GS-P output: the growing seasons of global forest ecosystems from 1850 to 2100 estimated with a probabilistic temperature-based model

Citation and usage If you use this dataset, please cite the associated publication and acknowledge the GS-P model. Proper citation is required in all derived works. Description This dataset provides global estimates of the Start (SGS) and End (EGS) of the forest growing season derived from the GS-P model, a probabilistic, temperature-based framework developed within a machine-learning approach. The data cover historical (ERA5, 2001–2023; UKESM1-0-LL, 1850-2014, historical experiment) and future climate conditions (UKESM1-0-LL simulations under SSP scenarios), at global scale. Outputs are provided as NetCDF files. File naming follows the convention: GS-P_ERA5_2001-2023.nc (reanalysis-driven estimates) GS-P_UKESM1-0-LL_sspXXX_YYYY-ZZZZ.nc (climate model projections) Each file contains gridded SGS and EGS estimates, representing the timing of leaf-out and senescence phases of forest ecosystems. Further use For additional simulations, custom scenarios, or methodological inquiries, please contact the authors.