Using McIDAS-V to display GOES-16 FDCA fields

March 22nd, 2022 |

The image below shows GOES-16 Fire Power, a Fire Detection/Characterization Algorithm (FDCA) output field (along with Fire Temperature and Fire Area), on a day when strong southerly winds helped support multiple fires over Texas (as shown in this animation, from this blog post). If you do not have access to AWIPS, as below (or in the linked-to animation), are there other ways to access and display FDCA output? This blog post shows how to do that with McIDAS-V.

GOES-16 Fire Power, 2101 UTC on 20 March 2022 (click to enlarge)

Where can you get the FDCA data to display? The NOAA CLASS data respository is one place. The toggle below outlines the products to choose in the drop-down menu (“GOES-R Series ABI Products (GRABIPRD) partially restricted L1b and L2+ Data Products”) near the top of the CLASS home page (then click on the >>GO), and then shows how to select the data wanted. In the example below, I’ve chosen the ABI L2+ GOES-16 CONUS files of Fire/Hot Spot Characterization on 20 March 2022 between 21:00 and 21:04. After making those selections, click on ‘Search’ and then order. When the files are queued up for retrieval, you’ll receive an email with instructions.

NOAA CLASS website, and GOES-R L2 Products data selection (Click to enlarge)

You can also access GOES-R data through this website below hosted at the University of Utah. (Kudos to Brian Blaylock, its developer!) Note in the animation below how you choose the satellite, the product and the time, and then receive a list of downloadable files.

Amazon Web Services portal showing data selection and files retrieved (Click to enlarge)

You can start up McIDAS-V to view the data once you have downloaded to your machine the data file:

OR_ABI-L2-FDCC-M6_G16_s20220792101168_e20220792103541_c20220792104155.nc

FDCC in the filename signifies Fire Detection Characterization in the CONUS domain, created with Mode 6 scanning (M6) and GOES-16 data (G16). The data starts at 21:01:16.8 on 20 March (Julian Day 79) in 2022, i.e., 20220792101168 and ends at 21:03:54.1 on the same day. It was created at 21:04:15.5. Once you start McIDAS-V, you must input the data, via the Data Sources tab within the Data Explorer. The satellite data we’re using are gridded data, and they’re local. Select the file needed for display and click ‘Add Source’. When you do that, you’ll see a different window (‘Field Selector’) brought to the front.

McIDAS-V Data Explorer (Click to enlarge)
Steps under ‘Field Selector’ in the Data Explorer to find the data to display (Click to enlarge)

Note in this example that 5 different fields are present in the file: Fire + Hot Spot Characterization Fire Area, Fire Temperatures, Fire Mask, Fire Radiative Power and Data Quality Flags. In this example, I’ve selected ‘Data Quality Flags’ — to be presented as ‘Value Plots’; those are shown below in a region zoomed in over Texas and annotated.

FDCA Data Quality Flags, 2101 UTC, 20 March 2022 (Click to enlarge)

Rather than Data Quality Flags, one can show ‘Fire Mask’ — these data values are available in AWIPS files, but aren’t generally shown. So, I recreated the ‘Value Plots’ but selected ‘Fire Mask’ rather than ‘data quality Flags’; Next, I created a ‘Color-Shaded Plan View’ (the Data Explorer for that is shown here, created with ‘Match Display Region’ chosen). The animation below steps through the plotted values, the color-shaded plan view with default enhancement, and the color-shaded plan view with a McIDAS Enhancement Table appropriate to the Fire Mask (clouds, for example, are grey, and fires stand out against the background). (This pdf describes what the file mask values mean).

Plotted FDCA Fire Mask values, and color-enhanced gridded values, 2101 UTC on 20 March 2022 (click to enlarge)

This toggle compares Fire Mask, and Fire Power. A zoom in on Fire Power to north Texas, below, shows the same data as the AWIPS screen grab at the top of this blog post. They are nearly identical.

GOES-16 FDCA Fire Power, 2101 UTC on 20 March 2022 (click to enlarge)

Use McIDAS-V to display Level 2 products if it is difficult to find them online.

Creating a VIIRS brightness temperature difference field from direct broadcast data using McIDAS-V

March 4th, 2022 |

This blog post contains Suomi-NPP VIIRS imagery that was derived (using CSPP) from data downloaded at the Direct Broadcast site at CIMSS. That blog post suggests the need of a brightness temperature difference field from the I04 and I05 data that can be found in this (https://ftp.ssec.wisc.edu/pub/eosdb/npp/viirs/2022_03_03_062_0632/sdr) direct broadcast directory (direct link, available for about 6 days). The Sensor Data Record directory includes I04 and I05 hdf5 granules that McIDAS-V can read: SVI04_npp_d20220303_t0641201_e0642443_b53613_c20220303071038095682_cspp_dev.h5 and SVI05_npp_d20220303_t0641201_e0642443_b53613_c20220303071039605225_cspp_dev.h5 ; determining exactly which granule you want — there are 10 different granules in this particular directory — is partly trial and error and partly viewing the orbit path (here) and choosing wisely. Save those files into a directory; also save the ‘GITCO’ files (that is: GITCO_npp_d20220303_t0641201_e0642443_b53613_c20220303070838040363_cspp_dev.h5) that contain georeferencing for the Imager (‘I’) bands (similarly, GMTCO files contain georeferencing for the Moderate-resolution ‘M’ bands).

McIDAS-V Data Source load window

After starting up McIDAS-V, you want to load the data. Note above that I’ve clicked on JPSS Imagery, and navigated to the directory containing the downloaded data (that directory also includes the GITCO files for those granules, but you don’t see them here). I’ve chosen both I04 and I05 data files from one granule, observed from 06:41:20.1 to 06:42:44.3. Click on ‘Add Source’ in the lower right corner of the window. If you then expand ‘IMAGE’ under ‘Fields’, you’ll see both I04 and I05 Brightness Temperatures.

McIDAS-V Field Selector window

Next, under the ‘Data Sources:’ tab, click on ‘Formulas’. You will see a ‘Miscellaneous’ tab, and under that tab, a ‘Simple Difference a-b’ choice. Choose that and click ‘Create Display’ — this will pop up a window in which you can choose the a (in this case, I05 Brightness Temperature) and b (for this case, I04 Brightness Temperature). Subsect the portion of the granule that you want to display using shift-left click and drag — and — after clicking ‘create image’ — you end up with the image below (zoomed in).

Created I05 – I04 field over portions of central Florida (Click to enlarge)

There is some fine-tuning yet to do. Under the ‘Legend’ in the image above, right-click on ‘VIIRS 2022-03-03…’ to bring up the Control Window shown below. Slide the ‘Texture Quality’ from ‘Medium’ to ‘High’ (if you have a large image — much larger than this one! — that will test your machine’s RAM!)

Layer Controls Window in McIDAS-V

Similarly, if you right-click (again!) under ‘Legend’ and ‘VIIRS 2022-03-03…’ to ‘Edit->Properties’, you can change the Layer Label to include more information, which I did, as shown in the image below. Finally, I edited the color table to highlight positive values (that is, where I05 – I04 Brightness Temperature Difference is between 0 and 2o C) that might show where stratiform clouds are present. That result is shown below. Yellow in the enhancement shows no difference between the fields, blue is a brightness temperature difference of 2o C. Are you obtaining a good signal of fog in the region of the very dense fog over southern Volusia County? I’d only ask what a ‘good signal’ is!

McIDAS-V display, I05-I04, 0641 UTC on 3 March 2022 (click to enlarge)

Imagery in this post was created using v1.8 of McIDAS-V (downloadable here). You can find further documentation on this here.

Blowing dust across the Canary Islands and Atlantic Ocean

February 23rd, 2020 |

GOES-16

GOES-16 “Red” Visible (0.64 µm) images, with plots of hourly surface reports [click to play animation | MP4]

GOES-16 (GOES-East) “Red” Visible (0.64 µm) images (above) showed the onset of a 2-day event of dense plumes of blowing sand/dust (known locally as a Calima) — with Western Sahara and Morocco being the primary source regions — which moved across the Canary Islands and the adjacent East Atlantic Ocean on 22 February 2020. Along the coast of Morocco, surface visibility was reduced to 1/8 mile at Tan-Tan (GMAT); over the Canary Islands, visibility dropped to 1/4 mile at Gran Canaria (GCLP).

GOES-16 Dust Red-Green-Blue (RGB) images spanning the period 0800 UTC on 22 February to 2100 UTC on 23 February (below) provided a continuous day/night visualization of the first dust plume (shades of pink/magenta). During the day on 23 February, a second dust plume could be seen emerging from below a patch of mid/high-altitude clouds. The RGB images were created using Geo2Grid.

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

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

VIIRS True Color RGB images from Suomi NPP and NOAA-20 as viewed using RealEarth (below) revealed orographic waves in the airborne sand/dust downwind (northwest) of some of the Canary Islands on 23 February.

VIIRS True Color RGB images from Suomi NPP and NOAA-20 [click to enlarge]

VIIRS True Color RGB images from Suomi NPP and NOAA-20 [click to enlarge]

This sand/dust was being lofted by anomalously strong lower-tropospheric winds — which were up to 5 standard deviations above the mean at the 925 hPa pressure level (below).

925 hPa wind speed anomaly during the period 00 UTC on 22 February to 00 UTC on 24 February [click to enlarge]

925 hPa wind speed anomaly during the period 00 UTC on 22 February to 00 UTC on 24 February [click to enlarge]

===== 24 February Update =====

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

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

GOES-16 Dust RGB images on 24 February (above) showed the second major pulse of sand/dust curling around the northern periphery of the offshore cutoff low pressure system. Toward the end of the animation, another minor pulse could be seen streaming northwestward off the coast of Western Sahara. A longer Dust RGB animation from 08 UTC on 22 February to 18 UTC on 24 February is available here.

In addition to the Dust RGB, signatures of the airborne sand/dust were also evident in GOES-16 Split Window Difference (10.3-12.3 µm) and Split Cloud Top Phase (11.2-8.4 µm) imagery (below). This arises from the fact that silicates (sand/dust particles) have different energy absorption characteristics at varying wavelengths.

GOES-16 Dust RGB, Split Window Difference (10.3-12.3 µm) and Split Cloud Top Phase (11.2-8.4 µm) [click to play animation | MP4]

GOES-16 Dust RGB, Split Window Difference (10.3-12.3 µm) and Split Cloud Top Phase (11.2-8.4 µm) images [click to play animation | MP4]

A comparison of TROPOMI Aerosol Index, TROPOMI Aerosol layer height (meters), Meteosat-11 Natural Color RGB and Meteosat-11 Dust RGB images at 1515 UTC is shown below (credit: Bob Carp, SSEC). Note that the height of the center of the aerosol layer near the western tip of the plume was generally in the 500-1000 meter range (shades of blue to cyan).

Panel 1: TROPOMI Aerosol Index Panel 2: TROPOMI Aerosol layer height (meters) Panel 3: Meteosat-11 Natural Color RGB Panel 4: Meteosat-11 Dust RGB [click to enlarge]

TROPOMI Aerosol Index (top left), TROPOMI Aerosol layer height in meters (top right), Meteosat-11 Natural Color RGB (bottom left) and Meteosat-11 Dust RGB (bottom right) [click to enlarge]

GOES-16 Split Window Difference image, with plots of available NUCAPS profile points [click to enlarge]

GOES-16 Split Window Difference (10.3-12.3 µm) image, with plots of available NUCAPS profile points [click to enlarge]

A GOES-16 Split Window Difference (10.3-12.3 µm) image with plots of available NUCAPS profile points at 1600 UTC (above) denoted the locations of a sequence of 9 consecutive north-to-south sounding points through the western tip of the dust plume. Profiles of NUCAPS temperature and dew point data for those 9 points are shown below — the strong temperature inversion and dry air below 1 km at Points 6, 7 and 8 showed the presence of this dry, dust-laden air (and the Total Precipitable Water value dropped to a minimum value of 0.34 inch at Point 7).

Profiles of NUCAPS temperature and dew point data for Points 1-9 [click to enlarge]

Profiles of NUCAPS temperature and dew point data for Points 1-9 [click to enlarge]

Eruption of the Whakaari volcano on White Island, New Zealand

December 9th, 2019 |

“Red” Visible (0.64 µm) images from Himawari-8 (left) and GOES-17 (right) [click to play animation | MP4]

A brief eruption of the Whakaari volcano on White Island, New Zealand occurred around 0110 UTC on 09 December 2019 — “Red” Visible (0.64 µm) images from JMA Himawari-8 and GOES-17 (GOES-West) showed the small volcanic cloud as it fanned out east of the island (above).

A signature of the volcanic cloud was also seen in VIIRS True Color Red-Green-Blue (RGB) and Infrared Window (11.45 µm) images from NOAA-20 and Suomi NPP, as viewed using RealEarth (below). The cloud exhibited a rather warm infrared brightness temperature, since the Wellington VAAC only estimated the maximum height to be

VIIRS True Color RGB and Infrared Window (11.45 µm) images from NOAA-20 and Suomi NPP [click to enlarge]

VIIRS True Color RGB and Infrared Window (11.45 µm) images from NOAA-20 and Suomi NPP [click to enlarge]

The volcanic plume contained elevated levels of SO2 which drifted south-southeastward, as seen in a McIDAS-V image of Sentinel-5 TROPOMI Vertical Column SO2 at 0206 UTC (below).

Sentinel-5 TROPOMI Vertical Column SO2 (credit: Bob Carp, SSEC) [click to enlarge]

Sentinel-5 TROPOMI Vertical Column SO2 (credit: Bob Carp, SSEC) [click to enlarge]