Publications

75. Ma, N., Zhang, Y., Szilagyi, J. 2024. Water-balance-based evapotranspiration for 56 large river basins: A benchmarking dataset for global terrestrial evapotranspiration modeling. Journal of Hydrology, 630, 130607, doi: 10.1016/j.jhydrol.2024.130607 [Data]

74. Zhang, K., Chen, H., Ma, N., Shang, S., Wang, Y., Xu, Q., Zhu, G. 2024. A global dataset of terrestrial evapotranspiration and soil moisture dynamics from 1982 to 2020. Scientific Data, In press.

73. Liu, C., Feng, S., Zhang, Q., Hu, J., Ma, N., Ci, H., Kong, D., Gu, X. 2024. Critical influence of vegetation response to rising CO2 on runoff changes. Science of the Total Environment, 906, 167717, doi: 10.1016/j.scitotenv.2023.167717

72. Cao, Y., Zhang, Y., Tian, J., Li, X., Tang, Z., Yang, X., Zhang, X., Ma, N. 2024. Strong Agricultural Resilience to 2022 Southern China Drought. Earth's Future, 12, e2023EF004243, doi: 10.1029/2023EF004243

71. Zhang, Y., Li, C., Chiew, F. H. S., Post, D. A., Zhang, X., Ma, N., Tian, J., Kong, D., Leung, R., Yu, Q., Shi, J., Liu, C. 2023. Southern Hemisphere dominates recent decline in global water availability. Science, 382, 579-584, doi: 10.1126/science.adh07166

70. Ma, N. 2023. Modeling land-atmosphere energy and water exchanges in the typical alpine grassland in Tibetan Plateau using Noah-MP. Journal of Hydrology: Regional Studies, 50, 101596, doi: 10.1016/j.ejrh.2023.101596

69. Wang, L., Zhang, Y., Ma, N., Song, P., Tian, J., Zhang, X., Xu, Z. 2023. Diverse responses of canopy conductance to heatwaves. Agricultural and Forest Meteorology, 335, 109453, doi: 10.1016/j.agrformet.2023.109453

68. Shao, X., Zhang, Y., Ma, N., Zhang, X., Tian, J., Liu, C. 2023. Flood Increase and Drought Mitigation Under a Warming Climate in the Southern Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 128, e2022JD037835, doi: 10.1029/2022JD037835

67. Li, X., Zhang, Y., Ma, N., Zhang, X., Tian, J., Zhang, L., McVicar, T. R., Wang, E., Xu, J. 2023. Increased grain crop production intensifies the water crisis in Northern China. Earth's Future, 11, e2023EF003608, doi: 10.1029/2023EF003608

66. Li, C., Yu, Q., Zhang, Y., Ma, N., Tian, J., Zhang, X. 2023. Dominant drivers for terrestrial water storage changes are different in northern and southern China. Journal of Geophysical Research: Atmospheres, 128, e2022JD038074, doi: 10.1029/2022JD038074

65. Luan, J., Zhang, Y., Li, X., Ma, N., Shaid, N., Xu, Z., He, S., Miao, P., Tian, X., Wang, R. 2023. Unexpected consequences of large-scale ecological restoration: Groundwater declines are reversed. Ecological Indicators, 155, 111008, doi: 10.1016/j.ecolind.2023.111008

64. Faiz, M. A., Zhang, Y., Tian, X., Zhang, X., Ma, N., Aryal, S., Naz, F. 2023. Time series analysis for droughts characteristics response to propagation. International Journal of Climatology, 43,1561-1575, doi: 10.1002/joc.79338

63. Qiao, B., Ma, N., Wang, H., Ma, Y., Xiang, L. 2023. Application of satellite gravimetry in terrestrial water storage change. Frontiers in Earth Science, 11, doi: 10.3389/feart.2023.1235259

62. Ma, N., Zhang, Y. 2022. Increasing Tibetan Plateau terrestrial evapotranspiration primarily driven by precipitation. Agricultural and Forest Meteorology, 317, 108887, doi: 10.1016/j.agrformet.2022.108887 [Data] [News in IGSNRR] [ESI Top 1% Highly Cited Paper]

61. Ma, N., Zhang, Y. 2022. Contrasting trends in water use efficiency of the alpine grassland in Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 127(14), e2022JD036919, doi: 10.1029/2022JD036919 [News in CAS]

60. Yan, D., Ma, N.*, Zhang, Y.* 2022. Development of a fine-resolution snow depth product based on the snow cover probability for the Tibetan Plateau: Validation and spatial-temporal analyses. Journal of Hydrology, 604, 127027, doi: 10.1016/j.jhydrol.2021.127027 [Data]

59. Wang, K., Ma, N.*, Zhang, Y.*, Qiang, Y., Guo, Y. 2022. Evapotranspiration and energy partitioning of a typical alpine wetland in the central Tibetan Plateau. Atmospheric Research, 267, 105931. doi: 10.1016/j.atmosres.2021.105931

58. Shao, X., Zhang, Y.*, Liu, C., Chiew, F H S, Tian, J., Ma, N.*, Zhang, X. 2022. Can indirect evaluation methods and their fusion products reduce uncertainty in actual evapotranspiration estimates? Water Resources Research, 58(6), e2021WR031069, doi: 10.1029/2021WR031069

57. Szilagyi, J., Ma, N., Crago, R., Qualls, R. 2022. Power‐function expansion of the polynomial complementary relationship of evaporation. Water Resources Research, 58, e2022WR033095, doi: 10.1029/2022WR033095

56. Huang, Q., Ma, N., Wang, P. 2022. Faster increase in evapotranspiration in permafrost-dominated basins in the warming Pan-Arctic. Journal of Hydrology, 615, 128678, doi: 10.1016/j.jhydrol.2022.128678

55. He, S., Zhang, Y., Ma, N., Tian, J., Kong, D., Liu, C. 2022. A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020. Earth System Science Data, 14, 5463-5488, doi: 10.5194/essd-2022-183

54. Huang, Q., Zhang, Y., Ma, N., Post, D. 2022. Estimating vegetation greening influences on runoff signatures using a log-based weighted ensemble method. Water Resources Research, 58, e2022WR032492, doi: 10.1029/2022WR032492

53. Guo, Y., Zhang, Y., Ma, N., Wang, T., Yang, D. 2022. Significant CO2 sink over the Tibet's largest lake: Implication for carbon neutrality across the Tibetan Plateau. Science of the Total Environment, 843, 156792, doi: 10.1016/j.scitotenv.2022.156792

52. Zhang, K., Zhu, G., Ma, N., Chen, H., Shang, S. 2022. Improvement of evapotranspiration simulation in a physically based ecohydrological model for the groundwater–soil–plant–atmosphere continuum. Journal of Hydrology, 613, 128440, doi: 10.1016/j.jhydrol.2022.128440

51. Xu, Z., Zhang, Y., Zhang, X., Ma, N., Tian, J., Kong, D., Post, D. 2022. Bushfire-induced water balance changes detected by a modified paired catchment method. Water Resources Research, 58, doi: 10.1029/e2021WR031013

50. Luan, J., Miao, P., Tian, X., Li, X., Ma, N., Xu, Z., Wang, H., Zhang, Y., 2022. Separating the impact of check dams on runoff from climate and vegetation changes. Journal of Hydrology, 614, 128565, doi: 10.1016/j.jhydrol.2022.128565

49. Meresa, H., Zhang, Y., Tian, J., Ma, N., Zhang, X., Heidari, H., Naeem, S. 2022. An integrated modeling framework in projections of hydrological extremes. Surveys in Geophysics, 43, doi: 10.1007/s10712-022-09737-w

48. Tian, J., Zhang, Y., Guo, J., Zhang, X., Ma, N., Wei, H., Tang, Z. 2022. Predicting root zone soil moisture using observations at 2121 sites across China. Science of the Total Environment, 847, 157425, doi: 10.1016/j.scitotenv.2022.157425

47. Faiz, M. A., Zhang, Y., Tian, X., Tian, J., Zhang, X., Ma, N., Aryal, S. 2022. Drought index revisited to assess its response to vegetation in different agro-climatic zones. Journal of Hydrology, 614, 128543, doi: 10.1016/j.jhydrol.2022.128543

46. Tang, Z., Tian, J., Zhang, Y., Zhang, X., Zhang, J., Ma, N., Li, X., Song, P. 2022. Anthropogenic aerosols dominated the decreased solar radiation in eastern China over the last five decades. Journal of Cleaner Production, 380, 135150, doi: 10.1016/j.jclepro.2022.135150

45. Zhang, X., Zhang, Y., Tian, J., Ma, N., Wang, Y-P., 2022. CO2 fertilization is spatially distinct from stomatal conductance reduction in controlling ecosystem water-use efficiency increase. Environmental Research Letters, 17, 054048, doi: 10.1088/1748-9326/ac6c9c

44. Luan. J, Miao, P., Tian, X., Li, X., Ma, N., Faiz, M. A., Xu, Z., Zhang, Y. 2022. Estimating hydrological consequences of vegetation greening. Journal of Hydrology, 611, 128018, doi: 10.1016/j.jhydrol.2022.128018

43. Shang, C., Wu, T., Ma, N., Wang, J., Li, X., Zhu, X., Wang, T., Hu, G., Li, R., Yang, S., Chen, J., Yao, J., Yang, C. 2022. Assessment of different complementary-relationship-based models for estimating actual terrestrial evapotranspiration in the frozen ground regions of the Qinghai-Tibet Plateau. Remote Sensing, 14(9), 2047, doi: 10.3390/rs14092047

42. Faiz, M. A., Zhang, Y., Zhang, X., Ma, N., Aryal, S., Ha, T. T. V., Baig, F., Naz, F. 2022. A composite drought index developed for detecting large-scale drought characteristics. Journal of Hydrology, 605, 127308, doi: 10.1016/j.jhydrol.2021.127308

41. Liu, Y., Qiu, G., Zhang, H., Yang, Y., Zhang, Y., Wang, Q., Zhao, W., Jia, L., Ji, X., Xiong, Y., Yan, C., Ma, N., Han, S., Cui, Y. 2022. Shifting from homogeneous to heterogeneous surfaces in estimating terrestrial evapotranspiration: Review and perspectives. Science China Earth Science, 65(2), 197-214. doi: 10.1007/s11430-020-9834-y

40. Zhang, Z., Arnault, J., Laux, P., Ma, N., Wei, J., Shang, S., Kunstmann, H. 2022. Convection-permitting fully coupled WRF-Hydro ensemble simulations in high mountain environment: impact of boundary layer- and lateral flow parameterizations on land–atmosphere interactions. Climate Dynamics, 59, 1355-1376. doi: 10.1007/s00382-021-06044-9

39. Ma, N., Szilagyi, J., Zhang, Y. 2021. Calibration-free complementary relationship estimates terrestrial evapotranspiration globally. Water Resources Research, 57, e2021WR029691, doi: 10.1029/2021WR029691 [Data] [WRR Top Cited Article during 2021-2022]

38. Zhang, X., Zhang, Y., Ma, N., Kong, D., Tian, J., Shao, X., Tang, Q. 2021. Greening-induced increase in evapotranspiration over Eurasia offset by CO2-induced vegetational stomatal closure. Environmental Research Letters, 16, 124008, doi: 10.1088/1748-9326/ac3532

37. Zhang, Z., Arnault, J., Laux, P., Ma, N., Wei, J., Kunstmann, H. 2021. Diurnal cycle of surface energy fluxes in high mountain terrain: High-resolution fully coupled atmosphere-hydrology modelling and impact of lateral flow. Hydrological Processes, 35(12), e14454, doi: 10.1002/hyp.14454

36. Luan, J., Zhang, Y., Ma, N., Tian, J., Li, X., Liu, D. 2021. Evaluating the uncertainty of eight approaches for separating the impacts of climate change and human activities on streamflow. Journal of Hydrology, 601, 126605, doi: 10.1016/j.jhydrol.2021.126605

35. Faiz, M. A., Zhang, Y., Ma, N., Baig, F., Naz, F., Niaz, Y. 2021. Drought indices: aggregation is necessary or is it only the researcher’s choice? Water Supply, 21, doi: 10.2166/ws.2021.163

34. Wang, P., Huang, Q., Pozdniakov, S., Liu, S., Ma, N., Wang, T., Zhang, Y., Yu, J., Xie, J., Fu, G., Frolova, N., Liu, C. 2021. Potential role of permafrost thaw on increasing Siberian river discharge. Environmental Research Letters, 16, 034046, doi: 10.1088/1748-9326/abe326

33. Paul, P. K., Zhang, Y., Ma, N., Mishra, A., Panigraphy, N., Singh, R. 2021. Selecting hydrological models for developing countries: Perspective of global, continental, and country scale models over catchment scale models. Journal of Hydrology, 600, doi: 10.1016/j.jhydrol.2021.126561

32. Li, X., Zhang, Y., Ma, N., Li, C., Luan, J. 2021. Contrasting effects of climate and LULC change on blue water resources at varying temporal and spatial scales. Science of the Total Environment, 786, 147488, doi: 10.1016/j.scitotenv.2021.147488

31. Wang, T., Wang, P., Wang, Z., Niu, G-Y., Yu, J., Ma, N., Wu, Z., Pozdniakov, S., Yan, D. 2021. Drought adaptability of phreatophytes: Insight from vertical root distribution in drylands of China. Journal of Plant Ecology, 14, doi: 10.1093/jpe/rtab059

30. Zou, X., Gao, H., Zhang, Y., Ma, N., Wu, J., Farhan, S. 2021. Quantifying ice storage in upper Indus river basin using ground‐penetrating radar measurements and glacier bed topography model version 2. Hydrological Processes, 35(4), e14145, doi: 10.1002/hyp.14145

29. Ma, N., Yu, K., Zhang, Y., Zhai, J., Zhang, Y., Zhang, H. 2020. Ground observed climatology and trend in snow cover phenology across China with consideration of snow-free breaks. Climate Dynamics, 55, 2867-2887. doi: 10.1007/s00382-020-05422-z

28. Ma, N., Szilagyi, J., Jozsa, J. 2020. Benchmarking large-scale evapotranspiration estimates: A perspective from a calibration-free complementary relationship approach and FLUXCOM. Journal of Hydrology, 590, 125221, doi: 10.1016/j.jhydrol.2020.125221

27. Yan, D., Huang, C., Ma, N.*, Zhang, Y. 2020. Improved Landsat-based water and snow indexes for extracting lake and snow cover/glacier in the Tibetan Plateau. Water, 12(5), doi: 10.3390/w12051339

26. Szilagyi, J., Crago, R., Ma, N. 2020. Dynamic scaling of the generalized complementary relationship (GCR) improves long-term tendency estimates in land evaporation. Advances in Atmospheric Sciences, 37(9), 975-986. doi: 10.1007/s00376-020-0079-6

25. Wang, K., Zhang, Y., Ma, N., Guo, Y., Qiang, Y. 2020. Cryosphere evapotranspiration in the Tibetan Plateau: A review. Sciences in Cold and Arid Regions, 12(6), 355-370. doi: 10.3724/SP.J.1226.2020.00355. [Open Acess]

24. Cui, J., Tian, L., Wei, Z., Huntingford, C., Wang, P., Cai, Z., Ma, N., Wang, L. 2020. Quantifying the controls on evapotranspiration partitioning in the highest alpine meadow ecosystem. Water Resources Research, 56(4). doi: 10.1029/2019WR024815

23. Ma, N., Szilagyi, J. 2019. The CR of evaporation: A calibration-free diagnostic and benchmarking tool for large-scale terrestrial evapotranspiration modeling. Water Resources Research, 55(8), 7246-7274. doi: 10.1029/2019WR024867. [Data]

22. Liu, L., Jiang, L., Jiang, H., Wang, H., Ma, N., Xu, H. 2019. Accelerated glacier mass loss (2011–2016) over the Puruogangri ice field in the inner Tibetan Plateau revealed by bistatic InSAR measurements. Remote Sensing of Environment, 231, doi: 10.1016/j.rse.2019.111241

21. Lei, Y., Zhu, Y., Wang, B., Yao, T., Yang, K., Zhang, X., Zhai, J., Ma, N. 2019. Extreme lake level changes on the Tibetan Plateau associated with the 2015/2016 El Niño. Geophysical Research Letters, 46, 5889-5898. doi: 10.1029/2019GL081946

20. Ma, N., Szilagyi, J., Zhang, Y., Liu, W. 2019. Complementary-relationship-based modeling of terrestrial evapotranspiration across China during 1982-2012: Validations and spatiotemporal analyses. Journal of Geophysical Research: Atmospheres, 124(8), 4326-4351. doi: 10.1029/2018JD029580. [Data] [News in Chinese Academy of Sciences] [News in TPE] [ESI Top 1% Highly Cited Paper]

19. Zhang, T., Zhang, Y., Guo, Y., Ma, N., Dai, D., Song, H., Qu, D., Gao, H. 2019. Controls of stable isotopes in precipitation on the central Tibetan Plateau: A seasonal perspective. Quaternary International, 513, 66-79. doi: 10.1016/j.quaint.2019.03.031

18. Zhu, L.,Wang, J., Ju J., Ma, N., Zhang, Y., Liu, C., Han, Bo, Liu, L., Wang, M., Ma, Q. 2019. Climatic and lake environmental changes in the Serling Co region of Tibet over a variety of timescales. Science Bulletin, 64(7): 422-424. doi: 10.1016/j.scib.2019.02.016

17. Wang, G., Wang, P., Wang, T., Zhang, Y., Yu, J., Ma, N., Frolova, N., Liu, C. 2019. Contrasting changes in vegetation growth due to different climate forcings over the last three decades in the Selenga-Baikal Basin. Remote Sensing, 11(4), 426. doi:10.3390/rs11040426. [Open Acess]

16. Guo, Y., Zhang, Y., Ma, N., Xu, J., Zhang, T. 2019. Long-term changes in evaporation over Siling Co Lake on the Tibetan Plateau and its impact on recent rapid lake expansion. Atmospheric Research, 216, 141-150. doi: 10.1016/j.atmosres.2018.10.006

15. Zhang, H., Zhang, F., Zhang, G., Che, T., Yan, W., Ye, M., Ma, N. 2019. Ground-based evaluation of MODIS snowcover product V6 across China: Implications for the selection of NDSI threshold. Science of the Total Environment, 651, 2172-2726. doi: 10.1016/j.scitotenv.2018.10.128

14. Ding, J., Zhang, Y., Guo, Y., Ma, N., 2018. Quantitative comparison of river inflows to a rapidly expanding lake in central Tibetan Plateau. Hydrological Processes, 32, 3241-3253. doi: 10.1002/hyp.13239

13. Zhang, Y., Ma, N.*, 2018. Spatiotemporal variability of snow cover and snow water equivalent in the last three decades over Eurasia. Journal of Hydrology, 559, 238-251, doi: 10.1016/j.jhydrol.2018.02.031.

12. Ma, N., Niu, G-Y., Xia, Y., Cai, X., Zhang, Y., Ma, Y., Fang, Y. 2017. A systematic evaluation of Noah-MP in simulating land-atmosphere energy, water and carbon exchanges over the continental United States. Journal of Geophysical Research: Atmospheres,122(22), 12245-12268. doi: 10.1002/2017JD027597.

11. Ebrahimi, S., Chen, C., Chen, Q., Zhang, Y., Ma, N., Zaman, Q., 2017. Effects of temporal scales and space mismatches on the TRMM 3B42 v7 precipitation product in a remote mountainous area. Hydrological Processes, 31, 4315-4327. doi: 10.1002/hyp.11357.

10. Ma, N., Zhang, Y., 2017. Comment on “Rescaling the complementary relationship for land surface evaporation” by R. Crago et al. Water Resources Research, 53, 6340-6342. doi: 10.1002/2017WR020892.

9. Ma, N., Szilagyi, J., Niu, G-Y., Zhang, Y., Zhang, T., Wang, B., Wu, Y., 2016. Evaporation variability of Nam Co Lake in the Tibetan Plateau and its role in recent rapid lake expansion. Journal of Hydrology, 537, 27-35. doi:10.1016/j.jhydrol.2016.03.030. [News in GlacierHub] [News in UNL]

8. Guo, Y., Zhang, Y., Ma, N., Song, H., Gao, H., 2016. Quantifying surface energy fluxes and evaporation over a significant expanding endorheic lake in the central Tibetan Plateau. Journal of the Meteorological Society of Japan, 94(5), 453-465. doi: 10.2151/jmsj.2016-023

7. Dong, C., Wang, N., Chen, J., Li, Z., Chen, H., Chen, L., Ma, N., 2016. New observational and experimental evidence for the recharge mechanism of the lake group in the Alxa Desert, north-central China. Journal of Arid Environments, 124, 48-61. doi: 10.1016/j.jaridenv.2015.07.008

6. Ma, N., Zhang, Y., Guo, Y., Gao, H., Zhang, H., Wang, Y., 2015. Environmental and biophysical controls on the evapotranspiration over the highest alpine steppe. Journal of Hydrology, 529, 980-992. doi: 10.1016/j.jhydrol.2015.09.013

5. Ma, N., Zhang, Y., Xu, C., Szilagyi, J., 2015. Modeling actual evapotranspiration with routine meteorological variables in the data-scarce region of the Tibetan Plateau: Comparisons and implications. Journal of Geophysical Research: Biogeosciences, 120, 1638-1657. doi: 10.1002/2015JG003006 [Ten Most Accessed Paper of JGR-Biogeosci (Rank 9) during the first three months (Aug to Nov, 2015) since published]

4. Ma, N., Zhang, Y., Szilagyi, J., Guo, Y., Zhai, J., Gao, H., 2015. Evaluating the complementary relationship of evapotranspiration in the alpine steppe of the Tibetan Plateau. Water Resources Research, 51, 1069-1083. doi: 10.1002/2014WR015493 [News in Chinese Academy of Sciences] [News in Jinritoutiao]

3. Farhan, S., Zhang, Y., Ma, Y., Guo, Y., Ma, N., 2015. Hydrological regimes under the conjunction of westerly and monsoon climates: A case investigation in the Astore Baisn, Northwestern Himalaya. Climate Dynamics, 44, 3015-3032. doi: 10.1007/s00382-014-2409-9

2. Ma, N., Wang, N., Zhao, L., Zhang, Z., Dong, C., Shen, S., 2014. Observation of mega-dune evaporation after various rain events in the hinterland of Badain Jaran Desert, China. Chinese Science Bulletin, 59(2), 162-170. doi: 10.1007/s11434-013-0050-3

1. Li, Y., Wang, N., Li, Z., Ma, N., Zhou, X., Zhang, C., 2013. Lake evaporation: A possible factor affecting lake level changes tested by modern observational data in arid and semi-arid China. Journal of Geographical Sciences, 23(1), 123-135. doi: 10.1007/s11442-013-0998-6

中文期刊 [Chinese Journals]

9. 刘元波, 邱国玉, 张宏昇, 杨永辉, 张寅生, 王权, 赵文智, 贾立, 吉喜斌, 熊育久, 鄢春华, 马宁, 韩淑敏, 崔逸凡. 2022. 陆域蒸散的测算理论方法：回顾与展望. 中国科学: 地球科学, 52(3): 381–399. doi: 10.1360/SSTe-2020-0342. [PDF]

8. 马宁. 2021. 近40年来青藏高原典型高寒草原和湿地蒸散发变化的对比分析. 地球科学进展, 36(8): 836-848. [PDF]

7. 马宁, 王乃昂. 2016. 巴丹吉林沙漠腹地湖泊水面蒸发模拟的特殊性. 干旱区研究, 33(6), 1141-1149. [PDF]

6. 马宁, 王乃昂, 黄银洲, 李宏宇, 路俊伟. 2015. 巴丹吉林沙漠腹地夏季不同天气条件下陆—湖面辐射收支与能量分配特征对比. 自然资源学报, 30(5): 796–809. [PDF]

5. 马宁, 王乃昂, 赵力强, 张振瑜, 董春雨, 沈士平. 2014. 巴丹吉林沙漠腹地降水事件后的沙山蒸发观测. 科学通报, 59(7): 615-622. [PDF]

4. 王乃昂，马宁*, 陈红宝, 陈秀莲，董春雨，张振瑜. 2013. 巴丹吉林沙漠腹地降水特征初步分析. 水科学进展, 24(2): 153-160. [*通讯作者] [入选"F5000领跑者—中国精品科技期刊顶尖学术论文"]. [PDF]

3. 马宁, 王乃昂, 王鹏龙, 孙彦猛，董春雨. 2012. 黑河流域参考蒸散量的时空变化特征及影响因素的定量分析. 自然资源学报, 27(6): 975-989. [PDF]

2. 马宁, 王乃昂, 朱金峰, 陈秀莲, 陈红宝, 董春雨. 2011. 巴丹吉林沙漠周边地区近50a来气候变化. 中国沙漠, 31(6): 1541-1547. [PDF]

1. 马宁, 王乃昂, 李卓仑, 陈秀莲, 朱金峰, 董春雨. 2011. 1960-2009年巴丹吉林沙漠南北缘气候变化分析. 干旱区研究, 28(2): 242-250. [PDF]