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 AgERA5 v2.0 reanalysis product (https://cds.climate.copernicus.eu/datasets/sis-agrometeorological-indicators?tab=overview), ensuring a consistent and high-quality methodological foundation across the entire time series and variable coverage. The computational workflow, implemented in Python using the open-source xclim and xarray libraries, converts daily meteorological variables into a collection of over 70 indicators and statistical measures. The dataset has a spatial resolution of 0.1° across the globe and spans the years 1979 to 2023. Variables are available at annual and, where applicable, monthly temporal resolutions to support analyses of seasonal dynamics. The data are provided via three distinct datasets: First, bioclimatic indicators (19 variables), which adhere to the ANUCLIM BIO1 to BIO19 definitions as implemented in the xclim library (https://xclim.readthedocs.io/en/stable/indicators_api.html#module-xclim.indicators.anuclim). These include: BIO01 Mean Annual Temperature, BIO02 Diurnal Temperature Range, BIO03 Isothermality, BIO04 Temperature Seasonality, BIO05 Highest Daily Maximum Temperature, BIO06 Lowest Daily Minimum Temperature, BIO07 Temperature Annual Range, BIO08 Mean Temperature of Wettest Quarter, BIO09 Mean Temperature of Driest Quarter, BIO10 Mean Temperature of Warmest Quarter, BIO11 Mean Temperature of Coldest Quarter, BIO12 Annual Precipitation Sum, BIO13 Precipitation of Wettest Month, BIO14 Precipitation of Driest Month, BIO15 Precipitation Seasonality, BIO16 Precipitation of Wettest Quarter, BIO17 Precipitation of Driest Quarter, BIO18 Precipitation of Warmest Quarter, and BIO19 Precipitation of Coldest Quarter. Second, the specialized agrometeorological indices (16 variables), including Aridity Index, Consecutive Frost Days, Consecutive Wet Days, Continentality Index, Dry Days, Frost Days, Growing Degree Days, Growing Season Length, Heat Wave Index, Heavy Wet Days, Ice Days, Inverted Water Deficit, Last Spring Frost, Maximum Consecutive Dry Days, Precipitation Range, and Wet Days. Third, the statistical variables of foundational input variables (40 variables): The minimum, mean, maximum, and variance of daily mean temperature, maximum temperature, minimum temperature, cloud cover, precipitation, reference evapotranspiration (RET), minimum relative humidity, maximum relative humidity, solar radiation flux, and wind speed. This dataset accompanies the Data Descriptor by Schneider & Klinnert (2026) in Scientific Data. The data are openly available under the CC-BY 4.0 license. Users are asked to cite both the Data Descriptor in Scientific Data and the AgERA5 input data in any publications.
Schneider, Kevin; Klinnert, Ana (2026). A global dataset of climate indices and statistics for agro-environmental research covering 1979 to 2023. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/AGERAINDICES
SQA - Scientific Quality Assurance 'approved by author'
Result Date
2026-05-22
Technical Quality Assurance (TQA)
TQA - Technical Quality Assurance 'approved by WDCC'
Description
1. Number of data sets is correct and > 0: passed; 2. Size of every data set is > 0: passed; 3. The data sets and corresponding metadata are accessible: passed; 4. The data sizes are controlled and correct: passed; 5. The spatial-temporal coverage description (metadata) is consistent to the data: passed; 6. The format is correct: passed; 7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
[1] DOIBoogaard, H.; Schubert, J.; De Wit, A.; Lazebnik, J.; Hutjes, R.; Van der Grijn, G. (2020). Agrometeorological indicators from 1979 to present derived from reanalysis. Copernicus Climate Change Service (C3S) Climate Data Store (CDS) (Accessed on 01-JUN-2025). doi:10.24381/cds.6c68c9bb