National Tibetan Plateau Data Center: Promoting Earth System Science on the Third Pole

Xiaoduo Pan 1National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

Search for other papers by Xiaoduo Pan in
Current site
Google Scholar
PubMed
Close
,
Xuejun Guo 1National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

Search for other papers by Xuejun Guo in
Current site
Google Scholar
PubMed
Close
,
Xin Li 2National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, and Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China

Search for other papers by Xin Li in
Current site
Google Scholar
PubMed
Close
,
Xiaolei Niu 1National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

Search for other papers by Xiaolei Niu in
Current site
Google Scholar
PubMed
Close
,
Xiaojuan Yang 1National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

Search for other papers by Xiaojuan Yang in
Current site
Google Scholar
PubMed
Close
,
Min Feng 1National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

Search for other papers by Min Feng in
Current site
Google Scholar
PubMed
Close
,
Tao Che 3Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, and Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China

Search for other papers by Tao Che in
Current site
Google Scholar
PubMed
Close
,
Rui Jin 3Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, and Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China

Search for other papers by Rui Jin in
Current site
Google Scholar
PubMed
Close
,
Youhua Ran 4Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China

Search for other papers by Youhua Ran in
Current site
Google Scholar
PubMed
Close
,
Jianwen Guo 4Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China

Search for other papers by Jianwen Guo in
Current site
Google Scholar
PubMed
Close
,
Xiaoli Hu 4Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China

Search for other papers by Xiaoli Hu in
Current site
Google Scholar
PubMed
Close
, and
Adan Wu 4Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China

Search for other papers by Adan Wu in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the Third Pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3,500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high-profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle and water security, early warning assessments of glacier avalanche disasters, and other geoscience studies on the Tibetan Plateau, are highlighted in this manuscript. The TPDC provides a cloud-based platform with integrated online data acquisition, quality control, analysis, and visualization capability to maximize the efficiency of data sharing. The TPDC shifts from the traditional centralized architecture to a decentralized deployment to effectively connect Third Pole–related data from other domestic and international data sources. As an embryo of data sharing and management over extreme environment in the upcoming “big data” era, the TPDC is dedicated to filling the gaps in data collection, discovery, and consumption in the Third Pole, facilitating scientific activities, particularly those featuring extensive interdisciplinary data use.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Xin Li, xinli@itpcas.ac.cn

Abstract

The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the Third Pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3,500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high-profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle and water security, early warning assessments of glacier avalanche disasters, and other geoscience studies on the Tibetan Plateau, are highlighted in this manuscript. The TPDC provides a cloud-based platform with integrated online data acquisition, quality control, analysis, and visualization capability to maximize the efficiency of data sharing. The TPDC shifts from the traditional centralized architecture to a decentralized deployment to effectively connect Third Pole–related data from other domestic and international data sources. As an embryo of data sharing and management over extreme environment in the upcoming “big data” era, the TPDC is dedicated to filling the gaps in data collection, discovery, and consumption in the Third Pole, facilitating scientific activities, particularly those featuring extensive interdisciplinary data use.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Xin Li, xinli@itpcas.ac.cn

Supplementary Materials

    • Supplemental Materials (PDF 490 KB)
Save
  • Cao, B., T. Zhang, Q. Wu, Y. Sheng, L. Zhao, and D. Zou, 2019: Permafrost zonation index map and statistics over the Qinghai-Tibet Plateau based on field evidence. Permafrost Periglacial Processes, 30, 178194, https://doi.org/10.1002/ppp.2006.

    • Search Google Scholar
    • Export Citation
  • Carter, C. S., C. E. Bearden, E. T. Bullmore, D. H. Geschwind, D. C. Glahn, R. E. Gur, A. Meyer-Lindenberg, and D. R. Weinberger, 2017: Enhancing the informativeness and replicability of imaging genomics studies. Biol. Psychiatry, 82, 157164, https://doi.org/10.1016/j.biopsych.2016.08.019.

    • Search Google Scholar
    • Export Citation
  • Che, T., X. Li, R. Jin, R. Armstrong, and T. Zhang, 2008: Snow depth derived from passive microwave remote-sensing data in China. Ann. Glaciol., 49, 145154, https://doi.org/10.3189/172756408787814690.

    • Search Google Scholar
    • Export Citation
  • Che, T., and Coauthors, 2019: Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China. Earth Syst. Sci. Data, 11, 14831499, https://doi.org/10.5194/essd-11-1483-2019.

    • Search Google Scholar
    • Export Citation
  • Chen, F. H., and Coauthors, 2015: Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 B.P. Science, 347, 248250, https://doi.org/10.1126/science.1259172.

    • Search Google Scholar
    • Export Citation
  • Chen, F. H., and Coauthors, 2019: A late middle Pleistocene Denisovan mandible from the Tibetan Plateau. Nature, 569, 409412, https://doi.org/10.1038/s41586-019-1139-x.

    • Search Google Scholar
    • Export Citation
  • Chen, F. H., and Coauthors, 2021. The Tibetan Plateau as the engine for Asian environmental change: the Tibetan Plateau Earth system research into a new era. Sci. Bull., 66, 12631266, https://doi.org/10.1016/j.scib.2021.04.017.

    • Search Google Scholar
    • Export Citation
  • Duan, A., S. Liu, Y. Zhao, K. Gao, and W. Hu, 2018: Atmospheric heat source/sink dataset over the Tibetan Plateau based on satellite and routine meteorological observations. Big Earth Data, 2, 179189, https://doi.org/10.1080/20964471.2018.1514143.

    • Search Google Scholar
    • Export Citation
  • Guo, W., and Coauthors, 2015: The second Chinese glacier inventory: Data, methods and results. J. Glaciol., 61, 357372, https://doi.org/10.3189/2015JoG14J209.

    • Search Google Scholar
    • Export Citation
  • Hanson, B., A. Sugden, and B. Alberts, 2011: Making data maximally available. Science, 331, 649, https://doi.org/10.1126/science.1203354.

    • Search Google Scholar
    • Export Citation
  • He, J., and Coauthors, 2019: Development and evaluation of an ensemble-based data assimilation system for regional reanalysis over the Tibetan Plateau and surrounding regions. J. Adv. Model. Earth Syst., 11, 25032522, https://doi.org/10.1029/2019MS001665.

    • Search Google Scholar
    • Export Citation
  • He, J., K. Yang, W. Tang, H. Lu, J. Qin, Y. Chen, and X. Li, 2020: The first high-resolution meteorological forcing dataset for land process studies over China. Sci. Data, 7, 25, https://doi.org/10.1038/s41597-020-0369-y.

    • Search Google Scholar
    • Export Citation
  • Huang, R., H. Zhu, E. Liang, B. Liu, J. Shi, R. Zhang, Y. Yuan, and J. Grießinger, 2019: A tree ring-based winter temperature reconstruction for the southeastern Tibetan Plateau since 1340 CE. Climate Dyn., 53, 32213233, https://doi.org/10.1007/s00382-019-04695-3.

    • Search Google Scholar
    • Export Citation
  • Immerzeel, W. W., L. P. H. van Beek, and M. F. P. Bierkens, 2010: Climate change will affect the Asian water towers. Science, 328, 13821385, https://doi.org/10.1126/science.1183188.

    • Search Google Scholar
    • Export Citation
  • Immerzeel, W. W., and Coauthors, 2020: Importance and vulnerability of the world’s water towers. Nature, 577, 364369, https://doi.org/10.1038/s41586-019-1822-y.

    • Search Google Scholar
    • Export Citation
  • Jin, R., X. Li, and T. Che, 2009: A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature. Remote Sens. Environ., 113, 26512660, https://doi.org/10.1016/j.rse.2009.08.003.

    • Search Google Scholar
    • Export Citation
  • Li, X., and Coauthors, 2009: Watershed allied telemetry experimental research. J. Geophys. Res., 114, D22103, https://doi.org/10.1029/2008JD011590.

    • Search Google Scholar
    • Export Citation
  • Li, X., and Coauthors, 2011: Toward an improved data stewardship and service for environmental and ecological science data in west China. Int. J. Digital Earth, 4, 347359, https://doi.org/10.1080/17538947.2011.558123.

    • Search Google Scholar
    • Export Citation
  • Li, X., and Coauthors, 2013: Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific objectives and experimental design. Bull. Amer. Meteor. Soc., 94, 11451160, https://doi.org/10.1175/BAMS-D-12-00154.1.

    • Search Google Scholar
    • Export Citation
  • Li, X., and Coauthors, 2017: A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system. Sci. Data, 4, 170083, https://doi.org/10.1038/sdata.2017.83.

    • Search Google Scholar
    • Export Citation
  • Li, X., and Coauthors, 2019: Internet of things to network smart devices for ecosystem monitoring. Sci. Bull., 64, 12341245, https://doi.org/10.1016/j.scib.2019.07.004.

    • Search Google Scholar
    • Export Citation
  • Li, X., and Coauthors, 2020a: CASEarth poles: Big data for the three poles. Bull. Amer. Meteor. Soc., 101, E1475E1491, https://doi.org/10.1175/BAMS-D-19-0280.1.

    • Search Google Scholar
    • Export Citation
  • Li, X., F. Liu, and M. Fang, 2020b: Harmonizing models and observations: Data assimilation in Earth system science. Sci. China Earth Sci., 63, 10591068, https://doi.org/10.1007/s11430-019-9620-x.

    • Search Google Scholar
    • Export Citation
  • Li, X., and Coauthors, 2021: Boosting geoscience data sharing in China. Nat. Geosci., 14, 541542, https://doi.org/10.1038/s41561-021-00808-y.

    • Search Google Scholar
    • Export Citation
  • Liu, F., L. Wang, X. Li, and C. Huang, 2020: ComDA: A common software for nonlinear and Non-Gaussian Land Data Assimilation. Environ. Modell. Software, 127, 104638, https://doi.org/10.1016/j.envsoft.2020.104638.

    • Search Google Scholar
    • Export Citation
  • Liu, J. Y., M. L. Liu, X. Z. Deng, D. F. Zhuang, Z. X. Zhang, and D. Luo, 2002: The land use and land cover change database and its relative studies in China. J. Geogr. Sci., 12, 275282, https://doi.org/10.1007/BF02837545.

    • Search Google Scholar
    • Export Citation
  • Liu, S., and Coauthors, 2018: The Heihe integrated observatory network: A basin-scale land surface processes observatory in China. Vadose Zone J., 17, 180072, https://doi.org/10.2136/vzj2018.04.0072.

    • Search Google Scholar
    • Export Citation
  • Liu, X., Z. Cheng, L. Yan, and Z. Y. Yin, 2009: Elevation dependency of recent and future minimum surface air temperature trends in the Tibetan Plateau and its surroundings. Global Planet. Change, 68, 164174, https://doi.org/10.1016/j.gloplacha.2009.03.017.

    • Search Google Scholar
    • Export Citation
  • Ma, Y., and Coauthors, 2009: Recent advances on the study of atmosphere-land interaction observations on the Tibetan Plateau. Hydrol. Earth Syst. Sci., 13, 11031111, https://doi.org/10.5194/hess-13-1103-2009.

    • Search Google Scholar
    • Export Citation
  • Mons, B., 2020: Invest 5% of research funds in ensuring data are reusable. Nature, 578, 491, https://doi.org/10.1038/d41586-020-00505-7.

    • Search Google Scholar
    • Export Citation
  • Morse, P. E., A. M. Reading, and T. Stål, 2019: Well-posed geoscientific visualization through interactive color mapping. Front. Earth Sci., 7, 274, https://doi.org/10.3389/feart.2019.00274.

    • Search Google Scholar
    • Export Citation
  • Nuijten, M. B., 2019: Practical tools and strategies for researchers to increase replicability. Dev. Med. Child Neurol., 61, 535539, https://doi.org/10.1111/dmcn.14054.

    • Search Google Scholar
    • Export Citation
  • Parsons, M. A., R. Duerr, and J. B. Minster, 2010: Data citation and peer review. Eos, Trans. Amer. Geophys. Union, 91, 297298, https://doi.org/10.1029/2010EO340001.

    • Search Google Scholar
    • Export Citation
  • Pei, S., F. Niu, Y. Ben-Zion, Q. Sun, Y. Liu, X. Xue, J. Su, and Z. Shao, 2019: Seismic velocity reduction and accelerated recovery due to earthquakes on the Longmenshan fault. Nat. Geosci., 12, 387392, https://doi.org/10.1038/s41561-019-0347-1.

    • Search Google Scholar
    • Export Citation
  • Peng, P., and L. P. Zhu, 2017: Observations of land surface processes of the Tibetan Plateau based on the field stations network. Sci. Technol. Rev., 35, 97102.

    • Search Google Scholar
    • Export Citation
  • Peng, S., Y. Ding, W. Liu, and Z. Li, 2019: 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth Syst. Sci. Data, 11, 19311946, https://doi.org/10.5194/essd-11-1931-2019.

    • Search Google Scholar
    • Export Citation
  • Pepin, N., and Coauthors, 2015: Elevation-dependent warming in mountain regions of the world. Nat. Climate Change, 5, 424430, https://doi.org/10.1038/nclimate2563.

    • Search Google Scholar
    • Export Citation
  • Pierce, H. H., A. Dev, E. Statham, and B. E. Bierer, 2019: Credit data generators for data reuse. Nature, 570, 3032, https://doi.org/10.1038/d41586-019-01715-4.

    • Search Google Scholar
    • Export Citation
  • Piwowar, H. A., R. S. Day, and D. B. Fridsma, 2007: Sharing detailed research data is associated with increased citation rate. PLOS ONE, 2, e308, https://doi.org/10.1371/journal.pone.0000308.

    • Search Google Scholar
    • Export Citation
  • Popkin, G., 2019: Data sharing and how it can benefit your scientific career. Nature, 569, 445447, https://doi.org/10.1038/d41586-019-01506-x.

    • Search Google Scholar
    • Export Citation
  • Qiu, J., 2008: China: The Third Pole. Nature, 454, 393396, https://doi.org/10.1038/454393a.

  • Ran, Y. H., and H. Q. Ma, 2016: 1KM plant functional types map over China in 2000. Remote Sens. Tech. Appl., 331, 827832.

  • Ran, Y. H., X. Li, L. Lu, and Z. Y. Li, 2012a: Large-scale land cover mapping with the integration of multi-source information based on the Dempster–Shafer theory. Int. J. Geogr. Inf. Sci., 26, 169191, https://doi.org/10.1080/13658816.2011.577745.

    • Search Google Scholar
    • Export Citation
  • Ran, Y. H., X. Li, G. D. Cheng, T. J. Zhang, Q. B. Wu, H. J. Jin, and R. Jin, 2012b: Distribution of permafrost in China: An overview of existing permafrost maps. Permafrost and Periglacial Processes. 23, 322333, https://doi.org/10.1002/ppp.1756.

    • Search Google Scholar
    • Export Citation
  • Ran, Y. H., X. Li, and G. D. Cheng, 2018: Climate warming over the past half century has led to thermal degradation of permafrost on the Qinghai–Tibet Plateau. Cryosphere, 12, 595608, https://doi.org/10.5194/tc-12-595-2018.

    • Search Google Scholar
    • Export Citation
  • Ran, Y. H., and Coauthors, 2021: Mapping the permafrost stability on the Tibetan Plateau for 2005–2015. Sci. China Earth Sci., 64, 6279, https://doi.org/10.1007/s11430-020-9685-3.

    • Search Google Scholar
    • Export Citation
  • Shangguan, W., Y. Dai, B. Liu, A. Ye, and H. Yuan, 2012: A soil particle-size distribution dataset for regional land and climate modelling in China. Geoderma, 171–172, 8591, https://doi.org/10.1016/j.geoderma.2011.01.013.

    • Search Google Scholar
    • Export Citation
  • Shangguan, W., and Coauthors, 2013: A China data set of soil properties for land surface modeling. J. Adv. Model. Earth Syst., 5, 212224, https://doi.org/10.1002/jame.20026.

    • Search Google Scholar
    • Export Citation
  • Shi, Y., C. Liu, and E. Kang, 2009: The glacier inventory of China. Ann. Glaciol., 50, 14, https://doi.org/10.3189/172756410790595831.

    • Search Google Scholar
    • Export Citation
  • Stall, S., and Coauthors, 2019: Make scientific data FAIR. Nature, 570, 2729, https://doi.org/10.1038/d41586-019-01720-7.

  • Su, Z., J. Wen, L. Dente, R. van der Velde, L. Wang, Y. Ma, K. Yang, and Z. Hu, 2011: The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products. Hydrol. Earth Syst. Sci., 15, 23032316, https://doi.org/10.5194/hess-15-2303-2011.

    • Search Google Scholar
    • Export Citation
  • Tang, W., K. Yang, J. Qin, X. Li, and X. Niu, 2019: A 16-year dataset (2000–2015) of high-resolution (3 h, 10 km) global surface solar radiation. Earth Syst. Sci. Data, 11, 19051915, https://doi.org/10.5194/essd-11-1905-2019.

    • Search Google Scholar
    • Export Citation
  • Wu, Q. B., and F. J. Niu, 2013: Permafrost changes and engineering stability in Qinghai-Xizang Plateau. Chin. Sci. Bull., 58, 10791094, https://doi.org/10.1007/s11434-012-5587-z.

    • Search Google Scholar
    • Export Citation
  • Xu, X., Q. Wu, and Z. Zhang, 2017: Responses of active layer thickness on the Qinghai-Tibet Plateau to climate change. Bingchuan Dongtu, 39, 18.

    • Search Google Scholar
    • Export Citation
  • Yang, C. D., X. Wang, J. F. Wei, and S. Y. Liu, 2018: A dataset of glacial lake inventory of West China in 2015. Chin. Sci. Data, 3, 9.

  • Yang, K., and Coauthors, 2013: A multiscale soil moisture and freeze–thaw monitoring network on the Third Pole. Bull. Amer. Meteor. Soc., 94, 19071916, https://doi.org/10.1175/BAMS-D-12-00203.1.

    • Search Google Scholar
    • Export Citation
  • Yang, K., Y. Chen, J. He, L. Zhao, H. Lu, J. Qin, D. Zheng, and X. Li, 2020: Development of a daily soil moisture product for the period of 2002–2011 in Chinese mainland. Sci. China Earth Sci., 63, 11131125, https://doi.org/10.1007/s11430-019-9588-5.

    • Search Google Scholar
    • Export Citation
  • Yang, Z. L., L. Zhao, Y. He, and B. Wang, 2020: Perspectives for Tibetan Plateau data assimilation. Natl. Sci. Rev., 7, 495499, https://doi.org/10.1093/nsr/nwaa014.

    • Search Google Scholar
    • Export Citation
  • Yao, T., 2019: Tackling on environmental changes in Tibetan Plateau with focus on water, ecosystem and adaptation. Sci. Bull., 64, 417, https://doi.org/10.1016/j.scib.2019.03.033.

    • Search Google Scholar
    • Export Citation
  • Yao, T., and Coauthors, 2012: Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings. Nat. Climate Change, 2, 663667, https://doi.org/10.1038/nclimate1580.

    • Search Google Scholar
    • Export Citation
  • Yao, T., and Coauthors, 2015: Multispherical interactions and their effects on the Tibetan Plateau’s Earth system: A review of the recent researches. Natl. Sci. Rev., 2, 468488, https://doi.org/10.1093/nsr/nwv070.

    • Search Google Scholar
    • Export Citation
  • Yao, T., and Coauthors, 2019: Recent Third Pole’s rapid warming accompanies cryospheric melt and water cycle intensification and interactions between monsoon and environment: Multidisciplinary approach with observations, modeling, and analysis. Bull. Amer. Meteor. Soc., 100, 423444, https://doi.org/10.1175/BAMS-D-17-0057.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, G., T. Yao, H. Xie, S. Kang, and Y. Lei, 2013: Increased mass over the Tibetan Plateau: From lakes or glaciers? Geophys. Res. Lett., 40, 21252130, https://doi.org/10.1002/grl.50462.

    • Search Google Scholar
    • Export Citation
  • Zhang, G., and Coauthors, 2019: Regional differences of lake evolution across China during 1960s–2015 and its natural and anthropogenic causes. Remote Sens. Environ., 221, 386404, https://doi.org/10.1016/j.rse.2018.11.038.

    • Search Google Scholar
    • Export Citation
  • Zhang, G., and Coauthors, 2021: 100 years of lake evolution over the Qinghai–Tibet Plateau. Earth Syst. Sci. Data, 13, 39513966, https://doi.org/10.5194/essd-13-3951-2021.

    • Search Google Scholar
    • Export Citation
  • Zheng, Z. J., and D. Chu, 2019: Snow cover dataset based on optical instrument remote sensing with 1 km spatial resolution on the Qinghai-Tibet Plateau (1989–2018). National Tibetan Plateau Data Center, accessed 19 April 2021, https://doi.org/10.11888/Snow.tpdc.270465.

    • Search Google Scholar
    • Export Citation
  • Zhou, Y., D. Li, and X. Li, 2019: The effects of surface heterogeneity scale on the flux imbalance under free convection. J. Geophys. Res. Atmos., 124, 84248448, https://doi.org/10.1029/2018JD029550.

    • Search Google Scholar
    • Export Citation
  • Zou, D., and Coauthors, 2017: A new map of permafrost distribution on the Tibetan Plateau. Cryosphere, 11, 25272542, https://doi.org/10.5194/tc-11-2527-2017.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 14 0 0
Full Text Views 3615 870 48
PDF Downloads 2852 459 31