PREP: A software for assessing and visualizing seasonal and spatial representativeness of climate proxies

Historical temperature reconstructions are primarily derived from climate proxy data such as tree-ring. Discrepancies among temperature reconstructions have prompted considerable debate, with much of this variation attributable to differences in the representativeness of the underlying proxy data. Representativeness refers to the specific seasonal temperature variations indicated by the proxies and the strength of their correlation with instrumental records, as well as the spatial extent over which they are applicable. At present, visualizations of historical climate change through science platforms predominantly rely on reconstruction curves, lacking effective methods to convey the representativeness of proxy data. In this study, we developed the Proxy Representativeness Evaluation Package (PREP), a software that employs a "clock-layout" to depict seasonality by dividing the clock dial into twelve 30° segments (one per month) and encodes correlation by fill color. We further optimized the algorithm for plotting representativeness maps, achieving more than a 50-fold increase in computational efficiency.