Hydrological series lengths are decreasing due to decreasing investments and increasing human activities. For short sequences, a copula-based composite likelihood approach (CBCLA) has been employed to enhance the quality of hydrological design values. However, the Pearson type III (P-III) distribution for short annual precipitation records has not yet been thoroughly investigated using the CBCLA. This study used the CBCLA to incorporate the concurrent and non-concurrent periods contained in data of various lengths into an integrated framework to estimate the parameters of precipitation frequency distributions. The marginal distributions were fitted using the P-III distribution, and the joint probability was constructed using a copula which offers flexibility in choosing arbitrary marginals and dependence structure. Furthermore, the uncertainties in the estimated precipitation design values for the short series obtained from this approach were compared with those obtained from univariate analysis. Then, Monte-Carlo simulations were performed to examine the feasibility of this approach. The annual precipitation series at four stations in Weihe River basin, China, were used as a case study. Results showed that CBCLA with P-III marginals reduced the uncertainty in the precipitation design values for the short series and the reduction in the uncertainty became more significant with longer adjacent series.