An evaluation of ERA5-Land Reanalysis Data for drought monitoring: comparison with drought indices from observational datasets in Sicily

Reliable drought monitoring based on standardized indices requires long, gap-free hydrological datasets. Reanalysis products such as ERA5-Land are increasingly used for this purpose due to their spatial coverage and temporal continuity; however, their biases in temperature and precipitation may propagate into drought indices such as SPI and SPEI. This study assesses the suitability of ERA5-Land for drought monitoring over Sicily—an ideal testbed thanks to its complex terrain, recurrent droughts, and availability of long-term observations. ERA5-Land temperature and precipitation were compared with a gridded observational dataset (1951–2013) using Nash–Sutcliffe Efficiency (NSE), RMSE, and correlation. ERA5-Land reproduced temperature well (correlation >0.9, NSE >0.8, RMSE <3 °C), whereas precipitation showed weaker skill (correlation 0.6–0.8, NSE often <0.5, RMSE 20–80 mm). Biases propagated into drought indices: long-term SPI and SPEI (24–48 months) were reasonably consistent with observations (correlation 0.75–0.9), while short-term indices exhibited limited skill, including negative NSE values. Results highlight both the potential and limitations of ERA5-Land for drought assessment in Mediterranean environments. They underline the need for spatial and temporal bias correction when using reanalysis-driven drought indices for agricultural planning and water resource management in regions with complex climatic and topographic settings.