Articles | Volume 17, issue 11
https://doi.org/10.5194/essd-17-6445-2025
https://doi.org/10.5194/essd-17-6445-2025
Data description paper
 | 
25 Nov 2025
Data description paper |  | 25 Nov 2025

Multi-spatial scale assessment and multi-dataset fusion of global terrestrial evapotranspiration datasets

Yi Wu, Chiyuan Miao, Yiying Wang, Qi Zhang, Jiachen Ji, and Yuanfang Chai

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Cited articles

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Our study introduces BMA-ET, a novel multi-dataset fusion product. Spanning 1980 to 2020 with spatial resolution of 0.5° and 1°, BMA-ET uses Bayesian model averaging (BMA) to combine thirty evapotranspiration (ET) datasets. A key innovation is dynamic weighting scheme, which adjusts for vegetation types and non-common coverage years among ET datasets. BMA-ET provides a comprehensive resource for understanding global ET patterns and trends, addressing the limitation of prior ET fusion efforts.
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