Abstract. The climate of the Tibetan Plateau (TP) has experienced substantial changes in recent decades as a result of the location's susceptibility to global climate change. The changes observed across the TP are closely associated with regional land–atmosphere interactions. Current models and satellites struggle to accurately depict the interactions; therefore, critical field observations on land–atmosphere interactions outlined here provide necessary independent validation data and fine-scale process insights for constraining reanalysis products, remote sensing retrievals, and land surface model parameterizations. Scientific data sharing is crucial for the TP since in situ observations are rarely available under these harsh conditions. However, field observations are currently dispersed among individuals or groups and have not yet been integrated for comprehensive analysis. This has prevented a better understanding of the interactions, the unprecedented changes they generate, and the substantial ecological and environmental consequences they bring about. In this study, we collaborated with different agencies and organizations to present a comprehensive dataset for hourly measurements of surface energy balance components, soil hydrothermal properties, and near-surface micrometeorological conditions spanning up to 17 years (2005–2021). This dataset, derived from 12 field stations covering a variety of typical TP landscapes, provides the most extensive in situ observation data available for studying land–atmosphere interactions on the TP to date in terms of both spatial coverage and duration. Three categories of observations are provided in this dataset: meteorological gradient data (met), soil hydrothermal data (soil), and turbulent flux data (flux). To assure data quality, a set of rigorous data-processing and quality control procedures are implemented for all observation elements (e.g., wind speed and direction at different height) in this dataset. The operational workflow and procedures are individually tailored to the varied types of elements at each station, including automated error screening, manual inspection, diagnostic checking, adjustments, and quality flagging. The hourly raw data series; the quality-assured data; and supplementary information, including data integrity and the percentage of correct data on a monthly scale, are provided via the National Tibetan Plateau Data Center (https://doi.org/10.11888/Atmos.tpdc.300977, Ma et al., 2023a). With the greatest number of stations covered, the fullest collection of meteorological elements, and the longest duration of observations and recordings to date, this dataset is the most extensive hourly land–atmosphere interaction observation dataset for the TP. It will serve as the benchmark for evaluating and refining land surface models, reanalysis products, and remote sensing retrievals, as well as for characterizing fine-scale land–atmosphere interaction processes of the TP and underlying influence mechanisms.

中文翻译：

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青藏高原空间广泛的长期质量保证的陆地-大气相互作用数据集


摘要。由于对全球气候变化的敏感性，青藏高原（TP）的气候在近几十年来经历了巨大的变化。青藏高原观测到的变化与区域陆地-大气相互作用密切相关。当前的模型和卫星很难准确地描述相互作用；因此，这里概述的陆地-大气相互作用的关键实地观测为约束再分析产品、遥感检索和地表模型参数化提供了必要的独立验证数据和精细过程见解。科学数据共享对于青藏高原至关重要，因为在这些恶劣条件下很难进行现场观测。然而，现场观察目前分散在个人或群体中，尚未整合进行综合分析。这阻碍了人们更好地理解相互作用、它们产生的前所未有的变化以及它们带来的重大生态和环境后果。在这项研究中，我们与不同的机构和组织合作，提供了一个全面的数据集，用于每小时测量地表能量平衡成分、土壤热液特性和近地表微气象条件，时间跨度长达 17 年（2005 年至 2021 年）。该数据集源自涵盖各种典型青藏高原景观的 12 个野外观测站，为研究青藏高原陆地-大气相互作用提供了迄今为止在空间覆盖范围和持续时间方面最广泛的实地观测数据。该数据集中提供了三类观测数据：气象梯度数据（met）、土壤热液数据（soil）和湍流通量数据（flux）。 为了保证数据质量，该数据集中的所有观测元素（例如不同高度的风速和风向）都实施了一套严格的数据处理和质量控制程序。操作工作流程和程序是根据每个站点的不同类型的元素单独定制的，包括自动错误筛选、手动检查、诊断检查、调整和质量标记。每小时的原始数据系列；有质量保证的数据；补充信息，包括月度数据完整性和正确数据百分比，由国家青藏高原数据中心提供（https://doi.org/10.11888/Atmos.tpdc.300977，Ma et al., 2023a） ）。该数据集是青藏高原迄今为止覆盖站数最多、气象要素最全、观测记录时间最长的逐时地气相互作用观测数据集。它将作为评估和完善地表模型、再分析产品和遥感反演以及描述青藏高原精细尺度陆地-大气相互作用过程和潜在影响机制的基准。