The best way to think about digital clocks is with the concept of a Fourier Series:
https://en.wikipedia.org/wiki/Fourier_series
Basically, any non-sinusoidal signal can be represented as a sinusoid at the base frequency of the clock, plug a sum of the harmonics of the base frequency...with each of the signals have a different magnitude and phase.
For example: A perfect square wave (which is what you want in a digital system) at 100 MHz will be composed of a sine wave at 100 MHz, 300 MHz, 500 MHz, etc.
However, it's impossible to generate a "perfect" square wave as this would require a circuit with infinite bandwidth.
The faster the rise or fall time, the more higher frequency content is required.
If you look at a frequency spectrum plot of a square wave, you will see the largest peak at the fundamental frequency, and peaks of reducing amplitude at multiples of the fundamental frequency.
A common mistake (that my engineers just made last week) is to look at a 50 MHz square wave signal on an oscilloscope with a 200 MHz bandwidth...and then spend hours troubleshooting the circuit as it's ringing. I smack them up side the head, remind them of their buddy Fourier, have them get an oscilloscope with a 1 GHz bandwidth...and solve their non-existent problem.
Spread spectrum is a technique where you vary the frequency of the source signal (square wave, sine wave, etc.) a few percent (to 10's of percents...depends on the application). When you look at this sort of signal in the frequency spectrum, you will see a peak that represents a "spread" of frequencies for the fundamental and harmonics. The amplitude of these peaks will be lower, but the energy will still be the same. (The energy is calculated by integrating the signals...or calculating the area under the curve in the frequency spectrum.)
EMI testing is all about keeping your peak energies below the required values...and less about the total spectral energy your circuit produces.
I hope that helps explain stuff...it's kind of hard to break down high level electrical engineering concepts when you may not have a lot of the necessary physics and calculus background...if I confused anybody, let me know and I will try to explain differently.
(A common mathematical technique used in electrical engineering is to do a Fourier Transform on a signal in the time domain. This will produce the frequency domain content of the time domain signal. Consequently, you can do an Inverse Fourier Transform on the frequency domain content to get the time domain content. The reason you do this is that you can multiply subsequent circuit transfer functions in the frequency domain...but would have to do a rather ugly convolution in the time domain to get the same result. An FFT is a Fast Fourier Transform (and IFFT for Inverse FFT) that uses digital sampling techniques to produce an approximate of the mathematical Fourier Transform calculation.)
