Hydrologic forecast models account for the movement of water from when precipitation occurs until it either becomes runoff or evaporation. These models have parameters, i.e. coefficients and exponents, that vary from one catchment to another. These parameters must be estimated, either by some a priori approach depending on catchment characteristics or by calibration with observed data or both. It is essential that precipitation data sets used for model calibration adequately reflect the local climatology of the catchment. At present a double mass analysis technique is used to compare data from a precipitation gage with surrounding stations. But the statistical basis for this technique is extremely weak and it does not explicitly consider climatological properties of the data sets. Some features of an alternative technique that considers the sampling properties of various climate statistics that are important for hydrologic modeling are presented.