Chinese FLUX Observation and Research Network (ChinaFLUX) Thematic Observation Datasets Zone II Versions ZH3 Vol 6 (1) 2021
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An observation dataset of carbon, water and heat fluxes over an alpine shrubland in Haibei (2003–2010)
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: 2020 - 05 - 06
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: 2020 - 05 - 22
: 2021 - 03 - 29
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Abstract & Keywords
Abstract: Alpine shrublands are an important vegetation on the Qinghai-Tibetan Plateau, a hotspot and sensitive area of global climate change. The spatial-temporal pattern and ecological process of their carbon, water, and heat fluxes are one of the most important keys to exploring the ecological function of the Plateau. Haibei National Field Research Station for Alpine Grassland (Haibei Station) is a field station of ChinaFLUX, which has used the eddy covariance technique to monitor the carbon, water, and heat fluxes over an alpine Potentilla fruticosa shrubland for 17 years since 2003. In order to promote the development of carbon, water, and heat fluxes and other related researches in the Qinghai-Tibetan Plateau and even in the global alpine ecosystems, we plan to publish the routine meteorological data of carbon, water and heat fluxes over an alpine shrubland observed from 2003 to 2010. This dataset includes routine meteorological data subset (air temperature, air relative humidity, water vapor pressure, wind speed, wind direction, soil temperature, soil moisture, total radiation, net radiation, photosynthetically active radiation, and precipitation) and carbon, water, and heat fluxes data subset (net ecosystem CO2 exchange, ecosystem CO2 respiration, gross ecosystem CO2 exchange, latent heat flux, and sensible heat flux) on a half-hour, day, month, and year scale. This dataset provides field observational data support for scientific knowledge, remote sensing retrieval, and model validation in exploring spatiotemporal patterns of carbon, water, and heat exchanges in alpine shrubland ecosystems.
Keywords: eddy covariance technique; carbon, water and heat fluxes; alpine shrubland; Potentilla fruticosa; Qinghai-Tibetan Plateau
Dataset Profile
TitleAn observation dataset of carbon, water and heat fluxes over an alpine shrubland in Haibei (2003–2010)
CorrespondenceLI Yingnian (ynli@nwipb.cas.cn)
Data producersObserver: ZHANG Fawei, LI Hongqin, ZHAO Liang, ZHANG Leiming, CHEN Zhi, ZHU Jingbin, XU Shixiao, YANG Yongsheng, ZHAO Xinquan, YU Guirui, LI Yingnian Director: LI Yingnian
Time range2003–2010
Study siteHaibei National Field Research Station for alpine grassland ecosystem, Menyuan county, Qinghai Province, China (37°37′N, 101°19′E)
Ecosystem typeAlpine Potentilla fruticosa Shrubland
Data amount36 MB
Data format*.xlsx
Data service system<http://www.cnern.org.cn/data/initDRsearch?cid=SYC_A02>
<http://www.sciencedb.cn/dataSet/handle/1007>
Source of fundingNational Key R&D Program (2017YFA0604801); National Natural Science Foundation of China (41877547, 32001149); Qinghai R&D Infrastructure and Facility Development Program (2018-ZJ-T09); Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19020302).
Dataset compositionThe dataset includes routine meteorological data (air temperature, relative humidity, water vapor, wind velocity, wind direction, atmosphere pressure, soil temperature, soil moisture, total radiation, net radiation, photosynthetically active radiation, and precipitation) and carbon, water, and heat fluxes data (net ecosystem CO2 exchange flux, ecosystem CO2 respiration, gross ecosystem CO2 exchange flux, latent heat flux, and sensible heat flux) on a half-hour, day, month, and year scale, in which the half-hour flux data are interpolated data.
Article and author information
Zhang Fawei
主要承担工作:数据监测和论文撰写。
Li Hongqin
主要承担工作:数据分析与论文修改。
Zhao Liang
主要承担工作:数据整理与质量控制。
Zhang Leiming
主要承担工作:数据处理和质量控制。
chenzhi
主要承担工作:数据质量分析。
Zhu Jingbin
主要承担工作:数据整理和论文修改。
Xu Shixiao
主要承担工作:数据整理。
Yang Yongsheng
主要承担工作:数据整理。
Zhao Xinquan
主要承担工作:数据管理和统筹。
Yu Guirui
主要承担工作:数据管理和统筹。
Li Yingnian
主要承担工作:数据分析和质量控制。
ynli@nwipb.cas.cn
Publication records
Released: May 22, 2020 ( VersionsZH2
Published: March 29, 2021 ( VersionsZH3
References
中国科学数据
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