Bayesian structural time series modeling

One question - is there a writeup or reference material somewhere that will provide more insight into why re-parameterizing it this way helps improve s_slope and s_level estimation (deviation of slope and level).

For s_level, we do have:
s_level = (u[t] - (u[t-1]+v[t-1]))/u_err[t]

That is where I am stuck at currently.