Error Characterization and Multi-source Merging of Global Land Evapotranspiration Products: Collocation-based approach
Abstract
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 (1981-2020) ET product at 0.1°-8Daily and 0.25°-Daily resolutions and evaluate the performance against 82 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 0.68, and 0.62 and root mean square errors of 0.84 and 1.03 mm/d on average over 0.1° and 0.25°. The produced Collocation-Analyzed Multisource Ensembled Land Evapotranspiration Data (CAMELE) are freely available at https://doi.org/10.5281/zenodo.6616791 (0.1°-8day-average) and https://doi.org/10.5281/zenodo.6616815 (0.25°-daily).
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H54C..01L