Error Characterization and Multi-source Merging of Global Land Evapotranspiration Products: Collocation-based approach

Evapotranspiration (ET) is one of the key elements linking Earth’s water-carbon system. Accurate estimation of global land evapotranspiration is essential for understanding land-atmosphere interactions under a changing climate. Past decades have witnessed the generation of various ET products. However, due to a lack of observations at the global scale, inherent uncertainties limit the direct use of these data. Here, the aims of our study were as follows: (1) to employ collocation analysis methods, including single and double instrumental variable algorithms (IVS/IVD), triple collocation (TC), quadruple collocation (QC), and extended double instrumental variable algorithms (EIVD) to evaluate five widely used ET products at 0.1° and 0.25° resolutions over daily and 8-day frequencies, including ERA5, FLUXCOM, PMLV2, GLDAS, and GLEAM; (2) to design and validate a collocation-based method for ET merging and generate a long-term (1980-2022) ET product at 0.1°-8Daily and 0.25°-Daily resolutions and evaluate the performance against 68 global flux tower observations. Our results demonstrated that: (1) collocation analysis methods could be reliable tools to serve as alternatives for tower observations at the global scale, which could be helpful for further data assimilation and merging; (2) the merged product performed well over different vegetation types with Correlation of Determination () of 0.65, and 0.61 and root mean square errors () of 0.94 and 1.22 mm/d on average over 0.1° and 0.25°.