Meteorological drought poses severe challenges in regions with intricate topography, such as southern Poland. This study evaluates the suitability of ERA5-Land reanalysis for drought monitoring in the Upper Vistula Basin, which encompasses mountainous, upland and lowland areas. The primary objective was to assess the agreement between ERA5-Land and in situ precipitation-based Standardised Precipitation Index (SPI) values across multiple timescales (3–24 months). Using precipitation records from 25 meteorological stations (1961–2023) and ERA5-Land gridded data, SPI was calculated for each dataset. Trend detection employed Sen's slope estimator, and drought characteristics (frequency, duration, severity, intensity) were derived using the run theory. The statistical performance of ERA5-Land was evaluated via Pearson correlation, RMSE, and spatial pattern analysis. Results reveal that ERA5-Land provides high accuracy for detecting short-term droughts (SPI-3), especially in dry extremes (SPI < −1), whereas it underperforms in representing prolonged droughts and overestimates wet conditions (SPI > 1), particularly at longer timescales. The results support regional-scale drought monitoring and water management applications by clarifying the strengths and limitations of ERA5-Land under local hydro-climatic conditions. Findings validate the utility of ERA5-Land for meteorological drought analysis in complex terrain and support its integration with observational networks to enhance regional climate assessments.
Validation of ERA5-Land Precipitation Data for Meteorological Drought Assessment in the Upper Vistula Basin, Central Europe
Chiaravalloti F.;De Marco A.;Caloiero T.Ultimo
2026
Abstract
Meteorological drought poses severe challenges in regions with intricate topography, such as southern Poland. This study evaluates the suitability of ERA5-Land reanalysis for drought monitoring in the Upper Vistula Basin, which encompasses mountainous, upland and lowland areas. The primary objective was to assess the agreement between ERA5-Land and in situ precipitation-based Standardised Precipitation Index (SPI) values across multiple timescales (3–24 months). Using precipitation records from 25 meteorological stations (1961–2023) and ERA5-Land gridded data, SPI was calculated for each dataset. Trend detection employed Sen's slope estimator, and drought characteristics (frequency, duration, severity, intensity) were derived using the run theory. The statistical performance of ERA5-Land was evaluated via Pearson correlation, RMSE, and spatial pattern analysis. Results reveal that ERA5-Land provides high accuracy for detecting short-term droughts (SPI-3), especially in dry extremes (SPI < −1), whereas it underperforms in representing prolonged droughts and overestimates wet conditions (SPI > 1), particularly at longer timescales. The results support regional-scale drought monitoring and water management applications by clarifying the strengths and limitations of ERA5-Land under local hydro-climatic conditions. Findings validate the utility of ERA5-Land for meteorological drought analysis in complex terrain and support its integration with observational networks to enhance regional climate assessments.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
