Gap-Filling for Daily Latent Heat Flux Observations with the Full-factorial method at Global Flux Sites

Latent heat flux (LE) plays a crucial role in the water-energy cycle. Eddy covariance (EC) measurements of LE frequently suffer from data gaps due to weather or equipment malfunctions. This study presents a novel framework combining median-adjusted full-factorial and iterative methods to fill LE data gaps. The findings indicate that the framework exhibits stable gap-filling across land surfaces, showing RMSEs of 14.69-19.51 W/m<sup>2</sup> for isolated gaps and averaging 24.41 W/m<sup>2</sup> for long-term missing periods (5-50 days). Gap-filled LE data closely matched temporal dynamics and fluctuations of adjacent measurements. Based on gap-filled LE data, all sites demonstrated strong correlations between available energy and turbulent fluxes, with RMSE values ranging 28.41-38.01 W/m<sup>2</sup> and achieving an average energy closure of 0.79 across sites. Compared to ERA5-Land and GLEAM products, the gap-filled data significantly outperformed both LE products. Overall, the filled LE data are of high quality and significantly improve the usability of observed data. The complete time-series data from 265 sites (1509 site-years) are valuable for LE model validation and water demand assessments.

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Publication Details

Journal
Scientific Data
Published
2025-11-28
DOI
https://doi.org/10.1038/s41597-025-06144-9
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
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article

Gap-Filling for Daily Latent Heat Flux Observations with the Full-factorial method at Global Flux Sites

Yunsheng Lou, Fujiao Tang, Xiaowei Wang, Yazhen Jiang
Scientific Data
Plant Water Relations and Carbon Dynamics
article

Gap-Filling for Daily Latent Heat Flux Observations with the Full-factorial method at Global Flux Sites

Yunsheng Lou, Fujiao Tang, Xiaowei Wang, Yazhen Jiang
article en

Abstract

Latent heat flux (LE) plays a crucial role in the water-energy cycle. Eddy covariance (EC) measurements of LE frequently suffer from data gaps due to weather or equipment malfunctions. This study presents a novel framework combining median-adjusted full-factorial and iterative methods to fill LE data gaps. The findings indicate that the framework exhibits stable gap-filling across land surfaces, showing RMSEs of 14.69-19.51 W/m<sup>2</sup> for isolated gaps and averaging 24.41 W/m<sup>2</sup> for long-term missing periods (5-50 days). Gap-filled LE data closely matched temporal dynamics and fluctuations of adjacent measurements. Based on gap-filled LE data, all sites demonstrated strong correlations between available energy and turbulent fluxes, with RMSE values ranging 28.41-38.01 W/m<sup>2</sup> and achieving an average energy closure of 0.79 across sites. Compared to ERA5-Land and GLEAM products, the gap-filled data significantly outperformed both LE products. Overall, the filled LE data are of high quality and significantly improve the usability of observed data. The complete time-series data from 265 sites (1509 site-years) are valuable for LE model validation and water demand assessments.

Scientific DataVol. 12(1)
Chinese Academy of Sciences (CN), Nanjing University of Information Science and Technology (CN), Harbin Institute of Technology (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 65%
Plant Water Relations and Carbon Dynamics
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Gap-Filling for Daily Latent Heat Flux Observations with the Full-factorial method at Global Flux Sites — Yunsheng Lou, Fujiao Tang, et al. · Scientific Data (2025) | TGRS Research Map | TGRS