查看大图

This file contains the datasets used in a manuscript published in JGR Biogeosciences (Nieberding, F., Wille, C., Ma, Y., Wang, Y., Maurischat, P., Lehnert, L., and Sachs, T.: Winter daytime warming and shift in summer monsoon increase plant cover and net CO2 uptake in a central Tibetan alpine steppe ecosystem, Journal of Geophysical Research: Biogeosciences, 126, e2021JG006441, doi:10.1029/2021JG006441, 2021.). The manuscript contains all the details on how the data was generated and processed and the corresponding code was published in the supplementary material.

数据文件命名方式和使用方法

The file "df_EP.csv" contains the processed half-hourly EddyPro full_output (https://www.licor.com/env/support/EddyPro/topics/output-files-full-output.html) and biomet data between 2005 and 2019.
The file "df_meteo_gf.csv" contains half hourly meteorological variables from NAMORS between 2005 and 2019, which have been gap filled using annual linear regression with the same variables from different measurement heigths.
The file "df_precipitation_NamCo_2005-2019.csv" contains daily precipitation measurements from NAMORS between 2005 and 2019.
The file" variable_description.csv" contains the variable descriptions and physical units for the above mentioned datasets.
The file "subset_plantcover.nc" contains an array of annual plant cover estimates applying the pre-trained support vector machine regression (SVM) models published in Lehnert et al. (2015) to to multispectral satellite data acquired by Landsat 5, 7, and 8 at 30 m spatial resolution between 2005 and 2020.

本数据要求的引用方式 查看数据引用帮助 数据引用必读

Felix Nieberding, 马耀明, Christian Wille, Lukas Lehnert, Yuyang Wang, Philipp Maurischat, Weiqiang Ma, Torsten Sachs. (2021). Half-hourly Eddy Covariance fluxes, gap-filled meteorological variables, precipitation and remotely sensed plant cover estimations from NAMORS between 2005 and 2020. 时空三极环境大数据平台, DOI: 10.11888/Meteoro.tpdc.271274. CSTR: 18406.11.Meteoro.tpdc.271274.
[Felix, N., Ma, Y., Cristian, W., Lehnert, L., Wang, Y., Maurischat, P., Ma, W., Torsten, S. (2021). . A Big Earth Data Platform for Three Poles, DOI: 10.11888/Meteoro.tpdc.271274. CSTR: 18406.11.Meteoro.tpdc.271274. ] (下载引用： RIS格式 | RIS英文格式 | Bibtex格式 | Bibtex英文格式 )

1. Nieberding, F., Wille, C., Ma, Y., Wang, Y., Maurischat, P., Lehnert, L., & Sachs, T. (2021). Winter daytime warming and shift in summer monsoon increase plant cover and net CO2 uptake in a central Tibetan alpine steppe ecosystem. Journal of Geophysical Research: Biogeosciences, 126, e2021JG006441, doi:10.1029/2021JG006441.( 查看 | Bibtex格式)

2. Nieberding, F., Wille, C., Fratini, G., Asmussen, M. O., Wang, Y., Ma, Y., and Sachs, T. (2020). A Long Term (2005–2019) Eddy Covariance Data Set of CO2 and H2O Fluxes from the Tibetan Alpine Steppe, Earth Syst. Sci. Data, doi:10.5194/essd-2020-63.( 查看 | Bibtex格式)

3. Lehnert, L. W., Meyer, H., Wang, Y., Miehe, G., Thies, B., Reudenbach, C., and Bendix, J. (2015). Retrieval of grassland plant coverage on the Tibetan Plateau based on a multi-scale, multi-sensor and multi-method approach, Remote Sensing of Environment, 164, 197–207, doi:10.1016/j.rse.2015.04.020.( 查看 | Bibtex格式)

4. Ma, Y.M., Ma, W.Q., Zhong, L., Hu, Z., Li, M., Zhu, Z., et al. (2017). Monitoring and Modeling the Tibetan Plateau’s climate system and its impact on East Asia, Scientific Reports, 7, 44574, doi:10.1038/srep44574.( 查看 | Bibtex格式)

5. Ma, Y.M., Kang, S.C., Zhu, L.P., Xu, B.Q., Tian, L.D., & Yao, T.D. (2008). Tibetan Observation and Research Platform- Atmosphere–land interaction over a heterogeneous landscape, Bulletin of the American Meteorological Society. 89, 1487–1492. doi:10.1175/2008BAMS2545.1.( 查看 | Bibtex格式)

使用本数据时必须引用“文章的引用”中列出的文献，并进行数据的引用

资助项目

国家自然科学基金 (项目编号:91837208) National Natural Science Foundation of China

中国科学院Ａ类战略性先导科技专项 (项目编号:XDA20060101) The Strategic Priority Research Program of Chinese Academy of Sciences

第二次青藏高原综合科学考察研究 (项目编号:2019QZKK0103) The Second Tibetan Plateau Scientific Expedition and Research (STEP) program

数据使用声明

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)

相关资源

数据评论

当前页面默认显示 中文 评论 显示所有语种的评论