The increased effect of spring leaf unfolding on autumn senescence in the northern and southern hemispheres

This dataset was generated to analyze the impacts of vegetation growth carryover (VGC) and climate factors on plant phenology at a global scale. It includes satellite NDVI data from GIMMS NDVI 3g (1982–2015) and MODIS NDVI (2001–2022), as well as ground-based phenological observations from PEP 725 (1963–2015). Additionally, the dataset incorporates climate data from ERA5, including temperature, precipitation, radiation, and potential evapotranspiration, spanning 1982–2022. The dataset provides start-of-season (SOS) and end-of-season (EOS) metrics alongside these climatic variables. Covering the Northern and Southern Hemispheres, the dataset offers insights into global phenological trends, carbon cycling, and vegetation-climate interactions under changing climatic conditions. This dataset is intended for use in phenology studies, ecosystem modeling, and global change research.

Methods
This dataset was collected from multiple sources. Satellite NDVI data were obtained from GIMMS NDVI 3g (1982–2015) and MODIS NDVI (2001–2022), providing global vegetation indices. Ground-based phenological observations were retrieved from the PEP 725 database (1963–2015), covering European regions. Climate data, including temperature, precipitation, radiation, and potential evapotranspiration, were extracted from ERA5 reanalysis datasets (1982–2022). Raw NDVI data were smoothed using a Savitzky-Golay filter to reduce noise. Start-of-season (SOS) and end-of-season (EOS) metrics were extracted by fitting a double logistic function to the smoothed NDVI time series. Climate data were spatially interpolated to match NDVI data resolution (0.1° × 0.1°), and all datasets were aligned temporally and spatially. Data processing and analysis were conducted in Python, with geospatial operations performed in ArcGIS.