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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 (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. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) and soil freeze–thaw (FT) are two relatively active surface parameters that are significant to the sustainable development of the water–land–air–plant–human nexus. Over time, regional or global SM and FT datasets with different spatial resolutions have been developed. In response to the requirements of multiscale product validation and multisource uncertainty tracking, a soil moisture and soil temperature (ST) monitoring network in the Qinghai Lake Basin (QLB-NET) was established in September 2019. The QLB-NET is characterized by densely distributed in situ sites (82 sites) measuring SM and ST at 5-, 10-, and 30-cm depths, with 60 sites in a large-scale network covering an area of 36 km × 40 km and 22 sites evenly distributed across two small-scale 1 km × 1 km networks. Quantitative analyses of the in situ measurements show that the QLB-NET can provide stable and reliable ground truth for SM and FT over coarse grid scales, e.g., 36 km × 36 km, 25 km × 25 km, and 0.25° × 0.25°. When statistics are correspondingly performed over 50 out of 54, 25 out of 29, and 25 out of 28 sites, the results are described as follows: 1) the standard deviation of the mean SM varies between 0.0127 and 0.0196 m3 m−3, with the corresponding difference between the upper and lower quartiles being less than 0.02 m3 m−3; 2) the ground freeze–thaw state can be correctly identified with high probabilities ranging from 85.3% to 100% on two freeze–thaw transitional dates. The QLB-NET observed datasets are distributed online and will be continuously updated through cooperation with the National Tibetan Plateau Data Center (http://data.tpdc.ac.cn), facilitating product validation and uncertainty tracking, spatiotemporal analysis of SM change and FT transition, optimization of the SM and FT retrieving algorithms and scaling methods, and development of the mountainous microwave radiative transfer model. SIGNIFICANCE STATEMENT: This study aims to introduce the newly constructed QLB-NET in detail, including the site deployment strategy, the installation and maintenance, the sensor calibration, and the characteristics and quality of the in situ SM and ST measurements. Quantitative analyses of the in situ measurements show that the QLB-NET can provide stable and reliable ground truth for SM and FT over coarse grid scales, e.g., the SMAP 36 km × 36 km grid. The high-quality QLB-NET measurements will facilitate research of product validation and uncertainty tracking, spatiotemporal analysis of SM change and FT transition, optimization of the SM and FT retrieving algorithms and scaling methods, and development of the mountainous microwave radiative transfer model. [ABSTRACT FROM AUTHOR]

Oases and deserts generally act as a landscape matrix and mosaic in arid and semiarid regions. The significant difference in thermal and dynamic characteristics between an oasis and desert surface will result in oasis–desert interaction. Specifically, this refers to the interaction between an oasis and desert system via the exchange of momentum, energy, water, and carbon, which can lead to a series of microclimate effects that affect the structure of the atmospheric boundary layer, changes in carbon sources and sinks in an oasis, and the local ecological environment. Therefore, studying water, heat, and carbon exchange is significant to achieve the goals of carbon peaking and carbon neutrality in oasis–desert areas and support the ecological security and sustainable development of oases. To monitor energy, water vapor, and carbon exchange between the land surface and atmosphere, a land surface process integrated observatory network was established in the oasis–desert area in the middle and lower reaches of the Heihe River basin, the second largest endorheic basin in China. In this study, we present a suite of observational datasets from artificial and natural oasis–desert systems that consist of long-term energy, water vapor, carbon and methane fluxes as well as auxiliary data involving hydrometeorology, vegetation, and soil parameters from 2012 to 2021. Half-hourly turbulent flux data were acquired by an eddy covariance system and scintillometer. The hydrometeorological data (including radiation, soil heat flux, and soil temperature profiles; gradients of air temperature and humidity and of wind speed and direction; and air pressure, precipitation, and soil moisture profiles) were observed from automatic weather stations with a 10 min average period as well as the groundwater table data. Moreover, vegetation and soil parameters were also supplemented in the datasets. Careful data processing and quality control were implemented during data production, including data collection, processing, archiving, and sharing. The current datasets can be used to explore the water–heat–carbon process and its mechanism of influence; to calibrate and validate related remote-sensing products; to simulate energy, water vapor, and carbon exchange in oasis and desert areas; and to provide references and representatives for other similar artificial and natural oases along the "Silk Road". The data are available from the National Tibetan Plateau Third Pole Environment: 10.11888/Terre.tpdc.300441 (Liu et al., 2023). [ABSTRACT FROM AUTHOR]