Below is a list of most of the accepted and measurable definitions for times of static.
White Noise - A random signal with a consistent power spectral density. In other words, a signal that contains equal power within any frequency band with a fixed width.
Pink Noise - Also called Flicker Noise, this has signal with a frequency spectrum with a power spectral density that is inversely proportional to the frequency. Here each octave carries an equal amount of noise power. But each octave represents a frequency band twice as large, in arithmetic terms, as the one below it, so when plotted on a spectrogram this would produce a line with a steep decline. More here.
Brown Noise - Also called Red Noise, or Brownian Noise. This signal decreases in power by 12 dB per octave. That sounds specific because it is also the kind of signal noise produced by Brownian motion. The sound is kind of a low roar resembling a heavy rainfall, similar to Purple Noise.
Blue Noise - The power density of this signal increases 3 dB per octave with increasing frequency, the inverse of pink noise. The power density is directly proportional to the frequency. In computer graphics, it's actually used for dithering. More here.
Green Noise - This signal is similar to pink noise but it has a power spike centered around 500 Hz. It has some technical applications in halftone dithering.
Purple Noise - Also called Violet noise, here the power density increases 6 dB per octave across the spectrum with increasing frequency. It has a power density directly proportional to the square of the frequency. More here.
Grey Noise - This is very similar to white noise except that the plotted spectrum is arched downward in the middle like a traditional smiley-face amplifier EQ. This gives the impression of it being equally loud at all frequencies, though it is not. It's exploiting the nature of the human ear.
Black Noise - Noise that has a frequency spectrum of predominantly zero power level over all frequencies except for a few narrow bands or spikes.