Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-1147-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-1147-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
10 Feb 2026
Data description article |
| 10 Feb 2026
| 10 Feb 2026
Quantifying the spatial-seasonal patterns of land–atmosphere water, heat and CO2 flux exchange over the Tibetan Plateau from an observational perspective
Binbin Wang
CORRESPONDING AUTHOR
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, 45320 Islamabad, Pakistan
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China
National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, 45320 Islamabad, Pakistan
Zeyong Hu
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Xuan Li
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Weiqiang Ma
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China
National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, 45320 Islamabad, Pakistan
Xuelong Chen
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, 45320 Islamabad, Pakistan
Cunbo Han
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, 45320 Islamabad, Pakistan
Zhipeng Xie
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, 45320 Islamabad, Pakistan
Yuyang Wang
College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China
Maoshan Li
School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China
Bin Ma
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, 45320 Islamabad, Pakistan
Xingdong Shi
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China
Zhengling Cai
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China
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María P. González-Dugo, Xuelong Chen, Ana Andreu, Elisabet Carpintero, Pedro J. Gómez-Giraldez, Arnaud Carrara, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 755–768, https://doi.org/10.5194/hess-25-755-2021, https://doi.org/10.5194/hess-25-755-2021, 2021
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Cited articles
André, J. C., Goutorbe, J. P., and Perrier, A.: HAPEX – MOBILHY: A Hydrologic Atmospheric Experiment the Study of Water Budget and Evaporation Flux at the Climatic Scale, Bulletin of the American Meteorological Society, 67, 138–144, https://doi.org/10.1175/1520-0477-67.2.138, 1986.
Baldocchi, D.: Measuring fluxes of trace gases and energy between ecosystems and the atmosphere – the state and future of the eddy covariance method, Global Change Biology, 20, 3600–3609, https://doi.org/10.1111/gcb.12649, 2014.
Bei, N., Zhao, L., Wu, J., Li, X., Feng, T., and Li, G.: Impacts of sea-land and mountain-valley circulations on the air pollution in Beijing-Tianjin-Hebei (BTH): A case study, Environmental Pollution, 234, 429–438, https://doi.org/10.1016/j.envpol.2017.11.066, 2018.
Chen, X., Cao, D., Liu, Y., Xu, X., and Ma, Y.: An observational view of rainfall characteristics and evaluation of ERA5 diurnal cycle in the Yarlung Tsangbo Grand Canyon, China, Quarterly Journal of the Royal Meteorological Society, 149, 1459–1472, https://doi.org/10.1002/qj.4468, 2023.
Duan, A. and Xiao, Z.: Does the climate warming hiatus exist over the Tibetan Plateau?, Scientific Reports, 5, 13711, https://doi.org/10.1038/srep13711, 2015.
Foken, T.: The energy balance closure problem: An overview, Ecological Applications, 18, 1351–1367, https://doi.org/10.1890/06-0922.1, 2008.
Gatti, L. V., Basso, L. S., Miller, J. B., Gloor, M., Gatti Domingues, L., Cassol, H. L. G., Tejada, G., Aragão, L. E. O. C., Nobre, C., Peters, W., Marani, L., Arai, E., Sanches, A. H., Corrêa, S. M., Anderson, L., von Randow, C., Correia, C. S. C., Crispim, S. P., and Neves, R. A. L.: Amazonia as a carbon source linked to deforestation and climate change, Nature, 595, 388–393, https://doi.org/10.1038/s41586-021-03629-6, 2021.
Gentine, P., Massmann, A., Lintner, B. R., Hamed Alemohammad, S., Fu, R., Green, J. K., Kennedy, D., and Vilà-Guerau de Arellano, J.: Land–atmosphere interactions in the tropics – a review, Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, 2019.
Gerken, T., Biermann, T., Babel, W., Herzog, M., Ma, Y., Foken, T., and Graf, H. F.: A modelling investigation into lake-breeze development and convection triggering in the Nam Co Lake basin, Tibetan Plateau, Theoretical and Applied Climatology, 117, 149–167, https://doi.org/10.1007/s00704-013-0987-9, 2014.
Goutorbe, J. P., Lebel, T., Dolman, A. J., Gash, J. H. C., Kabat, P., Kerr, Y. H., Monteny, B., Prince, S. D., Stricker, J. N. M., Tinga, A., and Wallace, J. S.: An overview of HAPEX-Sahel: a study in climate and desertification, Journal of Hydrology, 188–189, 4–17, https://doi.org/10.1016/S0022-1694(96)03308-2, 1997.
Halldin, S., Gryning, S. E., Gottschalk, L., Jochum, A., Lundin, L. C., and Van de Griend, A. A.: Energy, water and carbon exchange in a boreal forest landscape – NOPEX experiences, Agricultural and Forest Meteorology, 98–99, 5–29, https://doi.org/10.1016/S0168-1923(99)00148-3, 1999.
Huang, J., Zhou, X., Wu, G., Xu, X., Zhao, Q., Liu, Y., Duan, A., Xie, Y., Ma, Y., Zhao, P., Yang, S., Yang, K., Yang, H., Bian, J., Fu, Y., Ge, J., Liu, Y., Wu, Q., Yu, H., Wang, B., Bao, Q., and Qie, K.: Global Climate Impacts of Land-Surface and Atmospheric Processes Over the Tibetan Plateau, Reviews of Geophysics, 61, e2022RG000771, https://doi.org/10.1029/2022RG000771, 2023.
Li, G., Yu, Z., Wang, W., Ju, Q., and Chen, X.: Analysis of the spatial Distribution of precipitation and topography with GPM data in the Tibetan Plateau, Atmospheric Research, 247, 105259, https://doi.org/10.1016/j.atmosres.2020.105259, 2021a.
Li, L., Zhang, R., Wu, P., Wen, M., and Duan, J.: Roles of Tibetan Plateau vortices in the heavy rainfall over southwestern China in early July 2018, Atmospheric Research, 245, 105059, https://doi.org/10.1016/j.atmosres.2020.105059, 2020.
Li, P., Furtado, K., Zhou, T., Chen, H., and Li, J.: Convection-permitting modelling improves simulated precipitation over the central and eastern Tibetan Plateau, Quarterly Journal of the Royal Meteorological Society, 147, 341–362, https://doi.org/10.1002/qj.3921, 2021b.
Liu, S., Li, X., Xu, Z., Che, T., Xiao, Q., Ma, M., Liu, Q., Jin, R., Guo, J., Wang, L., Wang, W., Qi, Y., Li, H., Xu, T., Ran, Y., Hu, X., Shi, S., Zhu, Z., Tan, J., Zhang, Y., and Ren, Z.: The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China, Vadose Zone Journal, 17, 180072, https://doi.org/10.2136/vzj2018.04.0072, 2018.
Lü, D., Chen, Z., Wang, G., Chen, J., Ji, J., Li, Y., and Chen, H.: Inner Mongolia Semi-Arid Grassland Soil-Vegetation-Atmosphere Interaction, Climatic and Environmental Research, 2, 199–209, https://doi.org/10.3878/j.issn.1006-9585.1997.03.01, 1997.
Ma, N. and Zhang, Y.: Increasing Tibetan Plateau terrestrial evapotranspiration primarily driven by precipitation, Agricultural and Forest Meteorology, 317, 108887, https://doi.org/10.1016/j.agrformet.2022.108887, 2022.
Ma, Y., Fan, S., Ishikawa, H., Tsukamoto, O., Yao, T., Koike, T., Zuo, H., Hu, Z., and Su, Z.: Diurnal and inter-monthly variation of land surface heat fluxes over the central Tibetan Plateau area, Theoretical and Applied Climatology, 80, 259–273, https://doi.org/10.1007/s00704-004-0104-1, 2005.
Ma, Y., Kang, S., Zhu, L., Xu, B., Tian, L., and Yao, T.: Tibetan observation and research platform: Atmosphere-Land Interaction over a Heterogeneous Landscape, Bulletin of the American Meteorological Society, 89, 1487–1492, 2008.
Ma, Y., Wang, Y., and Han, C.: Regionalization of land surface heat fluxes over the heterogeneous landscape: from the Tibetan Plateau to the Third Pole region, International Journal of Remote Sensing, 39, 5872–5890, https://doi.org/10.1080/01431161.2018.1508923, 2018.
Ma, Y., Hu, Z., Xie, Z., Ma, W., Wang, B., Chen, X., Li, M., Zhong, L., Sun, F., Gu, L., Han, C., Zhang, L., Liu, X., Ding, Z., Sun, G., Wang, S., Wang, Y., and Wang, Z.: A long-term (2005–2016) dataset of hourly integrated land–atmosphere interaction observations on the Tibetan Plateau, Earth Syst. Sci. Data, 12, 2937–2957, https://doi.org/10.5194/essd-12-2937-2020, 2020.
Ma, Y., Yao, T., Zhong, L., Wang, B., Xu, X., Hu, Z., Ma, W., Sun, F., Han, C., Li, M., Chen, X., Wang, J., Li, Y., Gu, L., Xie, Z., Liu, L., Sun, G., Wang, S., Zhou, D., Zuo, H., and Wang, Z.: Comprehensive study of energy and water exchange over the Tibetan Plateau: A review and perspective: From GAME/Tibet and CAMP/Tibet to TORP, TPEORP, and TPEITORP, Earth-Science Reviews, 237, 104312, https://doi.org/10.1016/j.earscirev.2023.104312, 2023.
Ma, Y., Xie, Z., Chen, Y., Liu, S., Che, T., Xu, Z., Shang, L., He, X., Meng, X., Ma, W., Xu, B., Zhao, H., Wang, J., Wu, G., and Li, X.: Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau, Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, 2024.
Massman, W. J. and Lee, X.: Eddy covariance flux corrections and uncertainties in long-term studies of carbon and energy exchanges, Agricultural and Forest Meteorology, 113, 121–144, https://doi.org/10.1016/S0168-1923(02)00105-3, 2002.
Mauder, M. and Foken, T.: Impact of post-field data processing on eddy covariance flux estimates and energy balance closure, Meteorologische Zeitschrift, 15, 597–609, https://doi.org/10.1127/0941-2948/2006/0167, 2006.
Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H. P., Schmidt, M., and Steinbrecher, R.: A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements, Agricultural and Forest Meteorology, 169, 122–135, https://doi.org/10.1016/j.agrformet.2012.09.006, 2013.
Mauder, M., Foken, T., and Cuxart, J.: Surface-Energy-Balance Closure over Land: A Review, Boundary-Layer Meteorology, 177, 395–426, https://doi.org/10.1007/s10546-020-00529-6, 2020.
Mills, M. B., Malhi, Y., Ewers, R. M., Kho, L. K., Teh, Y. A., Both, S., Burslem, D. F. R. P., Majalap, N., Nilus, R., Huasco, W. H., Cruz, R., Pillco, M. M., Turner, E. C., Reynolds, G., and Riutta, T.: Tropical forests post-logging are a persistent net carbon source to the atmosphere, Proceedings of the National Academy of Sciences, 120, e2214462120, https://doi.org/10.1073/pnas.2214462120, 2023.
Oku, Y., Ishikawa, H., Haginoya, S., and Ma, Y.: Recent Trends in Land Surface Temperature on the Tibetan Plateau, Journal of Climate, 19, 2995–3003, https://doi.org/10.1175/JCLI3811.1, 2006.
Pan, Y., Birdsey, R. A., Phillips, O. L., Houghton, R. A., Fang, J., Kauppi, P. E., Keith, H., Kurz, W. A., Ito, A., Lewis, S. L., Nabuurs, G. J., Shvidenko, A., Hashimoto, S., Lerink, B., Schepaschenko, D., Castanho, A., and Murdiyarso, D.: The enduring world forest carbon sink, Nature, 631, 563–569, https://doi.org/10.1038/s41586-024-07602-x, 2024.
Qi, Y., Wei, D., Zhao, H., and Wang, X.: Carbon Sink of a Very High Marshland on the Tibetan Plateau, Journal of Geophysical Research: Biogeosciences, 126, e2020JG006235, https://doi.org/10.1029/2020JG006235, 2021.
Santanello Jr., J. A., Dirmeyer, P. A., Ferguson, C. R., Findell, K. L., Tawfik, A. B., Berg, A., Ek, M., Gentine, P., Guillod, B. P., van Heerwaarden, C., Roundy, J., and Wulfmeyer, V.: Land–Atmosphere Interactions: The LoCo Perspective, Bulletin of the American Meteorological Society, 99, 1253–1272, https://doi.org/10.1175/BAMS-D-17-0001.1, 2018.
Sellers, P., Hall, F., Margolis, H., Kelly, B., Baldocchi, D., den Hartog, G., Cihlar, J., Ryan, M. G., Goodison, B., Crill, P., Ranson, K. J., Lettenmaier, D., and Wickland, D. E.: The Boreal Ecosystem–Atmosphere Study (BOREAS): An Overview and Early Results from the 1994 Field Year, Bulletin of the American Meteorological Society, 76, 1549–1577, https://doi.org/10.1175/1520-0477(1995)076<1549:TBESAO>2.0.CO;2, 1995.
Sellers, P. J., Hall, F. G., Asrar, G., Strebel, D. E., and Murphy, R. E.: An overview of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), Journal of Geophysical Research: Atmospheres, 97, 18345–18371, https://doi.org/10.1029/92JD02111, 1992.
Seo, Y.-W. and Ha, K.-J.: Changes in land–atmosphere coupling increase compound drought and heatwaves over northern East Asia, npj Climate and Atmospheric Science, 5, 100, https://doi.org/10.1038/s41612-022-00325-8, 2022.
Suni, T., Guenther, A., Hansson, H. C., Kulmala, M., Andreae, M. O., Arneth, A., Artaxo, P., Blyth, E., Brus, M., Ganzeveld, L., Kabat, P., de Noblet-Ducoudré, N., Reichstein, M., Reissell, A., Rosenfeld, D., and Seneviratne, S.: The significance of land–atmosphere interactions in the Earth system – iLEAPS achievements and perspectives, Anthropocene, 12, 69–84, https://doi.org/10.1016/j.ancene.2015.12.001, 2015.
Turetsky, M. R., Abbott, B. W., Jones, M. C., Anthony, K. W., Olefeldt, D., Schuur, E. A. G., Grosse, G., Kuhry, P., Hugelius, G., Koven, C., Lawrence, D. M., Gibson, C., Sannel, A. B. K., and McGuire, A. D.: Carbon release through abrupt permafrost thaw, Nature Geoscience, 13, 138–143, https://doi.org/10.1038/s41561-019-0526-0, 2020.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R., Meyers, T. P., Prueger, J. H., Starks, P. J., and Wesely, M. L.: Correcting eddy-covariance flux underestimates over a grassland, Agricultural and Forest Meteorology, 103, 279–300, https://doi.org/10.1016/S0168-1923(00)00123-4, 2000.
Wang, B. and Ma, Y.: Meteorological variables and eddy fluxes at 15 land–atmosphere interaction stations over the Tibetan Plateau (May 2021 to July 2023), National Tibetan Plateau/Third Pole Environment Data Center [data set], https://doi.org/10.11888/Atmos.tpdc.302428, 2025.
Wang, B., Ma, Y., Ma, W., and Su, Z.: Physical controls on half-hourly, daily, and monthly turbulent flux and energy budget over a high-altitude small lake on the Tibetan Plateau, Journal of Geophysical Research: Atmospheres, 122, 2289–2303, https://doi.org/10.1002/2016JD026109, 2017.
Wang, S. and Ma, Y.: Characteristics of Land-Atmosphere Interaction Parameters over the Tibetan Plateau, Journal of Hydrometeorology, 12, 702–708, https://doi.org/10.1175/2010JHM1275.1, 2011.
Wang, Y., Xiao, J., Ma, Y., Luo, Y., Hu, Z., Li, F., Li, Y., Gu, L., Li, Z., and Yuan, L.: Carbon fluxes and environmental controls across different alpine grassland types on the Tibetan Plateau, Agricultural and Forest Meteorology, 311, 108694, https://doi.org/10.1016/j.agrformet.2021.108694, 2021.
Wang, Y., Xiao, J., Ma, Y., Ding, J., Chen, X., Ding, Z., and Luo, Y.: Persistent and enhanced carbon sequestration capacity of alpine grasslands on Earth's Third Pole, Science Advances, 9, https://doi.org/10.1126/sciadv.ade6875, 2023.
Wei, D., Qi, Y., Ma, Y., Wang, X., Ma, W., Gao, T., Huang, L., Zhao, H., Zhang, J., and Wang, X.: Plant uptake of CO2 outpaces losses from permafrost and plant respiration on the Tibetan Plateau, Proceedings of the National Academy of Sciences, 118, e2015283118, https://doi.org/10.1073/pnas.2015283118, 2021.
Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier, P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom, A., Law, B. E., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R., Oechel, W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at FLUXNET sites, Agricultural and Forest Meteorology, 113, 223–243, https://doi.org/10.1016/S0168-1923(02)00109-0, 2002.
Wu, G. and Zhang, Y.: Tibetan Plateau Forcing and the Timing of the Monsoon Onset over South Asia and the South China Sea, Monthly Weather Review, 126, 913–927, https://doi.org/10.1175/1520-0493(1998)126<0913:TPFATT>2.0.CO;2, 1998.
Wu, G., Zhou, X., Xu, X., Huang, J., Duan, A., Yang, S., Hu, W., Ma, Y., Liu, Y., Bian, J., Fu, Y., Yang, H., Zhao, P., Zhong, L., and Ma, W.: An Integrated Research Plan for the Tibetan Plateau Land–Air Coupled System and Its Impacts on the Global Climate, Bulletin of the American Meteorological Society, 104, E158–E177, https://doi.org/10.1175/BAMS-D-21-0293.1, 2023.
Wutzler, T., Lucas-Moffat, A., Migliavacca, M., Knauer, J., Sickel, K., Šigut, L., Menzer, O., and Reichstein, M.: Basic and extensible post-processing of eddy covariance flux data with REddyProc, Biogeosciences, 15, 5015–5030, https://doi.org/10.5194/bg-15-5015-2018, 2018.
Xie, Z., Wang, L., Jia, B., and Yuan, X.: Measuring and modeling the impact of a severe drought on terrestrial ecosystem CO2 and water fluxes in a subtropical forest, Journal of Geophysical Research: Biogeosciences, 121, 2576–2587, https://doi.org/10.1002/2016JG003437, 2016.
Xu, X. and Chen, L.: Advances of the Study on Tibetan Plateau Experiment of Atmospheric Sciences, Journal of Applied Meteorological Science, 17, 756–772, https://doi.org/10.11898/1001-7313.20060613, 2006.
Yang, K., Koike, T., Ishikawa, H., Kim, J., Li, X., Liu, H., Liu, S., Ma, Y., and Wang, J.: Turbulent Flux Transfer over Bare-Soil Surfaces: Characteristics and Parameterization, Journal of Applied Meteorology and Climatology, 47, 276–290, https://doi.org/10.1175/2007JAMC1547.1, 2008.
Yang, K., Chen, Y., Lazhu, Zhan, C., Ling, X., Zhou, X., Jiang, Y., Yao, X., Lu, H., Ma, X., Ouyang, L., Pan, W., Ren, Y., Shao, C., Tian, J., Wang, Y., Yang, H., Yue, S., Zhang, K., Zhao, D., Zhao, L., Zhou, J., and Zou, M.: Cross-sectional rainfall observation on the central-western Tibetan Plateau in the warm season: System design and preliminary results, Science China Earth Sciences, 66, 1015–1030, https://doi.org/10.1007/s11430-022-1081-4, 2023.
Yao, N., Ma, Y., Wang, B., Zou, J., Sun, J., and Xie, Z.: A comparative study of the land–atmosphere energy and water exchanges over the Tibetan Plateau and the Yangtze River Region, Atmospheric and Oceanic Science Letters, 17, 100447, https://doi.org/10.1016/j.aosl.2023.100447, 2024.
Ye, D. and Wu, G.: The role of the heat source of the Tibetan Plateau in the general circulation, Meteorology and Atmospheric Physics, 67, 181–198, https://doi.org/10.1007/BF01277509, 1998.
Yu, G., Chen, Z., and Wang, Y.: Carbon, water and energy fluxes of terrestrial ecosystems in China, Agricultural and Forest Meteorology, 346, 109890, https://doi.org/10.1016/j.agrformet.2024.109890, 2024.
Yuan, L., Ma, Y., Chen, X., Wang, Y., and Li, Z.: An Enhanced MOD16 Evapotranspiration Model for the Tibetan Plateau During the Unfrozen Season, Journal of Geophysical Research: Atmospheres, 126, https://doi.org/10.1029/2020JD032787, 2021.
Yuan, L., Chen, X., Ma, Y., Han, C., Wang, B., and Ma, W.: Long-term monthly 0.05° terrestrial evapotranspiration dataset (1982–2018) for the Tibetan Plateau, Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, 2024.
Zhang, C., Qin, D.-H., and Zhai, P.-M.: Amplification of warming on the Tibetan Plateau, Advances in Climate Change Research, 14, 493–501, https://doi.org/10.1016/j.accre.2023.07.004, 2023.
Zhang, Y., Wagner, N., Goergen, K., and Kollet, S.: Summer evapotranspiration-cloud feedbacks in land–atmosphere interactions over Europe, Climate Dynamics, 62, 10767–10783, https://doi.org/10.1007/s00382-024-07475-w, 2024.
Zhao, L., Li, Y., Zhao, X., Xu, S., Tang, Y., Yu, G., Gu, S., Du, M., and Wang, Q.: Comparative study of the net exchange of CO2 in 3 types of vegetation ecosystems on the Qinghai-Tibetan Plateau, Chinese Science Bulletin, 50, 1767–1774, https://doi.org/10.1360/04wd0316, 2005.
Zhong, L., Ma, Y., Hu, Z., Fu, Y., Hu, Y., Wang, X., Cheng, M., and Ge, N.: Estimation of hourly land surface heat fluxes over the Tibetan Plateau by the combined use of geostationary and polar-orbiting satellites, Atmos. Chem. Phys., 19, 5529–5541, https://doi.org/10.5194/acp-19-5529-2019, 2019.
Zhu, L., Meng, Z., Zhang, F., and Markowski, P. M.: The influence of sea- and land-breeze circulations on the diurnal variability in precipitation over a tropical island, Atmos. Chem. Phys., 17, 13213–13232, https://doi.org/10.5194/acp-17-13213-2017, 2017.
Short summary
This study reveals distinct patterns in water, heat, and carbon exchange over the Tibetan Plateau. Heat transfer peaks in spring, while water vapor release is highest in summer. Most stations act as carbon sinks, but one in a forested valley is a carbon source, likely due to vegetation loss and human activity. The findings highlight the strong connections between water, heat, and carbon fluxes, offering valuable insights into climate change and weather forecasting.
This study reveals distinct patterns in water, heat, and carbon exchange over the Tibetan...
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