Yu et al. (2025) Long-term land–atmosphere energy and water exchange observational dataset over central Tibetan Plateau

Identification

• Journal: Earth system science data
• Year: 2025
• Date: 2025-12-08
• Authors: Haipeng Yu, Guantian Wang, Zeyong Hu, Yaoming Ma, Maoshan Li, Weiqiang Ma, Lianglei Gu, Fanglin Sun, Huiwang Gao, Shujin Wang, Fuquan Lu
• DOI: 10.5194/essd-17-6871-2025

Research Groups

• Nagqu Plateau Climate and Environment Observation and Research Station of Tibet Autonomous Region, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
• Tianjin Meteorological Observatory, Tianjin, China
• Land-Atmosphere Interaction and Its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
• School of Atmospheric Sciences, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu Plain Urban Meteorology and Environment Observation and Research Station of Sichuan Province, Chengdu University of Information Technology, Chengdu, China
• University of Chinese Academy of Sciences, Beijing, China

Short Summary

This paper presents a 9-year (2014–2022) hourly observational dataset of land-atmosphere energy and water exchange from four field stations across the central Tibetan Plateau, providing crucial data for understanding regional climate dynamics. The dataset, which includes near-surface meteorological, radiation, turbulent flux, and soil hydrothermal characteristics, reliably reflects the complex interactions across diverse underlying surfaces and temporal scales.

Objective

• To present a long-term, high-resolution observational dataset of land-atmosphere interactions over the central Tibetan Plateau (CTP) to address the scarcity of field observation data in this challenging environment.

Study Configuration

• Spatial Scale: Four field stations (BJ, Amdo, NewD66, MS3478) in the Nagqu region of the central Tibetan Plateau, representing diverse underlying surfaces: plateau grassland, plateau meadow, plateau wetland, and plateau bareland.
• Temporal Scale: 9-year period (2014–2022) with hourly temporal resolution for the dataset. Observations were recorded at sampling frequencies of 10 s or 0.1 s, with output intervals of 30 min, which were then processed into hourly data.

Methodology and Data

• Models used: Not applicable for dataset generation; the data is purely observational. The dataset is intended for use in numerical simulations and climate assessments.
• Data sources: Observational data collected from the Nagqu Plateau Climate and Environment Observation Network (NPCE) using:
  • Planetary Boundary Layer (PBL) towers and Automatic Weather Stations (AWS) for vertical profiles of air temperature, relative humidity, wind direction, and wind speed.
  • Multilayer soil temperature and moisture probes (5–160 cm depth).
  • High-frequency Eddy Covariance (EC) systems for sensible, latent, and carbon dioxide fluxes.
  • Surface observations including air temperature, humidity, radiative quadrature, atmospheric pressure, precipitation, and snow depth.
  • Additional instruments at BJ station: ground-based microwave radiometer, blowing snow observation instrument, and wind profile radar.
  • Data underwent rigorous quality control, including range checks and manual outlier removal, with turbulent fluxes assigned quality classifications (0, 1, 2).

Main Results

• The dataset reveals distinct diurnal and seasonal patterns in near-surface meteorological variables, radiation fluxes, turbulent fluxes, CO2 concentrations, and soil hydrothermal characteristics across the four stations, reflecting the influence of different underlying surfaces.
• Temperature exhibits clear diurnal patterns with maximums around 18:00 LT and minimums around 09:00 LT, and seasonal peaks in summer (June-September). NewD66 (bareland) shows the most pronounced diurnal temperature variations and lower nighttime temperatures.
• Relative humidity decreases during the day and increases at night, with NewD66 consistently lower (below 50%). Wind speeds generally increase with altitude, lower at night and higher during the day, with prevailing westerlies in winter and northeast winds during the monsoon season.
• Radiation fluxes show similar diurnal patterns, with downward shortwave radiation peaking in May and decreasing during the monsoon season due to cloud cover. Net surface radiation is highest in summer and lowest in winter.
• Sensible heat flux (SH) is stronger in spring and weaker in summer, peaking in April (February for wetland MS3478). Latent heat flux (LH) shows an inverse trend, rapidly rising in May and maintaining levels above 100 W m−2 throughout summer, peaking in July (June for MS3478).
• Soil heat flux (SHF) shows moderate seasonal variation with clear diurnal cycles. NewD66 exhibits the most pronounced diurnal and interannual variability in SHF.
• CO2 concentrations show a diurnal cycle (nighttime increase, daytime decrease) with minimal monthly variation, more pronounced at densely vegetated stations (BJ, MS3478) compared to bareland (NewD66).
• Soil temperature variations diminish with depth and show seasonal delays. Soil moisture is higher in summer due to snowmelt and precipitation, with significant differences between stations, e.g., MS3478 (wetland) maintaining high soil moisture levels.

Contributions

• Provides the most detailed and extensive long-term (9-year) raw observational dataset on the central Tibetan Plateau's spatial coverage and recent changes, filling a critical data gap in a challenging, data-scarce region.
• Offers a high-time-resolution (hourly) dataset of near-surface meteorological, radiation, turbulent flux, and soil hydrothermal characteristics from four diverse stations, ensuring data quality through rigorous processing and quality control.
• Enables a more accurate and comprehensive depiction of land-atmosphere interactions and boundary layer structure on the Tibetan Plateau.
• Serves as a crucial resource for high-precision numerical simulations, in-depth research into land-atmosphere interaction mechanisms, and comprehensive assessments of the plateau's energy and water cycles and climate change.
• Supports the validation and calibration of satellite-derived products and land surface models, enhancing their accuracy over complex high-altitude terrain.

Funding

• Science and Technology Projects of Xizang Autonomous Region, China (grant no. XZ202501JD0022)
• National Natural Science Foundation of China (grant nos. 42330609, U2442207)
• Youth Innovation Promotion Association of Chinese Academy of Sciences (grant no. 2021427)
• West Light Foundation of the Chinese Academy of Sciences (grant no. xbzg-zdsys-202409)
• Key talent project in Gansu
• Central Guidance Fund for Local Science and Technology Development Projects in Gansu (grant no. 24ZYQA031)

Citation

@article{Yu2025Longterm,
  author = {Yu, Haipeng and Wang, Guantian and Hu, Zeyong and Ma, Yaoming and Li, Maoshan and Ma, Weiqiang and Gu, Lianglei and Sun, Fanglin and Gao, Huiwang and Wang, Shujin and Lu, Fuquan},
  title = {Long-term land–atmosphere energy and water exchange observational dataset over central Tibetan Plateau},
  journal = {Earth system science data},
  year = {2025},
  doi = {10.5194/essd-17-6871-2025},
  url = {https://doi.org/10.5194/essd-17-6871-2025}
}