Fundamentally, our objective has not been to illustrate the vast variety of cases in which CRAM fails to obtain a suitable solution, and in which E-CRAM succeeds; the limitations of CRAM are acknowledged and well established. Rather, we seek to present E-CRAM as a companion method (as distinct from a successor) to CRAM. Although CRAM and E-CRAM share much of the same heritage in terms of their constraints on spectral ratio parameters, they are distinct methods, each applicable in slightly different circumstances, though their objectives in terms of solutions are essentially the same. There is a vast repository of data that can benefit substantially from a more thorough application of the traditional CRAM method (the CALIOP lidar is probably the best example), by which the uncertainties on 1064-nm aerosol retrievals can be reduced. E-CRAM is a means by which we propose to augment and diversify the set of aerosol models underpinning the CRAM method. Application of E-CRAM to data from instruments such as HSRL makes such improvements possible, and we believe that we have laid out a clear and compelling framework for how the process might work. This seems to be among the more exciting possible applications for E-CRAM. Alternatively, E-CRAM offers a compelling approach to 1064-nm aerosol retrievals from so-called two-beta, one-alpha systems [i.e., attenuated backscatter (one beta) from one channel, and aerosol backscatter and extinction (one beta and one alpha) from a second channel]. Many such systems are beginning to come online, also three-beta, two-alpha systems, to which E-CRAM could also be applied (possibly even more stably) by imposing simultaneous constraints across two wavelengths, and perhaps also relaxing substantially the requirement on spatial homogeneity.