A Comprehensive Hourly Land–Atmosphere Interaction Dataset from a Coordinated 15-Station Network Spanning the Environmental Gradients of the Tibetan Plateau (2021–24)

Abstract Accurate characterization of land–atmosphere interactions over the Tibetan Plateau (TP) is hindered by fragmented measurements, inconsistent data-processing standards, and a scarcity of integrated, multi-component observations. To address these limitations, we present an integrated dataset from 15 stations spanning monsoon-dominated, westerlies-dominated, and transitional regions of the TP. The dataset features hourly gradient meteorological variables, radiation components, soil temperature and moisture measurements, and turbulent fluxes, providing vertically resolved information on land surface processes. Processed under standardized protocols with harmonized temporal resolutions, consistent variable definitions, and rigorous quality control procedures, the data ensure high reliability and internal consistency. This dataset provides a robust observational foundation for advancing process-based understanding of land–atmosphere coupling and its representation in models over the TP. It is expected to support land surface and Earth system model evaluation, satellite product validation, and data assimilation. Furthermore, it provides a basis for developing hybrid physics-machine learning approaches for data quality control and gap-filling in-situ observations in complex high-altitude environments.