This project focuses on the processing of high-resolution climate reanalysis data to generate easy-to-use agro-environmental indicators and variables. The core scientific idea is to bridge the temporal
This experiment provides a global dataset of agrometeorological and bioclimatic indicators for use by ecologists, agronomists, and environmental economists. The dataset is derived exclusively from the
We provide all the necessary scripts to reproduce the data in its entirety. The accompanying .zip file contains four distinct Python scripts that execute the full data processing workflow. These scripts
The dataset contains bioclimatic indicators derived from daily AgERA5 data. These indices are provided as annual and, where applicable, monthly variables with a resolution of 0.1 degrees across the globe from 1979 to 2023.
The dataset contains a collection of agriculturally relevant indices derived from daily AgERA5 data. These indices are provided as annual and, where applicable, monthly variables with a resolution of 0.1 degrees across the globe from 1979 to 2023.
The dataset contains statistical variables derived from daily AgERA5 data. These statistics (min., mean, max., variance) are provided as annual and monthly variables with a resolution of 0.1 degrees across the globe from 1979 to 2023.