Enhancing GOES Channels 4 & -5 IR (long-wave) Imagery

GOES longwave infrared (channels 4 and 5) data are the easiest to understand since almost all of the energy in this portion of the spectrum is emitted from either the earth or cloud tops. There is little atmospheric absorption or emission in either of these longwave infrared window channels, with only slightly more absorption in channel-5 than in channel-4. These two infrared window channels are generally treated similarly and differences between the channels are small. Two channel-4 images (one un-enhanced and one enhanced) are given to show how to enhance imagery in this portion of the spectrum.
Un-enhanced ch. 4 IR (long-wave)

The un-enhanced GOES channel-4 image's 8-bit count values have been converted into temperatures which are written above the gray bar on the bottom of all images. The temperature scale is bi-linear with a 0.5 degree C per count resolution for temperatures warmer than -31 degrees C [242 K], and 1 degree C per count resolution for temperatures below that value. This temperature scale is the standard Look Up Table (LUT) applied to all GOES infrared channels except those for the GOES water vapor channel available for AWIPS distribution. See: http://www.cira.colostate.edu/

The original image may be enhanced by the use of a fixed color enhancement table. In this image the cloud tops colder than -31 degrees C [242 K] are treated with several color variations, starting at yellow to magenta to cyan to green. Then at about -71 degrees C [202 K] the gray shades begin again. Then below -78 degrees C [195 K] the enhancement color changes to blue, for temperatures which are seldom seen except for cloud tops in the tropics. The examples in this tutorial use the same colors to highlight temperatures below about -45 C [228 K] for both channel-3 (water vapor) and the long-wave channels, -4 and -5. The goal is to be able to easily compare cold cloud tops in these wavelengths.

Other color variations for cloud tops can be used, but the idea is to vary the colors so that any given color represents only a small variation in temperature. This effectively stretches the ability to see variations in cloud top structure. And the addition of distinctly different colors for the most extreme cloud tops or overshooting tops helps to easily identify these cloud structures.