Mapping variations of redshift distributions with probability integral transforms

We present a method for mapping variations between probability distribution functions and apply this within the context of measuring galaxy redshift distributions from imaging survey data. This method, which we name PITPZ integral transformations it relies on, uses difference in curves an ensemble as transformation to another function, thus transferring variation latter function. procedure is broadly applicable problem uncertainty propagation. In distributions, example, contribution due certain effects can be studied effectively only simulations, necessitating transfer measured simulations illustrate use by using propagate photometric calibration Dark Energy Survey Year 3 weak lensing source galaxies. For test case, find that yields amplitude estimate error 1 per cent truth, compared much 30 underestimate when traditional methods.