Estimates of the Priestley-Taylor coefficient based on FLUXNET data at multiple spatiotemporal scales

The Priestley-Taylor equation (PT) is a key method for estimating regional evapotranspiration (ET) calculation, with the precision of its parameter (alpha) being crucial for accurate ET calculations across diverse plant functional types (PFTs). In this study, we explored the temporal and spatial variability of alpha and its biotic and abiotic drivers leveraging observations from 163 global flux sites spanning diverse PFTs. The results showed that the mean annual alpha was 0.86 across all sites, with high alpha values predominantly located in humid regions and diminished values in arid locales. In terms of seasonality, the alpha showed similar fluctuation patterns in the Northern or Southern Hemispheres with lower values in local summer and higher ones in spring and autumn. The spatial variations in alpha were mainly caused by climatic factors while the temporal variations were mainly driven by seasonal vegetation change. Among all factors, vapor pressure deficit, air temperature, precipitation and shortwave radiation were significantly correlated with alpha. Among vegetation types, deciduous needleleaf forests had the highest alpha (1.1), and open shrublands had the lowest alpha (0.5). Leaf Area Index (LAI) and canopy height significantly affected alpha in forest site, with varying mechanisms across vegetation types. Combining the observed alpha and global meteorological datasets, we employed a machine learning (random forest) model to establish global alpha dataset. The results enhanced the understanding of the biological and environmental controls of land surface energy flux, aiding in ET prediction across multiple spatiotemporal scales.