In order to assess the astronaut exposure received within vehicles or habitats, accurate models of the ambient galactic cosmic ray (GCR) environment are required. Many models have been developed and compared to measurements, with uncertainty estimates often stated to be within 15%. However, intercode comparisons can lead to differences in effective dose exceeding 50%. This is the second of three papers focused on resolving this discrepancy. The first paper showed that GCR heavy ions with boundary energies below 500 MeV/n induce less than 5% of the total effective dose behind shielding. Yet, due to limitations on available data, model development and validation are heavily influenced by comparisons to measurements taken below 500 MeV/n. In the current work, the focus is on developing an efficient method for propagating uncertainties in the ambient GCR environment to effective dose values behind shielding. A simple approach utilizing sensitivity results from the first paper is described and shown to be equivalent to a computationally expensive Monte Carlo uncertainty propagation. The simple approach allows a full uncertainty propagation to be performed once GCR uncertainty distributions are established. This rapid analysis capability may be integrated into broader probabilistic radiation shielding analysis and also allows error bars (representing boundary condition uncertainty) to be placed around point estimates of effective dose.