Minor explosive eruption of Kilauea in Hawai’i

May 19th, 2018 |

Himawari-8 Ash Cloud Height product {click to play animation]

Himawari-8 Ash Cloud Height product [click to play animation]

An explosive eruption from the Halema’uma’u crater at the Kilauea summit on the Big Island of Hawai’i occurred around 1550 UTC on 19 May 2018. Using Himawari-8 data, multispectral retrievals of parameters such as Ash Cloud Height (above) and Ash Loading (below) from the NOAA/CIMSS Volcanic Cloud Monitoring site helped to characterize the volcanic ash plume.

Himawari-8 Ash Loading product [click to play animation]

Himawari-8 Ash Loading product [click to play animation]

Later in the day, a Suomi NPP VIIRS True-color Red-Green-Blue (RGB) image viewed using RealEarth (below) showed the hazy signature of volcanic smog or “vog” which had spread out to the south, southwest and west of the Big Island. Light amounts of ash fall were reported downwind of Kilauea.

Suomi NPP VIIRS True-color RGB image [click to enlarge]

Suomi NPP VIIRS True-color RGB image [click to enlarge]

The 3.9 µm channel at night over very cold cloud tops

May 17th, 2018 |

GOES-16 ABI Infrared Imagery from 3.9 µm (Upper Left), 10.3 µm (Upper Right), 8.5 µm (Lower Left) and 12.3 µm (Lower Right), 0747 – 0832 UTC on 15 May 2018 (Click to enlarge)

When cloud top temperatures are very cold, the 3.9 µm imagery will have characteristics that suggest a noisy signal.  The 45-minute animation above shows a cold cloud top east of Florida in 4 different infrared channels:  3.9 µm (Upper Left), 10.3 µm (Upper Right), 8.5 µm (Lower Left) and 12.3 µm (Lower Right).  That the 3.9 µm image shows noise is not a new problem, as it was present in legacy GOES imagery as explained here.  At very cold temperatures the relationship between radiance (detected by the satellite) and temperature is highly non-linear, because of the character of the Planck function for that wavelength, meaning a very small change in radiance — within the noise — causes a large change in temperature (Compare the first two figures at this link for legacy GOES, for example).

Examine the two figures for GOES-16 below. They show the Planck curves for Band 14 (11.2 µm) and Band 7 (3.9 µm). Two things are apparent. Band 7 (3.9 µm), by design, covers a larger range of temperatures. In addition, very small changes in detected radiance (“counts”) at cold temperatures cause very big changes in the 3.9 µm brightness temperature. The relationship between detected radiance and very cold temperatures is much smoother at 11.2 µm.  The 3.9 µm band lacks precision compared to the other window channels, such as the 11.2 µm, for very cold temperatures. 

Plot of discrete values of Radiance vs. 11.2 µm brightness temperatures (190 K to 420 K) according to the Planck Relationship (Click to enlarge)

Plot of discrete values of Radiance vs. 3.9 µm brightness temperatures (190 K to 420 K) according to the Planck Relationship (Click to enlarge)

A zoomed-in view for cold brightness temperatures between 190 and 230 K (-83.15º C to -43.15º C) is shown below. If a true temperature of 208 K is being sensed by the satellite at the two wavelengths, it will be well-resolved at 11.2 µm, but the 3.9 µm detection will jump between 205 K and 210 K: the nature of the relationship between radiance and brightness temperature is such that there is less precision at the colder end at 3.9 µm. In the 30 K range from 197-227 K, just 12 possible bits are available in the 3.9 µm band (12 out of 2^14 — 16,384; recall that Band 7 on ABI has the highest bit depth of all the channels).  A change of just one count is a large difference in 3.9 µm brightness temperature.

Users need smarter ways to enhance the coldest 3.9 µm to prevent the flashing pixels evident in common traditional color and black-and-white enhancements.  Consider creating a color enhancement that shows only one color at temperatures colder than, say, -40º C, because the detector does not precisely distinguish between the coldest temperatures.  In other words, don’t highlight the noise!  Conversely, don’t use the 3.9 µm imagery at night to discern cloud-top features.   During the day, solar radiation at 3.9 µm reflected off cloud tops causes an increase in apparent brightness temperature so this quantization noise does not occur.

Plot of discrete values of Radiance vs. 11.2 µm brightness temperatures (190 K to 230 K) according to the Planck Relationship (Click to enlarge)

Plot of discrete values of Radiance vs. 3.9 µm brightness temperatures (190 K to 230 K) according to the Planck Relationship (Click to enlarge)

As noted above, this is not a new problem. An image (produced using McIDAS-X) of an Mesoscale Complex over the Great Plains of the United States from GOES-16 is here at 10.3 µm and here at 3.9 µm; the same image from GOES-15 is shown here at 10.7 µm and here at 3.9 µm. In both shortwave images, speckling at very cold cloud top temperatures is apparent.

(Thanks to Mat Gunshor, CIMSS, and Tim Schmit, NOAA, for figures and comments on this entry)

Severe weather in the Northeastern US

May 15th, 2018 |

GOES-16

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

Severe thunderstorms developed along and ahead of a cold front that was moving across the Northeastern US on 15 May 2018. 1-minute Mesoscale Domain Sector GOES-16 “Red” Visible (0.64 µm) images (above) showed the progression of these storms — and SPC storm reports (plotted in red, and parallax-corrected to align with the corresponding cloud-top feature) included an EF2 tornado at 2029 UTC near Kent, New York and a macroburst producing winds of 100-110 mph at 2044 UTC near Brookfield, Connecticut.

The corresponding GOES-16 “Clean” Infrared Window (10.3 µm) images (below) showed the evolution of cold overshooting tops, as well as the development of a few “enhanced-v” signatures with a pronounced warm wake immediately downwind of the cold overshooting top.

GOES-16

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

A toggle between 1-km resolution POES (NOAA-19) AVHRR Near-Infrared “Vegetation” (0.86 µm) and “Dirty” Infrared Window (12.0 µm) images (below) provided a more detailed view of the storm at 2004 UTC. SPC storm reports within +/- 30 minutes of the image are plotted on the 12.0 µm image.The coldest cloud-top infrared brightness temperature was -82ºC, associated with an overshooting top in southeastern New York.

POES (NOAA-19) Visible (0.86 µm) and Inrared (12.0 µm) images, with plots of SPC storm reports [click to enlarge]

POES (NOAA-19) Near-Infrared “Vegetation” (0.86 µm) and “Dirty” Infrared Window (12.0 µm) images, with plots of SPC storm reports [click to enlarge]

Fires in Saskatchewan

May 15th, 2018 |

GOES-16 ABI Band 1 (“Blue Visible”, 0.47 µm, top), Band 2 (“Red Visible”, 0.64 µm, middle) and Band 7 (“Shortwave Infrared”, 3.9 µm, bottom) from 1345 to 2230 UTC on 15 May 2018 (Click to animate);  Note that the yellow enhancement in the shortwave infrared starts at 305 K.

Fires that developed over the plains of Saskatchewan, near Meadow Lake in west-central Saskatchewan, and near Prince Albert in central Saskatchewan, showed up well in Visible and Infrared imagery, shown above.  A wind shift that occurred as the fires burned changed the direction of the smoke plume.  Prince Albert had visibilities that dropped to 3 statute miles.  Meadow Lake had visibilities down to 4 statute miles.

True-Color imagery (Source: (Link), imagery provided by Paul Ford, ECC Canada), also shows the distinct smoke plumes from the fires.

True-Color imagery over Saskatchewan, 1730-2000 UTC

The Dual-Pol S-band radar at Radisson captured the plume north of Prince Albert at 1900 UTC (See below; click here for the satellite imagery at that time).  Very small Cross-Correlation coefficients are apparent in the smoke plume. The radar at 2010 UTC (link) suggests 3 separate fires, which agrees with the satellite imagery. (Click here for 2015 UTC Satellite Imagery).

Cross-Correlation Scan from the dual pol, S-band at Radisson, Saskatchewan, 1900 UTC on 15 May 2018 (Click to enlarge)

Many Thanks to Paul Ford, ECC Canada, for the radar imagery, and for alerting us to this event. Saskatchewan fires can be tracked at this website. Most of Saskatchewan is currently under a fire ban.


========== ADDED ============
AWIPS imagery of this fire were collected. Click here to see the towns of the region. Full-disk imagery is available from GOES-16 at 15-minute increments. The 3.9 µm imagery is shown from 1200 to 2345 UTC, followed by the Fire RGB Imagery. The Fire RGB image combines the 3.9 µm (Red), 2.2 µm (Green) and 1.6 µm (Blue) imagery. The wavelength of the radiation emitted by the fire decreases as the temperature of the fire increases; a relatively cool fire will emit mostly 3.9 µm energy and will be red in the RGB. A very hot fire will emit all three wavelengths and will appear whiter in the RGB.

GOES-16 ABI Band 7 (“Shortwave Infrared”, 3.9 µm) from 1200 to 2345 UTC on 15 May 2018 (Click to enlarge)

GOES-16 ABI Fire RGB, combining 3.9 µm, 2.2 µm and 1.6 µm imagery, from 1200 to 2345 UTC on 15 May 2018 (Click to enlarge)

The imagery below is zoomed in on the region of the three fires.  (Map).  The 3.9 µm is shown first, then the Fire RGB.

GOES-16 ABI Band 7 (“Shortwave Infrared”, 3.9 µm) from 1200 to 2345 UTC on 15 May 2018 (Click to enlarge)

GOES-16 ABI Fire RGB, combining 3.9 µm, 2.2 µm and 1.6 µm imagery, from 1200 to 2345 UTC on 15 May 2018 (Click to enlarge)

 

The RGB — like many — gives an excellent qualitative estimate of the fire.  Quantitative estimates are available that more define the fire more comprehensively. The 1845 UTC Fire RGB suggests a very hot fire (the 3.9 µm imagery at 1845 UTC suggests the same thing). What do the Baseline fire products show? The Fire Temperature, Fire Power, and Fire Area products for 1845 UTC are shown below.  (Animations are here:  Fire Temperature, Fire Power, Fire Area)   Hotter fire pixels are apparent at 1745 and 2015 UTC.    Click for toggles of Band 7 (3.9 µm), Fire RGB and Baseline Fire Temperature at 1745 UTC, 1845 UTC, and 2015 UTC.  These products might facilitate resource allocation in a way that single channels or RGB combinations cannot.

GOES-16 Baseline Fire Temperature Product 1845 UTC on 15 May 2018 (Click to enlarge)

GOES-16 Fire Power Baseline Product, 1845 UTC on 15 May 2018 (Click to enlarge)

GOES-16 ABI Fire Area Baseline Product at 1845 UTC on 15 May 2018 (Click to enlarge)