  Many observational records critically rely on our ability to merge different
(and not necessarily overlapping) observations into a single composite. We
provide a novel and fully-traceable approach for doing so, which relies on a
multi-scale maximum likelihood estimator. This approach overcomes the problem
of data gaps in a natural way and uses data-driven estimates of the
uncertainties. We apply it to the total solar irradiance (TSI) composite, which
is currently being revised and is critical to our understanding of solar
radiative forcing. While the final composite is pending decisions on what
corrections to apply to the original observations, we find that the new
composite is in closest agreement with the PMOD composite and the NRLTSI2
model. In addition, we evaluate long-term uncertainties in the TSI, which
reveal a 1/f scaling
