Data for: Green droughts as a rising phenomenon in Central Europe

This dataset accompanies the manuscript "Green droughts as a rising phenomenon in Central Europe" and contains all variables used in the analyses presented in the publication. The dataset contains the variables used to identify and analyse the occurrence of green drought across Central Europe during the period 2000–2025. Green drought is defined as the simultaneous occurrence of soil moisture deficit, hydrological drought, and normal or above-normal vegetation activity. The analyses were performed for Germany, Poland, the Czech Republic, and Slovakia, using NUTS1 regions for Germany and Poland and NUTS2 regions for the Czech Republic and Slovakia. All variables were aggregated to a weekly temporal resolution. Three indicators were used to define green drought: Soil moisture deficit (AWD) representing the anomaly of soil water availability within the 0–100 cm soil profile; Standardized Runoff Index (SRI) representing hydrological drought conditions; Vegetation condition (VegCon) derived from satellite-based EVI2 anomalies. The following thresholds were applied to identify green drought conditions: AWD: values range from −100 mm to +100 mm, with −20 mm used as the threshold for soil drought. Vegetation condition (VegCon): expressed as a percentage relative to the long-term mean vegetation condition. Values between 90 and 110% represent normal vegetation activity. Green drought was identified when vegetation condition remained within or above this range. SRI: values range from −3 to +3, with a threshold of −1 indicating hydrological drought associated with below-normal streamflow. Vegetation condition was evaluated using the two-band Enhanced Vegetation Index (EVI2) derived from reflected radiation in the near-infrared and visible red spectral regions (Jiang et al., 2008; Rocha and Shaver, 2009). EVI2 was calculated from observations acquired by the MODIS Terra satellite (NASA) at a spatial resolution of 250 m. To reduce variability caused by crop rotation and seasonal changes in vegetation cover, the data were aggregated to a 5 × 5 km grid and evaluated at a weekly time step. Vegetation condition was expressed as the percentage of the long-term mean for each calendar week during the 2000–2025 reference period. Soil moisture deficit (AWD) represents the anomaly in soil water availability relative to the 1961–2010 reference period and is expressed in millimetres for the 0–100 cm soil profile. AWD was estimated using the SoilClim model, which simulates soil moisture dynamics while accounting for vegetation development, phenology, rooting depth, snow processes, soil properties, land cover, and meteorological conditions. SoilClim operates on a 500 m spatial grid and produces weekly estimates of soil moisture conditions. The Standardized Runoff Index (SRI) was derived from simulations of the mesoscale Hydrologic Model (mHM). mHM is a spatially distributed hydrological model driven by daily precipitation, air temperature, and potential evapotranspiration. It simulates snow accumulation and melt, evapotranspiration, infiltration, groundwater recharge, baseflow generation, and river routing. Daily discharge simulations were aggregated to monthly mean streamflow to calculate the 1-month SRI. A two-parameter Gamma distribution was fitted separately for each calendar month using the 1981–2020 reference period, and runoff values were transformed into standardized normal deviates. For this study, monthly SRI values were subsequently aggregated to weekly values to ensure consistency with the AWD and vegetation datasets. Negative SRI values indicate below-normal streamflow conditions, whereas positive values indicate above-normal runoff. Dataset metadata Variables AWD – Soil moisture deficit (mm) SRI – Standardized Runoff Index (dimensionless) VegCon – Vegetation condition anomaly (% of the long-term mean) Spatial units Germany (DE) – NUTS1 Poland (PL) – NUTS1 Czech Republic (CZ) – NUTS2 Slovakia (SK) – NUTS2 Temporal coverage 2000–2025 Temporal resolution Weekly Seasonal aggregation MAM – March–May JJA – June–August SON – September–November Spatial unit Administrative regions (NUTS1 and NUTS2)