Extracting and sub-setting geospatial climate data for crop modelling
Brief model summary
Several platforms provide open-access geospatial data from satellites, ground observations, and model outputs, managed by agencies such as NASA and ECMWF. These data sources vary widely in format and structure, tailored to their specific objectives. For example, atmospheric reanalysis datasets often feature high temporal resolutions and large volumes, requiring significant computational resources to handle. In agricultural research, there is a focus on surface weather variables, which must often be extracted from broader geospatial datasets. Furthermore, agricultural researchers commonly require data in formats different from the original, creating bottlenecks as processing tools may not be compatible with standard geophysical data formats.
Fig 1. Clim2Agri factsheet
Clim2Agri is a Python tool developed to streamline access and processing of climate data for the agricultural research community, specifically for crop modeling and analysis. It enables extraction and subsetting of climate data from diverse gridded products and formats, transforming them into formats commonly used in agricultural research (e.g., CSV, TXT). Hosted on the CGIAR Foresight Initiative GitHub repository, Clim2Agri facilitates single-point time-series extraction, allowing users to specify variables, data products, and output formats suited to crop models like DSSAT, AquaCrop, and APSIM by simply inputting geographical coordinates. This adaptability makes Clim2Agri an essential resource for varied agricultural research applications.
Model workflow
Input data
Clim2Agri supports various gridded climate data products. The following table shows the products and variables provided by them.
List of variables provided by each selected gridded climate data product.
| AgEra5 | CHIRPS | MSWEP | MSWX | NASA POWER | PERSIANN | |
| Temperature | x | x | x | |||
| Radiation | x | x | ||||
| Precipitation | x | x | x | x | x | x |
| Windspeed | x | x | ||||
| T dew | x | x | ||||
| Relative Humidity | x | |||||
| Vapor pressure | x |
Output metrics
Clim2Agri extracts climate data from the above presented products, to generate output files in the format required by various crop simulation models, as schematized in workflow figure. The supported crop models include:
Software requirements
The tool for extracting climate and weather data for crop models is Python-based.
Accessibility
User Documentation
There is a report on Clim2Agri (see general documentation below) That includes a user guide how to use the code.
Model code
The model code of Clim2Agri is available as open source code through CGIAR Foresight Initiative GitHub repository:
References
General documentation
Montes, C., & Gómez, F. (2023). Clim2Agri version 1.0. CIMMYT. https://hdl.handle.net/11529/10549012
Please use this document as reference when citing the use of Clim2Agri.
Acknowledgements
The development of Clim2Agri was supported by the CGIAR initiative on Foresight.