Geostationary Lightning Mapper (GLM) data displayed with Geo2Grid

January 30th, 2021 |

GOES-16 ABI CONUS sector band 13 (Clean Window, 10.3 µm) infrared imagery, 1901-2001 UTC on 30 January 2021

Geo2Grid is a scripting tool that accesses various Python packages to display Geostationary Satellite data, described on this blog before here, here and here (Polar2Grid is a similar package for Low Earth Orbit satellite data).  The animation above shows GOES-16 Band-13 (Clean Window, 10.3 µm) infrared data for an hour over Oklahoma/Kansas/Missouri/Arkansas during a time when tornadoes occurred (imagery was produced using Geo2Grid and GOES-16 level-1b radiance files).  (SPC Storm Reports).

Gridded GLM data are available at this website;  both CONUS and Full Disk domains are available, CONUS data are a simple subset of the Full Disk imagery.  These netCDF files (with ‘GLMC’ in the filename) are available each minute, and contain a variety of gridded GLM products, some of which as distributed to National Weather Service forecast offices. By using the ‘glm_l2’ reader in Geo2Grid, data can be plotted, and subsequently overlain on top of the ABI imagery, as shown below.

GOES-16 ABI CONUS sector band 13 (Clean Window, 10.3 µm) infrared imagery, 1901-2001 UTC on 30 January 2021, overlain with GLM Total Optical Energy at 1-minute time steps (Click to animate)

NOAA/CIMSS ProbSevere with a tornado in Tallahassee, FL

January 27th, 2021 |

NOAA/CIMSS ProbSevere display, 1545 – 1700 UTC on 27 January 2021 (Click to animate)

A tornado struck the Tallahassee, FL, airport at 1643 UTC on 27 January 2021 (SPC Storm Report).  The animation above shows ProbSevere (version 2) fields (from this site) in the hour leading up to tornadogenesis.  The animation demonstrates how ProbTor values can be used to identify for closer scrutiny a particular radar object:  the radar object that ultimately caused a tornado showed greater ProbTor values (than surrounding identified radar objects) in the hour leading up to tornadogenesis. In addition, ProbTor values ramped up quickly just prior to tornadogenesis as low-level azimuthal shear jumped.

One time series below compares ProbWind, ProbHail and ProbTor for the radar object (#15080) that produced the tornado; for this event, ProbWind and ProbTor values were comparable until a ramp-up in ProbTor values before the tornado occurred. The second time series shows the various components of ProbTor for radar object 15080 (both time series courtesy John Cintineo, SSEC/CIMSS).  Note in particular that this storm was not a lightning-producer.  Much of ProbTor’s variability was determined by changes in low-level azimuthal shear.

NOAA/CIMSS ProbSevere values (ProbWind, ProbHail, ProbTor) for radar object #15080, 1530 – 1658 UTC on 27 January 2021 (Click to enlarge)

NOAA/CIMSS ProbTor and component values for Radar object #15080, 1530 – 1658 UTC on 27 January 2021, associated with the Tallahassee FL tornado (Click to enlarge)

Lead time with ProbTor in this example was not exceptional.  However, its elevated values in the hour leading up to the tornado could have provided better situational awareness, and perhaps enhanced confidence in warning issuance for this well-warned event.



GOES-16 “Red” Visible (0.64 µm, left) and “Clean” Infrared Window (10.35 µm, right) images, with plots of SPC Storm Reports [click to play animation | MP4]

Unfortunately, the default Mesoscale Domain Sectors were positioned too far north to cover the Florida Panhandle — but 5-minute CONUS Sector GOES-16 (GOES-East) “Red” Visible (0.64 µm) and “Clean” Infrared Window (10.35 µm) images (above) depicted a west-to-east oriented line of thunderstorms across the northern portion of the Panhandle; a trend of cooling cloud-top infrared brightness temperatures was seen as the convection began to produce the tornado.

There was an overpass of the Terra satellite about 19 minutes before the start of the tornado event, at 1618 UTC — 1-km resolution MODIS Visible (0.64 µm) and Infrared Window (11.0 µm) images are shown below.

Terra MODIS Visible (0.64 µm) and Infrared Window (11.0 µm) images [click to enlarge]

Terra MODIS Visible (0.64 µm) and Infrared Window (11.0 µm) images [click to enlarge]

NUCAPS fields across an upper tropospheric front

January 20th, 2021 |

GOES-16 ABI Airmass RGB, Band 10 and Band 8 (7.34 µm and 6.19 µm, respectively), and GOES-16 Airmass RGB overlain with NUCAPS sounding availability plots, 0801 UTC oni 20 January 2021 (click to enlarge)

The AirMass RGB from GOES-16 at 0800 UTC on 20 January 2021 showed a distinct color change across central Missouri, from red to green.  The enhanced red coloring suggests a large difference in water vapor brightness temperatures.  The toggle above (including an image with NUCAPS* sounding points), shows structures in the water vapor imagery consistent with an upper tropospheric front.

Water Vapor and Airmass RGB imagery fields are useful because they be compared to model fields of the tropopause, and similarities in model fields and satellite imagery lend credence to the idea that the model initialization is accurate.  Compare the Airmass RGB and the Rapid Refresh mapping of the pressure on the 1.5 PVU surface below.  There is good spatial correlation between model and satellite fields.

GOES-16 Airmass RGB and Rapid Refresh model field of Pressure on the 1.5 PVU surface, 0800 UTC 20 January 2021 (Click to enlarge)

How do vertical profiles from NUCAPS vary across the tropopause fold?  The animation below shows six different profile in Missouri and Arkansas, spanning the reddish region of the airmass RGB.

GOES-16 Airmass RGB image with selected NUCAPS profiles, as indicated. (Click to enlarge)

A more efficient way to view information from NUCAPS is to view gridded fields.  Polar2Grid is used to transform the vertical profile to horizontal fields at the individual NUCAPS pressure levels (and then vertical interpolation moves those fields to standard levels).  The animations below show gridded values that are all in agreement with the presence of a tropopause fold where the Airmass RGB and model fields suggest.  Gridded temperature and moisture can be combined in many ways.  Gridded Ozone is also available in AWIPS (some of these fields were created using the Product Browser).

Ozone from NUCAPS, below, does show an enhancement, as expected, in the region where the tropopause fold is suggested by the airmass RGB.

NUCAPS-derived ozone anomalies, ca. 0800 UTC on 20 January 2021 (Click to enlarge)

The gridded NUCAPS tropopause level, shown below, can also be inferred from the individual profiles shown above.

Gridded NUCAPS Tropopause level, ca. 0800 UTC on 20 January 2021 (click to enlarge)

Note how the lapse rates show relatively less stable air (in the mid-troposphere) in the region of the tropopause fold.

Gridded 500-700 mb Lapse rates, ca. 0800 UTC on 20 January 2021 (click to enlarge)

Mixing ratio shows dry mid- and upper-tropospheric air, in the region of the tropopause fold, as might be expected from the GOES-16 water vapor imagery.

Gridded NUCAPS esimates of 300-700 mb mixing ratio, ca. 0800 UTC on 20 January 2021 (Click to enlarge)

In general, NUCAPS data can be used to augment other satellite and model data to better understand the thermodynamic structure of the atmosphere.  For more information on NUCAPS profiles, refer to this training video.

*The careful reader will note that the timestamp of the NUCAPS Sounding Availability plot, 0753 UTC, is different from the GOES-16 imagery.  Why?  The NUCAPS Sounding Availability plot is timestamped (approximately) when NOAA-20 initially overflies North American airspace.  NOAA-20 was flying over Missouri shortly after 0800 UTC, as shown in this plot (from this website).  Gridded NUCAPS fields are timestamped when NOAA-20 is overhead.

Derived Motion Winds in a Dust Storm

January 15th, 2021 |

GOES-16 Visible (0.64 µm) imagery and Mesoscale Sector 2 Derived Motion Winds, 1430 -1930 UTC. Winds are available every 5 minutes, imagery is also shown every 5 minutes, rather than the default 1 minute for Mesoscale Sectors (Click to animate)

The High Plains of Kansas, Colorado, Oklahoma and Texas experienced a significant dust storm (with Dust Storm Warnings issued) on 15 January 2021, (Click here for a blog post on the blowing dust with this storm on 14 January) associated with a strong jet streak and extratropical cyclone discussed here. The animation above (Here’s the same animation, but slower) shows visible imagery along with GOES-16 Mesoscale Sector Derived Motion Winds from the Visible Channel. These derived winds are available with a 5-minute cadence, and the dust was thick enough that features could be tracked. There aren’t a lot of derived winds; how well do these derived winds compare to surface winds?

METAR Observations, GOES-16 Visible (0.64 µm) imagery, and Derived Motion Winds from Visible data, 1900 UTC on 15 January 2021 (Click to enlarge)

The image above, from 1900 UTC, shows Derived Motion winds along with METAR observations. Derived Motion winds are stronger than surface winds, as expected; compare, for example, the observations at Limon CO (KLIC) with the nearby derived wind vectors. The levels of the derived motion winds are between 800-820 hPa, away from the effects of friction/surface roughness. However, they do give a nice estimate of what surface winds might be in regions without surface observations, as apparent in the animation at the top.

It can be difficult to view dust with just one ABI channel such as the visible, especially when the sun is high(ish) in the sky and there is little forward scattering. Multi-spectral RGB products, such as the GOES-16 Dust RGB, shown below in a toggle with a VIIRS True-Color image and the GOES-16 Fire RGB (there is a fire evident near KLHX, LaJunta, CO), are a valuable tool in identifying the horizontal extent of dust plumes.  Dust is highlighted in the Dust RGB by a vivid pink/magenta color.

NOAA-20 VIIRS True-Color image, GOES-16 Dust RGB and GOES-16 Fire Temperature RGB at 1956 UTC, 15 January 2021 (Click to enlarge)