Station-Constrained FAO-56 Reference Evapotranspiration Dataset for Ghana

This dataset contains a station-constrained daily and monthly reference evapotranspiration (ET₀) dataset developed for Ghana using the standardized FAO-56 Penman–Monteith method. The dataset was produced by integrating observations from 22 Ghana Meteorological Agency (GMet) synoptic stations with bias-corrected NASA Prediction of Worldwide Energy Resources (NASA POWER) meteorological data to generate a spatially continuous, high-resolution reference evapotranspiration product. Daily ET₀ was computed for the period 1990–2024 following the FAO Irrigation and Drainage Paper No. 56 methodology. NASA POWER and ERA5 meteorological variables were first evaluated against GMet observations and corrected using several statistical bias-correction techniques. Polynomial regression was identified as the most effective method and was subsequently applied to the complete NASA POWER dataset (which was the dataset that performed better). The corrected dataset was then interpolated using Ordinary Kriging with a spherical semivariogram model to generate continuous spatial surfaces. Finally, the interpolated dataset was merged with station observations through a weighted station-constrained data fusion approach to preserve local accuracy while maintaining complete national spatial coverage. The dataset covers the entire territory of Ghana and includes the country's Coastal, Forest, Transition, and Savannah ecological zones. It is provided at approximately 3.7 x 3.7 km spatial resolution with daily temporal resolution. The repository includes: Daily station-constrained ET₀ dataset for Ghana (1990–2024); Monthly station-constrained ET₀ dataset for Ghana; Other formats such as NetCDF and Spatial raster products (GeoTIFF) will be available upon reasonable request. The dataset was developed to improve the spatial accuracy of FAO-56 reference evapotranspiration estimates for agricultural water management, irrigation scheduling, drought monitoring, hydrological modelling, climate impact assessment, and environmental research in Ghana. It also provides a reproducible framework for developing station-constrained evapotranspiration datasets in other regions with sparse meteorological observations. If this dataset is used in scientific publications, please cite both this Zenodo dataset and the associated journal article: Bonsu, R.B, et al. Development and Analysis of a Station-Constrained Reference Evapotranspiration Dataset for Ghana (1990–2024). (Journal information and DOI to be updated after publication.)