Articles | Volume 16, issue 4
https://doi.org/10.5194/essd-16-1811-2024
https://doi.org/10.5194/essd-16-1811-2024
Data description paper
 | 
12 Apr 2024
Data description paper |  | 12 Apr 2024

CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data

Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, and Hanbo Yang

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Cited articles

Baker, J. C. A., Garcia-Carreras, L., Gloor, M., Marsham, J. H., Buermann, W., da Rocha, H. R., Nobre, A. D., de Araujo, A. C., and Spracklen, D. V.: Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models, Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, 2021. 
Barraza Bernadas, V., Grings, F., Restrepo-Coupe, N., and Huete, A.: Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple collocation method, Int. J. Remote Sens., 39, 6300–6315, 2018. 
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Chen, Z., Zhu, Z., Jiang, H., and Sun, S.: Estimating daily reference evapotranspiration based on limited meteorological data using deep learning and classical machine learning methods, J. Hydrol., 591, 125286, https://doi.org/10.1016/j.jhydrol.2020.125286, 2020. 
De Lannoy, G. J., Houser, P. R., Verhoest, N. E., Pauwels, V. R., and Gish, T. J.: Upscaling of point soil moisture measurements to field averages at the OPE3 test site, J. Hydrol., 343, 1–11, 2007. 
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Using a collocation-based approach, we developed a reliable global land evapotranspiration product (CAMELE) by merging multi-source datasets. The CAMELE product outperformed individual input datasets and showed satisfactory performance compared to reference data. It also demonstrated superiority for different plant functional types. Our study provides a promising solution for data fusion. The CAMELE dataset allows for detailed research and a better understanding of land–atmosphere interactions.
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