Comparing remote sensing products for drought characteristics analysis in Italy

Accurate precipitation estimates are paramount for reliable hydrological monitoring of drought. Precipitation constitutes the principal input of most drought indices, and even minor systematic errors can substantially influence the detection, timing, and intensity of drought episodes. This concern is especially pronounced for indices such as the Standardized Precipitation Index (SPI), which depend solely on precipitation records and are extensively employed in operational drought monitoring across various time scales. In areas like Italy, defined by rugged terrain, interactions between coastal and mountain environments, and an irregular network of rain-gauge stations, uncertainties in rainfall measurement can propagate directly into drought evaluations, potentially undermining the dependability of decision-support tools. To overcome these shortcomings, satellite-derived precipitation products have become vital for surface-based observations, offering spatially continuous coverage and near-real-time availability. Nevertheless, their accuracy varies considerably according to retrieval technique, spatial resolution, and the dominant weather conditions, making a thorough evaluation essential prior to their use in drought monitoring applications. This study aims to examine how various satellite precipitation products influence SPI-based drought characterization across Italy. Four widely adopted satellite precipitation datasets, CHIRPS, GPM, PDIRNOW, and SM2RAIN, were chosen to represent a wide spectrum of retrieval strategies, including infrared–station hybrid methods, passive microwave integration, multi-sensor geostationary blending, neural-network-driven infrared approaches, and soil-moisture inversion techniques. Their varied temporal and spatial resolutions render them appropriate for both research purposes and operational monitoring contexts. SPI values derived from each satellite product were systematically compared. The analysis reveals pronounced discrepancies in SPI magnitude, frequency, and duration depending on the precipitation dataset used, evidencing how sensitive drought assessments are to errors in rainfall estimation. The findings show that no individual satellite product consistently surpasses the others, and suggest that combining multiple satellite datasets or adopting hybrid methodologies can enhance the robustness of SPI-based drought monitoring in complex Mediterranean settings. Furthermore, the results highlight the importance of establishing a benchmark dataset. The use of ground-based measurements, even over a geographically restricted area, can help to identify the most appropriate product, ultimately allowing for a more dependable analysis of the spatial patterns of drought events, with direct relevance to water resource planning and management.