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Framework demonstrates stable gap-filling of latent heat flux in global sites, highlighting improved energy closure and temporal dynamics.
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/m² for isolated gaps and averaging 24.41 W/m² 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/m² 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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Tang et al. (2025) studied this question.
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