Reconstruction of High-Resolution Daily Precipitation Field over Sicily since 1951: A Doubly Conditional Atlas

Long-term, high-resolution precipitation datasets are indispensable for understanding hydroclimatic variability and supporting water-resource and climate-impact studies. Yet, the reconstruction of spatially consistent rainfall fields over extended historical periods remains a major challenge, particularly in data-sparse Mediterranean regions characterized by complex terrain and pronounced precipitation heterogeneity. The purpose of the present study is to present the first long-term, high-resolution gridded precipitation dataset for Sicily, delivering a continuous historical reconstruction since 1951 from sparse gauge observations through a novel two-phase, doubly conditional spatial interpolation framework. Calibration was performed on a dense modern network of automated rain gauges; a Transfer-Informed Modelling strategy, whereby all geostatistical parameters calibrated on this high-density contemporary period are transferred without modification to epochs of substantially lower network density, ensures temporal coherence across the full historical record. A merged archive of historical stations was assembled from two independent networks following rigorous homogeneity assessment of inter-network spatial coherence prior to reconstruction. Three principal methodological innovations distinguish the framework: (i) a double classification of daily events by intermittency and magnitude into distinct hydrometeorological regimes having unique spatial correlation structures; (ii) a comparison of regime-specific intensity-modelling paradigms based on geostatistics or regression; and (iii) a contrast of binary masking against probabilistic hurdle-weighting for occurrence-conditional intensity. Leave-one-out cross-validation demonstrated high rainfall detection capability across all intermittency classes and established the consistent superiority of the geostatistical framework over its regression-kriging counterpart across all hydrometeorological regimes. The superior framework was consequently selected for operational historical reconstruction. Validated against an independent monthly climatological benchmark over the full study period, the bias-corrected primary dataset reproduces the reference climatology with high fidelity, affirming its fitness for long-term hydroclimatic analysis across topographically complex Mediterranean terrain.