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Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau.

Authors :
Ma, Yaoming
Xie, Zhipeng
Chen, Yingying
Liu, Shaomin
Che, Tao
Xu, Ziwei
Shang, Lunyu
He, Xiaobo
Meng, Xianhong
Ma, Weiqiang
Xu, Baiqing
Zhao, Huabiao
Wang, Junbo
Wu, Guangjian
Li, Xin
Source :
Earth System Science Data; 2024, Vol. 16 Issue 6, p3017-3043, 27p
Publication Year :
2024

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 (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]

Details

Language :
English
ISSN :
18663508
Volume :
16
Issue :
6
Database :
Complementary Index
Journal :
Earth System Science Data
Publication Type :
Academic Journal
Accession number :
178316069
Full Text :
https://doi.org/10.5194/essd-16-3017-2024