2026-10-15T04:18:55Z https://www.scidb.cn/oai

10.57760/sciencedb.45211 2026-08-05T17:59:31Z

2026-08-05 A global 0.05° dataset of daily latent heat flux and resistances (2001–2020) derived via the Energy–Resistance–Coupling framework doi:10.57760/sciencedb.45211 en Latent heat flux (LE) is a key component of land-surface energy partitioning and plays an important role in terrestrial water–carbon interactions and land–atmosphere feedbacks. Reliable estimation of LE depends strongly on effective aerodynamic resistance (rae​) and surface resistance (rs​), which regulate turbulent transport and surface water-vapour transfer. However, most existing global products provide only final flux estimates and rarely include long-term, spatially explicit resistance-related variables.This dataset provides global daily estimates of LE, rae​, rs​​, the atmosphere–surface decoupling coefficient (Ω), and the maximum surface relative humidity parameter (hs,max⁡​) at a spatial resolution of 0.05° for the period 2001–2020. The dataset was generated using an Energy–Resistance–Coupling (ERC) iterative framework driven by multi-source remote-sensing data, meteorological reanalysis, and flux-tower observations. The framework incorporates an aerodynamic temperature (T0​) calibration scheme, an XGBoost-based dynamic constraint on hs,max⁡​​, and a Newton–Raphson solver to obtain physically constrained estimates of the resistance network and latent heat flux.The dataset was evaluated against observations from 244 flux sites. ERC-derived LE showed good agreement with site observations, with an overall R2 of 0.76 and an RMSE of 23.54 W m⁻². The estimated hs,max​ achieved an R2 of 0.91 and an RMSE of 0.06, while rae​, rs​, and Ω exhibited physically consistent spatial gradients and seasonal variations. This dataset provides a global high-resolution source of latent heat flux and resistance-related variables for drought monitoring, land–atmosphere coupling analysis, and evaluation of Earth system models. latent heat flux; aerodynamic resistance; surface resistance; land–atmosphere coupling; remote sensing Lingfei Zhang Xiaowei Wang Yazhen Jiang Shuqing Wang Menglin Si PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank