SSMI/S 85 GHz microwave brightness temperature image

An SSMI/S 85 GHz microwave brightness temperature image from the CIMSS Tropical Cyclones site (above) displayed a well-defined eyewall structure associated with Hurricane Igor ar 11:32 UTC on 12 September 2010.

GOES-13 1-km resolution 0.63 µm visible channel images (below) showed an improving appearance to the eye of Igor during the morning hours.

GOES-13 0.63 µm visible channel images

========== UPDATE ==========

GOES-13 10.7 µm IR images

Igor rapidly intensified into a Category 4 hurricane later in the day. GOES-13 4-km resolution 10.7 µm IR images (above) displayed a well-defined eye, while a plot of the CIMSS Advanced Dvorak Technique (below) showed the trend of rapid intensification.

Plot of the CIMSS Advanced Dvorak Technique (ADT)

1-km resolution GOES-13 0.63 µm visible channel images (below) showed a fairly nice eye structure during the daytime hours.

GOES-13 0.63 µm visible channel images

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GOES-13 10.7 µm IR images

Hurricane Igor became the 4th hurricane of the season in the Atlantic Basin late in the day on 11 September 2010. GOES-13 10.7 µm IR images from the CIMSS Tropical Cyclones site (above) displayed an increasingly organized structure to the convection surrounding the center of the storm. Igor existed in an environment of low deep layer wind shear, which was a favorable factor for further intensification.

The development of a few convective bursts near the center of Igor’s circulation could be seen on GOES-13 0.63 µm visible images (below), suggesting the formation of an eyewall.

GOES-13 0.63 µm visible images

A 22:56 UTC microwave image from the SSMI/S instrument (below) revealed a well-defined convective ring around the center of Igor.

SSMI/S 85 GHz mircrowave brightness temperature

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GOES-11 / GOES-15 / GOES-13 3.9 µm shortwave IR images

A large natural gas explosion occurred in San Bruno, California on the evening of 09 September 2010, which killed 4 people and destroyed 38 homes. McIDAS images of GOES-11 (GOES-West), GOES-15, and GOES-13 (GOES-East) 3.9 µm shortwave IR channel data (above) showed the resulting fire “hot spots” (black to yellow color enhancement) during the 01:00 UTC to 04:00 UTC time period (6 pm to 9 pm local time).

The plot below shows that the maximum 3.9 µm shortwave IR pixel brightness temperatures were seen on the 01:15 UTC (6:15 pm local time) GOES-15 and GOES-13 images, and 30 minutes later at 01:45 UTC (6:45 pm local time) on the GOES-11 images.

Plot of GOES-11, GOES-15, and GOES-13 3.9 µm IR brightness temperatures

A comparison of the 1-km resolution NOAA-16 AVHRR 3.7 µm and the 4-km resolution GOES-11 3.9 µm shortwave IR images (below) showed the fire hot spot (black pixels) around 02:00 UTC (7:00 pm local time). Note the more accurate placement of the fire hot spot on the AVHRR image — San Bruno is located more toward the eastern side of the San Francisco Peninsula.

NOAA-16 AVHRR 3.7 µm shortwave IR and GOES-11 3.9 µm shortwave IR images

AWIPS images of the 1-km resolution MODIS 3.7 µm shortwave IR channel and the 4-km resolution GOES-11 3.9 µm shortwave IR data around 06:00 UTC (11:00 pm local time) can be seen below. Although no fire hot spot was evident on the GOES-11 image, a small cluster of yellow pixels could still be seen on the MODIS image.

MODIS 3.7 µm shortwave IR and GOES-11 3.9 µm shortwave IR images

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MODIS 6.7 µm water vapor image + GOES-13 6.5 µm water vapor image

AWIPS images of the 1-km resolution MODIS 6.7 µm water vapor channel and the 4-km resolution GOES-13 water vapor channel data on 09 September 2010 (above) is another great example that demonstrates how an improvement in spatial resolution leads to a dramatic improvement in the ability to detect the total areal coverage of mountain wave signatures on water vapor imagery.

Overlays of RUC model wind speeds (below) indicated that a 105-knot upper level jet was located over the region — these strong winds were interacting with the complex terrain of the Rocky Mountains to produce the widespread mountain waves.

MODIS water vapor image + RUC model wind speeds

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