Models with low observed uncertainty compared to rv uncertainty

Sorry, that is what I mean. What I was thinking was is it possible to do something like:

with pm.Model() as model:
    define my model here...

    y = pm.Normal('y',mu=surrogate_out, sd=factor*sigma, observed=data)

where factor can start as a large number and be gradually decreased as the sampling converges?