第一作者及通讯作者：

30   Liu D, Wang T*, Pe？uelas J, Piao SL. Drought resistance enhanced by tree species diversity in global forests. Nature Geosciences, 2022, https://doi.org/10.1038/s41561-022-01026-w

29   Wang XY, Wang T*, Xu JF, et al. Enhanced habitat loss of the Himalayan endemic flora driven by warming-forced upslope tree expansion. Nature Ecology & Evolution, 2022, 6, pages890–899

28.  Feng YY, Wang T*, Chen YN, et al. A transition towards an unusually wet condition will not alleviate water scarcity risk in Xinjiang, China. AGU Advances, 2022, 3, e2021AV000589

27.    Wang T*, Zhao Y, Xu C, et al. Atmospheric dynamic constraints on Tibetan Plateau freshwater under Paris climate targets. Nature Climate Change, 2021, 11(3): 219-225.

26.Zhang T,Wang T*, Feng Y, et al. An emerging impact of Eurasian spring snow cover on summer rainfall in eastern China. Environmental Research Letters, 2021, 16(5): 054012.

25.    Zhang T, Wang T*, Zhao Y, et al. Drivers of Eurasian spring snow-cover variability. Journal of Climate, 2021, 34(6): 2037-2052.

24.    Ren S, Ding J*,Wang T*, et al. Higher temperature sensitivity of soil C release to atmosphere from northern permafrost soils as indicated by a meta - analysis. Global Biogeochemical Cycles, 2020, 34(11): e2020GB006688.

23.    Ding J, Wang T*, Piao SL, et al. The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region. Nature communications, 2019, 10(1): 1-9.

22.    Zhang T, Wang T*, Krinner G, et al. The weakening relationship between Eurasian spring snow cover and Indian summer monsoon rainfall. Science advances, 2019, 5(3): eaau8932.

21.    Yang T, Ding J*, Wang T*, et al. Combined use of multiple drought indices for global assessment of dry gets drier and wet gets wetter paradigm. Journal of Climate, 2019, 32(3): 737-748.

20.    Liu D, Wang T*, Yang T, et al. Deciphering impacts of climate extremes on Tibetan grasslands in the last fifteen years. Science Bulletin, 2019, 64(7): 446-454.

19.    Wang X, Wang T*, Liu D*, et al. Multisatellite Analyses of Spatiotemporal Variability in Photosynthetic Activity Over the Tibetan Plateau. Journal of Geophysical Research: Biogeosciences, 2019, 124(12): 3778-3797.

18.    Wang T*, Liu D, Piao SL, et al. Emerging negative impact of warming on summer carbon uptake in northern ecosystems. Nature communications, 2018, 9(1): 1-7.

17.    Wang X, Wang T*, Guo H, et al. Disentangling the mechanisms behind winter snow impact on vegetation activity in northern ecosystems. Global change biology, 2018, 24(4): 1651-1662.

16.    Ding J*, Yang T, Wang T*, et al. Increasingly important role of atmospheric aridity on Tibetan alpine grasslands. Geophysical Research Letters, 2018, 45(6): 2852-2859.

15.    Liu D, Li Y, Wang T*, et al. Contrasting responses of grassland water and carbon exchanges to climate change between Tibetan Plateau and Inner Mongolia. Agricultural and Forest Meteorology, 2018, 249: 163-175.

14.    Yao Y, Li Z, Wang T*, et al. A new estimation of China’s net ecosystem productivity based on eddy covariance measurements and a model tree ensemble approach. Agricultural and forest meteorology, 2018, 253: 84-93.

13.    Guo H, Wang X, Wang T*, et al. Spring snow‐albedo feedback analysis over the Third Pole: results from satellite observation and CMIP5 model simulations. Journal of Geophysical Research: Atmospheres, 2018, 123(2): 750-763.

12.    Wang X, Wang T*, Liu D, et al. Moisture‐induced greening of the South Asia over the past three decades. Global change biology, 2017, 23(11): 4995-5005.

11.    Li J, Wang T*, Li Y*, et al. Grassland restoration reduces water yield in the headstream region of Yangtze River. Scientific reports, 2017, 7(1): 1-9.

10.    Wang T*, Lin X, Liu Y, et al. Causes of uncertainty in China's net primary production over the 21st century projected by the CMIP5 Earth system models. International Journal of Climatology, 2016, 36(5): 2323-2334.

9.   Li Y, Wang T*, Piao SL*, et al. Evaluating biases in simulated land surface albedo from CMIP5 global climate models. Journal of Geophysical Research: Atmospheres, 2016, 121(11): 6178-6190.

8.  Wang T*, Peng S, Ottlé C, et al. Spring snow cover deficit controlled by intraseasonal variability of the surface energy fluxes. Environmental Research Letters, 2015, 10(2): 024018.

7.  Wang T*, Peng S, Krinner G, et al. Impacts of satellite-based snow albedo assimilation on offline and coupled land surface model simulations. PLoS One, 2015, 10(9): e0137275.

6.     Wang T*, Ottlé C, Peng S, et al. The influence of local spring temperature variance on temperature sensitivity of spring phenology. Global Change Biology, 2014, 20(5): 1473-1480.

5.     Wang T*, Lin X, Peng S, et al. Multimodel projections and uncertainties of net ecosystem production in China over the twenty-first century. Chinese science bulletin, 2014, 59(34): 4681-4691.

4.   Wang T*, Peng S, Lin X, et al. Declining snow cover may affect spring phenological trend on the Tibetan Plateau. Proceedings of the National Academy of Sciences, 2013, 110(31): E2854-E2855.

3.    Wang T*, Ottlé C, Boone A, et al. Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model. Journal of Geophysical Research: Atmospheres, 2013, 118(12): 6064-6079.

2.  Wang T*, Brender P*, Ciais P, et al. State-dependent errors in a land surface model across biomes inferred from eddy covariance observations on multiple timescales. Ecological Modelling, 2012, 246: 11-25.

1.     Wang T*, Ciais P, Piao SL, et al. Controls on winter ecosystem respiration in temperate and boreal ecosystems. Biogeosciences, 2011, 8: 2009-2025.