.

NOAA-20 VIIRS Day/Night Band (0.7 µm) image at 0825 UTC [click to enlarge]

NOAA-20 VIIRS Day/Night Band (0.7 µm) image at 0825 UTC [click to enlarge]

Use Polar2Grid to create VIIRS True Color imagery over one State (Missouri)

April 11th, 2019 |

VIIRS True-Color Imagery over Missouri, 1942 UTC on 9 April 2019 (Click to enlarge)

Polar2Grid allows users to create true-color imagery from VIIRS (Visible Infrared Imaging Radiometer Suite) data from Suomi-NPP or NOAA-20. This tutorial will take you through the needed steps. Step one is to decide when you want the data; the ways to determine when a Polar Orbiter overflies a particular point are outlined in this blog post, that points to this website. For this blog post I’ve chosen Missouri. The image above shows a True-Color image over Missouri at about 19:42 UTC on 9 April 2019.

To create true-color imagery, Polar2Grid requires VIIRS M-Bands 3, 4 and 5 (Blue (0.48 µm), Green (0.55 µm) and Red (0.67 µm), respectively, all with 750-m resolution); click here for a list of all VIIRS bands). If the VIIRS I-Band 1 (at 0.64 µm) is present in the directory, then that image is used to sharpen the resultant image. Polar2Grid CREFL software also performs a simple atmospheric Rayleigh scattering removal; smoke and haze will still be apparent in the imagery, however.

To create the imagery above, first order the data from NOAA Class. (Steps to follow are shown here). Download the data into a unique directory. We are going to remap these data onto a map centered on Missouri, and for that to happen, Polar2Grid needs mapping parameters. These can be generated automatically with the p2_grid_helper.sh script that comes with Polar2Grid software. From the bin directory, I entered this command to put the grid parameters in a file .

/p2g_grid_helper.sh missouri -93.0 38.0 500 -500 2000 2000 > my_grids.txt

The line of data entered into that file is this:

missouri, proj4, +proj=lcc +datum=WGS84 +ellps=WGS84 +lat_0=38.000 +lat_1=38.000 +lon_0=-93.000 +units=m +no_defs, 2000, 2000, 500.000, -500.000, -99.055deg, 42.352deg

Now I’m ready to generate a true-color image (corrected ceflectance — crefl — imagery) with Polar2Grid, using this command:

./polar2grid.sh crefl gtiff –grid-configs /home/scottl/Polar2Grid/polar2grid_v_2_2_1/bin/my_grids.txt -g missouri -f /data-hdd/storage/Polar2GridData/09April/

The flags “–grid-configs <path to directory where file created by p2g_grid_help sits” and “-g map <name of map inside that file>” instruct to the Polar2Grid software to pull the mapping data for the defined grid out of the file. Otherwise, the data are in satellite projection. This polar2grid.sh invokation created a file named ‘j01_viirs_true_color_20190409_194226_missouri.tif’; I want to put a map on it so it is easier to georeference, and that is done using this shell in the Polar2Grid bin directory:

./add_coastlines.sh –add-borders –borders-resolution=f –borders-level=2 –borders-outline=’black’ j01_viirs_true_color_20190409_194226_missouri.tif

This adds a map to the image, then converts it to the png file (j01_viirs_true_color_20190409_194226_missouri.png) that is shown above.

After doing the same steps for a series of clear days in the midwest (09 March 2019, 15 March 2019, 21 March 2019, 26 March 2019, 31 March 2019), and annotating and concatenating the images in an animation, the greening up of Spring is apparent. See below.

NOAA-20 VIIRS True Color Imagery on select mostly clear days over the mid-Mississippi Valley, dates and times as indicated in the image (Click to enlarge)

Special shout-out to Dave Hoese, SSEC/CIMSS, for crafting software that is so easy to use to produce excellent satellite imagery.

Large-scale blowing dust event

April 10th, 2019 |

GOES-16 Split Window (10.3-12.3 µm) images [click to play animation | MP4]

GOES-16 Split Window (10.3-12.3 µm) images [click to play animation | MP4]

Strong winds — gusting as high as 77 mph in New Mexico and 88 mph in Texas — associated with a rapidly-intensifying midlatitude cyclone generated large plumes of blowing dust (originating from southeastern Arizona,southern New Mexico, northern Mexico and western Texas) on 10 April 2019. GOES-16 (GOES-East) Split Window (10.3-12.3 µm) images (above) helped to highlight the areas of blowing dust, which initially developed along and behind a cold front after 15 UTC.

GOES-16 Split Window (10.3-12.3 µm) images, with hourly plots of surface winds and gusts [click to play animation | MP4]

GOES-16 Split Window (10.3-12.3 µm) images, with hourly plots of surface wind barbs and gusts [click to play animation | MP4]

GOES-16 Split Window images with hourly plots of surface wind barbs and gusts (above) showed the distribution of strong winds across the region, while plots of the surface visibility (below) showed decreases to 1/4 mile at Deming, New Mexico, 1/2 mile at Lubbock, Texas and 4 miles at Altus, Oklahoma.

GOES-16 Split Window (10.3-12.3 µm) images, with hourly plots of surface visibility [click to play animation | MP4]

GOES-16 Split Window (10.3-12.3 µm) images, with hourly plots of surface visibility [click to play animation | MP4]

GOES-16 True Color Red-Green-Blue (RGB) images (below; courtesy of Rick Kohrs, SSEC) depicted the blowing dust as shades of tan to light brown. Willcox Playa was the source of the dust plume coming from southeastern Arizona. Note that the dust plume emanating from White Sands, New Mexico was lighter in appearance compared to the other tan/brown-colored areas of blowing dust — this is due to the white gypsum sand that comprises the surface of White Sands National Monument.

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

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

250-meter resolution MODIS True Color RGB images from the MODIS Today site (below) provided a more detailed view of the plume streaming northeastward from its White Sands source. On the later Aqua image, dense tan-colored areas of blowing dust had developed below the thin higher-altitude veil of brighter gypsum aerosols that had earlier been lofted from White Sands.

MODIS True Color RGB images from Terra and Aqua [click to enlarge]

MODIS True Color RGB images from Terra and Aqua [click to enlarge]

A NOAA-20 True Color RGB image viewed using RealEarth is shown below. 19 UTC surface observations at 3 sites near White Sands included Las Cruces KLRU (visibility 3 miles, wind gusting to 46 knots), Alamogordo KALM (visibility 3 miles, wind gusting to 43 knots) and Ruidoso KSRR (visibility 5 miles, wind gusting to 55 knots). The strong winds and dense areas of blowing dust reducing surface visibility not only impacted ground transportation but also posed a hazard to aviation.

NOAA-20 True Color RGB image at 1928 UTC [click to enlarge]

NOAA-20 True Color RGB image at 1928 UTC [click to enlarge]

===== 11 April Update =====

In a larger-scale view of GOES-16 Split Window images (below), the yellow dust signature could be followed during the subsequent overnight hours and into the following day on 11 April, as the aerosols were being transported northeastward across the Upper Midwest. There were widespread reports and photos of dust residue on vehicles and tan/brown-colored snow in parts of Nebraska, Iowa, Minnesota and Wisconsin.

GOES-16 Split Window (10.3-12.3 µm) images [click to play animation | MP4]

GOES-16 Split Window (10.3-12.3 µm) images [click to play animation | MP4]

IDEA forward trajectories (below) — initialized from a cluster of elevated Aura OMI Aerosol Index points over Mexico, New Mexico and Texas — passed directly over areas of model-derived precipitation across the Upper Midwest, providing further support of precipitation scavenging of dust aerosols. Interestingly, a similar event of long range dust transport occurred on 10-11 April 2008.

IDEA forward trajectories initialized from a cluster of elevated Aqua MODIS Aerosol Optical Depth points over NM/TX [click to play animation]

IDEA forward trajectories initialized from a cluster of elevated Aqua MODIS Aerosol Optical Depth points over NM/TX [click to play animation]

HYSPLIT model 24-hour forward trajectories initialized at 3 locations — El Paso, Lubbock and Amarillo in Texas — showed a few of the likely dust transport pathways toward the Upper Midwest at 3 different levels (below).

HYSPLIT model forward trajectories initialized at El Paso, Lubbock and Amarillo, Texas [click to enlarge]

HYSPLIT model 24-hour forward trajectories initialized at El Paso, Lubbock and Amarillo, Texas [click to enlarge]

GOES-16 True Color RGB images from the AOS site (below) showed that some clouds across the Upper Midwest exhibited a subtle light brown hue at times.

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

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

===== 12 April Update =====

GOES-16 Split Window (10.3-12.3 µm) images [click to play animation | MP4]

GOES-16 Split Window (10.3-12.3 µm) images [click to play animation | MP4]

GOES-16 Split Window (10.3-12.3 µm) images (above) showed that the yellow signature of dust aerosols aloft had wrapped all the way around the southern and eastern sectors of the occluded low on 12 April.

Ground-based lidar at the University of Wisconsin – Madison confirmed the presence of elevated levels of aerosol loading between the surface and 6 km.

Lidar aerosol class [click to enlarge]

Lidar aerosol class [click to enlarge]

Using Polar2Grid software to create JPSS Imagery

April 9th, 2019 |

NOAA-20 VIIRS Imagery (Image bands I01 (0.64 µm), I03 (1.61 µm) and I05 (11.45 µm)) at 23:25 UTC on 8 April 2019 (Click to enlarge)

Polar2Grid is Python-based software created at CIMSS/SSEC to process data from Polar Orbiting satellites into useful imagery (or into files that can be imported directly into the National Weather Service Advanced Weather Information Processing System (AWIPS) for display). (You can download it for a linux machine at this site.) This tutorial will describe where to find downloadable NOAA-20 (or Suomi-NPP) data, and how to create imagery. Thus, this blog post is similar to earlier blogs posts (here, and here) that described how to use Geo2Grid for Geostationary Satellites. Earlier blog posts showing Polar2Grid output are here and here.

There are data repositories associated with many direct broadcast antennas — but they are not always publically available. NOAA CLASS data is a reliable source for NOAA-20 and Suomi-NPP data. Typically data shows up there within six hours of its being sampled by the satellite. For a post-event analysis, this is a good data source. For near-real time investigation, it’s better to acquire data from a direct broadcast site. (Data from the Direct Broadcast antenna at CIMSS are available here.)

The first thing required at the NOAA CLASS site is to request the data that you want to access. There is a long drop-down menu (‘Please select a product to search’ is its original title) on the CLASS front page; use the drop down to select ‘JPSS Visible Infrared Imaging Radiometer Suite Sensor Data Record (VIIRS_SDR)’. This tells CLASS that you want VIIRS data from either Suomi NPP or NOAA-20. Click on the ‘Go’ button to the right of the menu bar. That takes you to a selection page.

It is necessary to log into the CLASS system. When you order data, an email is sent acknowledging the order, and a follow-on email once the data are available specifies how you can download it. The log-in tells CLASS where to send the emails.

Polar2Grid expects the data to be ‘de-aggregated’, so you must set User Preferences in NOAA CLASS to do this. Click on the ‘User Preferences’ link in the table on the left-hand side of the main NOAA CLASS Page (after you have logged in). The location is shown below in the toggle.

NOAA Class Front Page after logging in as a user. Note the ‘User Preferences’ Tab, circled in red.

Once you have entered the User Preference page, make certain that the ‘Package Geolocation with JPSS Data Products’ button is toggled to ‘No’. (Shown here) You also do want to De-aggregate JPSS Data Products. (That is, separate files for each band). In practice, this blogger finds it easier (that is, Polar2Grid complains less) if I make separate data requests at CLASS for each VIIRS band I want to view. (Update: ‘JPSS Companion Files to deliver with data’ should also be blank, as as shown at the link. This allows for one data request.)

Data requests require you to know something about the orbits of the satellites — so you can narrow down the amount of data you want. This handy website shows where all polar orbiters have been flying. Follow the links to the specific satellite and location; for example, if we’re interested in NOAA-20 orbits over Hawai’i on April 8 2019, this map shows them. The map suggests requesting NOAA-20 from 23:20 to 23:30 on 8 April 2019 will give a good view of the islands.

The data we will request are I01, I03 and I05 (0.64 µm, 1.61 µm and 11.45 µm, respectively). In addition to requesting the Sensor Data Records, it is also necessary to request, near the bottom of the page, the ‘VIIRS Image Bands SDR Ellipsoid Terrain Corrected Geolocation (GITCO) (public)’. These geolocation files are used by Polar2Grid to navigate the imagery.

After submitting the data request, and waiting a period of time (sometimes as short as two or three minutes), you will receive an email telling you exactly where the data sits, and how to access it. It will look something like this. Download the data into a directory, and you’re ready to have Polar2Grid create imagery for you. The directory for I05 (I will put data for each band in a separate directory) should include files named like this:

GIMGO_j01_d20190408_t2320306_e2321551_b07188_c20190409223158545413_noac_ops.h5
GITCO_j01_d20190408_t2320306_e2321551_b07188_c20190409223155222712_noac_ops.h5
SVI03_j01_d20190408_t2320306_e2321551_b07188_c20190409223158545413_noac_ops.h5

‘GIMGO’ and ‘GITCO’ refer to geolocation data; even though you only requested GITCO fields, CLASS will give both. That’s okay. SVI01, SVI03 and SVI05 hold data from bands I01, I03 and I05, respectively. The ‘j01’ tag signifies data from NOAA-20, or JPSS-1. For the 20-minute request I made for each band, I received 8 of each type of file.

The Polar2Grid command that creates imagery is this one:

polar2grid.sh viirs_sdr gtiff -p i03 -f /home/scottl/Polar2Grid/data/viirs/I03/

The polar2grid.sh shell script is within the bin directory of the Polar2Grid software that emerges after you g-unzip and untar the file from the Polar2Grid download site. The command results in a .tif file with highest-resolution grey-scaled imagery. The image below (converted from .tif to .png) shows the scene. It’s quite large: 6876×7616 pixels!

NOAA-20 Imagery (I-3, 1.61 µm) from 23:20 to 23:30 on 8 April 2019 (Click to enlarge)

It’s useful to add maps to the imagery, and that is done in Polar2Grid after the .tif file has been created by using ‘add_coastlines.sh’, also in the bin directory. The command can add coastlines (–add-coastlines), borders (–add-borders), rivers (–add-rivers) and lat/lon lines (–add-grid). Lat/Lon lines can also be labeled. When maps are added to the .tif file, the image is also saved as a .png file so the original scene is not overwritten. You can use the -o flag to rename the new file. The command I used is shown below.

add_coastlines.sh –add-coastlines j01_viirs_i03_20190408_231906_wgs84_fit.tif –coastlines-resolution=f –coastlines-level=6 –coastlines-outline=’magenta’ -o j01_I03_20190408_231906.png

After adding maps to all three files created, I used ImageMagick to crop the large fields to something more manageable in size (convert -crop 1520×900+2112+2409 +repage -quality 100 j01_I05_20190408_231906.png j01_I05_20190408_231906.gif, for example), and added annotation to the imagery:

convert -font helvetica -fill yellow -pointsize 36 -draw “text 70,70 ‘NOAA-20 VIIRS Image Band I01 (0.64 µm) 23:25 UTC 8 April 2019′” j01_I01_20190408_231906.gif j01_I01_20190408_231906.annot.gif

The animation at the top of this blog post shows all three images (I01, I03 and I05) sequentially.

Final note: Infrared imagery by default is not color-enhanced, and built-in enhancements are not (yet) available. Polar2Grid does support creation of colortables, however. That will be the subject of a future blog post.