In this study, we develop a three steps rank adjustment procedure to constrain future projections of interest. This procedure uses nonparametric present-future relations from a given multi model ensemble (MME) to estimate the rank distribution of observations in future projection period to constrain the corresponding projections. We then applied this rank adjustment procedure to constrain future projections of the global mean surface temperature (GMST) as well as the surface temperature and the precipitation fields from the CMIP5 Representative Concentration Pathway 8.5 (RCP85) scenario MME. For the GMST, we successfully narrow the 5 - 95 uncertainty range by one-half at the end of the 21st century. For the surface temperature field, the constrained MME medians averaged over 2081 - 2100 exhibit more smooth and homogeneous spatial variations than those original MME medians. More interestingly, the corresponding projected precipitation field are completely free from the long-standing double ITCZ bias. These results suggest that the use of rank adjustment procedure is capable of yielding more consistent future projections for both the surface temperature and the precipitation fields. More importantly, because the rank adjustment procedure is based on nonparametric present-future relations of a given MME, one expects that it have wider range of applicability than previously identified and proposed emergent constraints.