I'm trying to understand this answer: https://stats.stackexchange.com/a/151969/25186 which details Fisher's geometric derivation of the t-distribution.
There are some loose ends in my understand I'm trying to wrap up. For reference, we'll need the figure presented there.

In the description of the figure, the answerer says:
The figure depicts the upper hemisphere (with $Z \ge 0$) of $S^s$ in $\mathbb{R}^{s+1}$. The crossed axes span the $W$-hyperplane. The black dots are part of a random sample of a $s+1$-variate standard Normal distribution: they are the values projecting to a constant given latitude $\theta$, shown as the yellow band. The density of these dots is proportional to the $s-1$-dimensional volume of that band, which itself is an $S^{s-1}$ of radius $\theta$.
So far so good.
The cone over that band is drawn to terminate at a height of $\tan \theta$. Up to a factor of $\sqrt{s}$, the Student t distribution with $s$ degrees of freedom is the distribution of this height as weighted by the measure of the yellow band upon normalizing the area of the unit sphere $S^s$ to unity.
Why is the cone drawn to terminate at $\tan \theta$? What significance does this have? Aren't all points projected on this space at whatever height eligible for projection to the sphere?
It seems they use the notation $S^s$ to refer to the surface of an $s+1$ dimensional sphere. Is that correct? If so, I couldn't find other references to this notation anywhere. Can someone point to any links?
Next, about the normalizing constant:
Incidentally, the normalizing constant must be $1/\sqrt{s}$ (as previously mentioned) times the relative volumes of the spheres,
- Why is this?