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

Related authors

Estimating the sensitivity of the Priestley–Taylor coefficient to air temperature and humidity
Ziwei Liu, Hanbo Yang, Changming Li, and Taihua Wang
Hydrol. Earth Syst. Sci., 28, 4349–4360, https://doi.org/10.5194/hess-28-4349-2024,https://doi.org/10.5194/hess-28-4349-2024, 2024
Short summary
Long-term reconstruction of satellite-based precipitation, soil moisture, and snow water equivalent in China
Wencong Yang, Hanbo Yang, Changming Li, Taihua Wang, Ziwei Liu, Qingfang Hu, and Dawen Yang
Hydrol. Earth Syst. Sci., 26, 6427–6441, https://doi.org/10.5194/hess-26-6427-2022,https://doi.org/10.5194/hess-26-6427-2022, 2022
Short summary
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
Changming Li, Hanbo Yang, Wencong Yang, Ziwei Liu, Yao Jia, Sien Li, and Dawen Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-456,https://doi.org/10.5194/essd-2021-456, 2022
Revised manuscript not accepted
Short summary

Related subject area

Domain: ESSD – Land | Subject: Hydrology
A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps
Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner
Earth Syst. Sci. Data, 16, 4311–4323, https://doi.org/10.5194/essd-16-4311-2024,https://doi.org/10.5194/essd-16-4311-2024, 2024
Short summary
Satellite-based near-real-time global daily terrestrial evapotranspiration estimates
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
Earth Syst. Sci. Data, 16, 3993–4019, https://doi.org/10.5194/essd-16-3993-2024,https://doi.org/10.5194/essd-16-3993-2024, 2024
Short summary
Multivariate characterisation of a blackberry–alder agroforestry system in South Africa: hydrological, pedological, dendrological and meteorological measurements
Sibylle Kathrin Hassler, Rafael Bohn Reckziegel, Ben du Toit, Svenja Hoffmeister, Florian Kestel, Anton Kunneke, Rebekka Maier, and Jonathan Paul Sheppard
Earth Syst. Sci. Data, 16, 3935–3948, https://doi.org/10.5194/essd-16-3935-2024,https://doi.org/10.5194/essd-16-3935-2024, 2024
Short summary
SHIFT: a spatial-heterogeneity improvement in DEM-based mapping of global geomorphic floodplains
Kaihao Zheng, Peirong Lin, and Ziyun Yin
Earth Syst. Sci. Data, 16, 3873–3891, https://doi.org/10.5194/essd-16-3873-2024,https://doi.org/10.5194/essd-16-3873-2024, 2024
Short summary
First comprehensive stable isotope dataset of diverse water units in a permafrost-dominated catchment on the Qinghai–Tibet Plateau
Yuzhong Yang, Qingbai Wu, Xiaoyan Guo, Lu Zhou, Helin Yao, Dandan Zhang, Zhongqiong Zhang, Ji Chen, and Guojun Liu
Earth Syst. Sci. Data, 16, 3755–3770, https://doi.org/10.5194/essd-16-3755-2024,https://doi.org/10.5194/essd-16-3755-2024, 2024
Short summary

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. 
Bates, J. M. and Granger, C. W.: The combination of forecasts, J. Oper. Res. Soc., 20, 451–468, 1969. 
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. 
Download
Short summary
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.
Altmetrics
Final-revised paper
Preprint