Joshua Tree National Park (JTNP) is an expansive national park encompassing distinctive microclimates in Southern California. Newly collected ground observations within the park provides the unique opportunity to test the performance of climate reanalysis/interpolation products for a large geographic area where extensive observed data have not been incorporated into models. In this study, two reanalysis products, the North American Regional Reanalysis (NARR) and the National Center for Atmospheric Research/Department of Energy Atmospheric Model Intercomparison Project Reanalysis (AMIP-II), and a climate interpolation model, Parameter-elevation Regression on Independent Slopes Model (PRISM), are tested against collected monthly air temperature observations for JTNP and for an equivalent region in and around Tucson, Arizona (TUC), and an elevation-adjusted dataset for the Tucson region (TEA). Compared to TEA, statistical analyses show that JTNP has statistically poorer model performance for the NARR (r2=.952 to r2=.883 respectively), and AMIP-II reanalysis models (r2=.911 to r2=.841), but the difference is not significant for the PRISM interpolation model (r2=.983 to r2=.984). TUC results also indicate that elevation outliers in the dataset can be locations of significant error for the NARR and AMIP-II reanalysis models. This research stresses the benefits and limitations of reanalysis models in data-sparse regions. In particular, given the marked climate and geographic sensitivity of some environmental biomes within JTNP, this study's data provide valuable information to biologists, conservationists, and others associated with monitoring these vital resources.