1.个人简介：
姓名：陈铁喜
性别：男
最高学历：博士
职称：教授，博士生导师
职务：青海理工学院生态与环境科学学院院长
南京信息工程大学地理科学学院副院长
青海师范大学地理科学学院副院长
研究方向：从事生态气象交叉领域研究，主要关注气候变化与人类活动对生态系统的影响，以及陆地生态系统碳循环通量估算。
2.联系方式
E-mail: txchen@qhit.edu.cn; txchen@nuist.edu.cn
3.教育背景：
2002年-2006年 本科 南京大学 大气科学学院
2006年-2009年 硕士 南京大学 大气科学学院
2009年-2014年 博士 荷兰阿姆斯特丹自由大学 地球科学系
2013年 访问科学家 NASA GSFC
4.工作经历：
2021年12月至今
青海理工学院（原青海理工大学（筹）） 生态与环境科学学院 院长
2024年3月至今
南京信息工程大学 地理科学学院 副院长
2021年12月至今
青海师范大学地理科学学院 副院长（挂职）
2021年3–12月
南京信息工程大学 雷丁学院 副院长（挂职）
2019年10月–2021年9月
南京信息工程大学 地理科学学院 自然地理系 系主任
2017年7月至今
南京信息工程大学 教授
2014年6月-2017年7月
南京信息工程大学 讲师
5.荣誉奖励：
2019年入选 江苏省双创团队（排名3）
2022年入选 青海省“昆仑英才·高端创新创业人才”计划 杰出人才
6.学术兼职：
青海省高原气候变化及其生态环境效应重点实验室主任
国际水文科学协会中国委员会遥感专业委员会委员（CNC-IAHS-CRS）
青海省遥感学会理事
南京市气象学会理事
《应用生态学报》、《干旱气象》编委等
7. 科研项目：
[1].利用涡度通量观测与光能利用率模型估算全球农田初级生产力
国家自然科学基金面上项目 主持 2016年至2019年
[2].京津冀地区高时空分辨率陆地生态系统碳通量模拟
国家重点研发计划子课题 主持 2017年至2021年
[3].环维多利亚湖城市氮磷排放量核算、减量化策略及气候变化影响研究
国家自然科学基金联合重点项目 参与 2022年至2026年
[4].区域水热格局及森林残体与土壤碳氮计量调控土壤有机碳积累的机制
国家自然科学基金重点项目 参与 2022至2026年
8.发表论文 (*通讯作者，#指导学生):
[56]. Xiao, Y.#, Chen, T.*, Chen, X., Yang, Y., Wang, S., & Zhou, S. (2024). CMIP6 ESMs overestimate greening and the photosynt hesis trends in Dryland East Asia. Science of The Total Environment, 173432. https://doi.org/10.1016/j.scitotenv.2024.173432
[55]. Wang, S., Chen, T., Luo, J. J., Gao, M., Zuo, H., Ling, F., ... & Yamagata, T. (2024). Warming climate is helping human beings run faster, jump higher and throw farther through less dense air. npj Climate and Atmospheric Science, 7(1), 94.
[54]. Wang, X., Zhang, N., Chen, K.*, Chen, T.*, Qi, D., Ma, Y., 2024.Response mechanism of soil microorganisms to simulated precipitation in the source wetland of Qinghai Lake. Ecological Process 13, 25. https://doi.org/10.1186/s13717-024-00502-y
[53]. Wang, S., Chen, T., Xie, Y. and Luo, J.J., 2024. Different impacts of the variations of western and eastern portions of the East Asian westerly jet stream on southern China rainfalls in Meiyu season. Atmospheric Research, 300, p.107229. https://doi.org/10.1016/j.atmosres.2024.107229
[52]. Chen, X.#, Chen, T.*, Liu, S., Chai, Y., Guo, R., Dai, J., Wang, S., Zhang, L. and Wei, X., 2024. Vegetation Index‐Based Models Without Meteorological Constraints Underestimate the Impact of Drought on Gross Primary Productivity. Journal of Geophysical Research: Biogeosciences, 129(1), p.e2023JG007499. https://doi.org/10.1029/2023JG007499
(提出仅用植被指数估算GPP的问题，无法有效估算极端事件的影响)
[51]. Chen, T.*, Dai, J., Chen, X., Liang, C., Shi, T., Lyu, Y., Zhao, F., Wu, X., Gao, M., Huang, J. and Zhou, S., 2024. Agricultural land management extends the duration of the impacts of extreme climate events on vegetation in double–cropping systems in the Yangtze–Huai plain China. Ecological Indicators, 158, p.111488. https://doi.org/10.1016/j.ecolind.2023.111488
(首次指出土地管理会影响极端事件对植被影响的时间尺度)
[50]. Chen, X.#, Chen, T.*, He, B., Liu, S., Zhou, S. and Shi, T., 2024. The global greening continues despite increased drought stress since 2000. Global Ecology and Conservation, 49, p.e02791. https://doi.org/10.1016/j.gecco.2023.e02791
[49]. Li, S., Wang, G., Chai, Y., Miao, L., Hagan, D.F.T., Sun, S., Huang, J., Su, B., Jiang, T., Chen, T. and Lu, C., 2023. Increasing vapor pressure deficit accelerates land drying. Journal of Hydrology, 625, p.130062. https://doi.org/10.1016/j.jhydrol.2023.130062
[48]. Wang, S., He, B., Chen, H.W., Chen, D., Chen, Y., Yuan, W., Shi, F., Duan, J., Wu, W., Chen, T. and Guo, L., 2023. Fire carbon emissions over Equatorial Asia reduced by shortened dry seasons. npj Climate and Atmospheric Science, 6(1), p.129. https://doi.org/10.1038/s41612-023-00455-7
[47]. Guo, R.#, Chen, T.*, Chen, X., Yuan, W., Liu, S., He, B., Li, L., Wang, S., Hu, T., Yan, Q. and Wei, X., 2023. Estimating global GPP from the plant functional type perspective using a machine learning approach. Journal of Geophysical Research: Biogeosciences, 128(4), p.e2022JG007100. https://doi.org/10.1029/2022JG007100
(建立全新的基于机器学习算法的GPP数据集，欢迎下载使用：https://datadryad.org/stash/dataset/doi:10.5061/dryad.dncjsxm2v)
[46]. Yan, Q., Chen, Y., Jin, S., Liu, S., Jia, Y., Zhen, Y., Chen, T.*, Huang, W., 2022. Inland Water Mapping Based on GA-LinkNet from CyGNSS Data. IEEE Geoscience and Remote Sensing Letters. https://doi.org/10.1109/LGRS.2022.3227596
[45]. Hu, T., Wang, T., Yan, Q., Chen, T., Jin, S. and Hu, J., 2022. Modeling the spatiotemporal dynamics of global electric power consumption (1992–2019) by utilizing consistent nighttime light data from DMSP-OLS and NPP-VIIRS. Applied Energy, 322, p.119473. https://doi.org/10.1016/j.apenergy.2022.119473
[44]. Chai, Y., Yue, Y.*, Slater, L. J., Yin, J., Borthwick, A. G., Chen, T., and Wang, G., 2022. Constrained CMIP6 projections indicate less warming and a slower increase in water availability across Asia. Nature communications, 13(1), 1-9. https://doi.org/10.1038/s41467-022-31782-7
[43]. Chen, T.*, Dolman, H., Sun, Z., Gao, H., Miao, L., Wei, X., Li, C., Han, Q., Shi, T., Wang. G., Zhou. S., Liang, C., and Chen. X., 2022. Land management explains the contrasting greening pattern across China-Russia border based on Paired Land Use Experiment approach, JGR-Biogeosciences, 127, e2021JG006659. https://doi.org/10.1029/2021JG006659
(建立PLUE方法，识别土地管理对植被变化的影响)
[42]. Zhou, S.#, Chen, T.*, Zeng, N., Cai, Q.*, Fang Zhao, F., Han, P., and Yan. Q., 2022. The Impact of Cropland Abandonment of Post-Soviet Countries on the Terrestrial Carbon Cycle Based on Optimizing the Cropland Distribution Map, Biology, 11, no. 5: 620. https://doi.org/10.3390/biology11050620
[41]. Chen, T.*, Guo, R., Yan, Q., Xin Chen, Zhou, S., Chen, X., Liang, C., Wei, X., and Dolman, H., 2022. Land Management Contributes significantly to observed Vegetation Browning in Syria during 2001–2018, Biogeosciences, 19, 1515–1525. https://doi.org/10.5194/bg-19-1515-2022
(叙利亚社会动荡引发的土地管理能力退化导致了褐变现象)
[40]. Wei, X., Ye, Y., Li, B. and Chen, T., 2022. Reconstructing cropland change since 1650 AD in Shaanxi province, central China. Quaternary International, 641, pp.74-86.
[39]. 张林林,梁传壮,马海云,陈鑫,蔡江涛,郭仁杰,陈铁喜*. 2022. 土地管理对植被变绿的潜在贡献——以中国东北农业区为例[J]. 生态学报, 42(02):720-731. http://dx.doi.org/10.5846/stxb202011192977
[38]. Chen, S., Yan, Q., Jin, S., Huang, W., Chen, T., Jia, Y., Liu, S. and Cao, Q., 2022. Soil Moisture Retrieval from the CyGNSS Data Based on a Bilinear Regression. Remote Sensing, 14(9), p.1961. https://doi.org/10.3390/rs14091961
[37]. Cai, J., Chen, T.*, Yan, Q., Chen, X., and Guo, R., 2022. The Spatial-Temporal Characteristics of Soil Moisture and Its Persistence over Australia in the Last 20 Years. Water, 14(4), 598. https://doi.org/10.3390/w14040598
[36]. Xie, Y., Su, Y., Gu, X., Chen, T., Shao, W., and Hu, Q., 2022. Columnar Aerosol Optical Property Characterization and Aerosol Typing Based on Ground-Based Observations in a Rural Site in the Central Yangtze River Delta Region. Remote Sensing, 14(2), 406. https://doi.org/10.3390/rs14020406
[35]. Chen, X.#, Chen, T.*, Shu, Y.*, Yan, Q., Han, Q., Wei, X., Li, C., Wang, G. and Xie, Y., 2021. A framework to assess the potential uncertainties of three FPAR products. Journal of Geophysical Research: Biogeosciences, 126(10), p.e2021JG006320. https://doi.org/10.1029/2021JG006320
[34]. Wei, X., Li, Y., Guo, Y., Chen, T., and Li, B., 2021. Spatio-temporal analysis of cropland change in the Guanzhong area, China, from 1650 to 2016. Journal of Geographical Sciences, 31(9), 1381-1400. https://doi.org/10.1007/s11442-021-1902-4
[33]. 蔡江涛,陈铁喜,姜建武,胡垚,潘文宇. 2021. 基于空间点模式的桂林市星级酒店空间分布特征研究[J].福建师范大学学报(自然科学版), 37(04):77-86. https://doi.org/10.12046/j.issn.1000-5277.2021.04.011
[32]. Wei, X., Widgren, M., Li, B., Ye, Y., Fang, X., Zhang, C., Chen, T., 2021. Dataset of 1 km cropland cover from 1690 to 1999 in Scandinavia. Earth System Science Data, 13(6), 3035-3056. https://doi.org/10.5194/essd-13-3035-2021
[31]. Wang, J., Wang, M., Kim, J.-S., Joiner, J., Zeng, N., Jiang, F., Wang, H., He, W., Wu. M., Chen, T., Ju. W., Chen. J., 2021. Modulation of land photosynthesis by the Indian Ocean Dipole: Satellite-based observations and CMIP6 future projections. Earth's Future, 9, e2020EF001942. https://doi.org/10.1029/2020EF001942
[30]. Shi, X., Wang, G., Chen, T., Li, S., Lu, J., & Hagan, D. F. T., 2021. Long‐term changes in layered soil temperature based on ground measurements in Jiangsu Province, China. International Journal of Climatology, 41(5), 2996-3009. https://doi.org/10.1002/joc.7001
[29]. Li, S., Wang, G., Sun, S., Hagan, D.F.T., Chen, T., Dolman, H. and Liu, Y., 2021. Long-term changes in evapotranspiration over China and attribution to climatic drivers during 1980–2010. Journal of Hydrology, 595, p.126037.
[28]. Lu, J., Wang, G., Chen, T., Li, S., Hagan, D. F. T., Kattel, G., Peng, J., Jiang, T., and Su, B., 2021. A harmonized global land evaporation dataset from model-based products covering 1980–2017, Earth Syst. Sci. Data, 13, 5879–5898, https://doi.org/10.5194/essd-13-5879-2021, 2021. https://doi.org/10.5194/essd-13-5879-2021
[27]. Chai, Y., Martins, G., Nobre, C., von Randow, C., Chen, T., Dolman, H., 2021. Constraining Amazonian land surface temperature sensitivity to precipitation and the probability of forest dieback. npj Climate and Atmospheric Science, 4(1), 1-7. https://doi.org/10.1038/s41612-021-00162-1
[26]. 马海云，张林林，魏学琼，施婷婷，陈铁喜* 2021. 2000—2015年西南地区土地利用与植被覆盖的时空变化[J].应用生态学报, 32(02):618-628. https://doi.org/10.13287/j.1001-9332.202102.017
[25]. 张林林, 陈铁喜* 2021. 1989—2018年京津冀地区人体舒适度的变化特征[J].天津师范大学学报(自然科学版), 41(04):53-60. https://doi.org/10.19638/j.issn1671-1114.20210408
[24]. Chen, X., Chen, T*., Yan, Q.., Cai, J.., Guo, R.., Gao, M.., Wei, X.., Zhou, S.., Li, C.., Xie, Y., 2021. The Ongoing Greening in Southwest China despite Severe Droughts and Drying Trends. Remote Sensing, 13, 3374. https://doi.org/10.3390/rs13173374
[23]. Yan, Q., Hu, T., Jin, S., Huang, W., Jia, Y., Chen, T., Wang, J., 2021. Improving CyGNSS-Based Land Remote Sensing: Track-Wise Data Calibration Schemes. Remote Sensing, 13(14), 2844. https://doi.org/10.3390/rs13142844
[22]. 蔡江涛,付波霖,陈铁喜,耿仁方,李颖,何宏昌,范冬林,邓腾芳, 2020.基于Sentinel-2卫星多光谱数据的会仙喀斯特湿地植物理化参数反演研究[J].湿地科学,18(06):693-705. https://doi.org/10.13248/j.cnki.wetlandsci.2020.06.008
[21]. Yue, S., Chen, M., Song, J., Yuan, W., Chen, T., Lü, G., Shen, C., Ma, Z., Xu, K., Wen, Y. and Song, H., 2020. Participatory intercomparison strategy for terrestrial carbon cycle models based on a service-oriented architecture. Future Generation Computer Systems, 112, pp.449-466.https://doi.org/10.1016/j.future.2020.05.044
[20]. Miao, L., Li, S., Zhang, F., Chen, T., Shan, Y., Zhang, Y., 2020. Future drought in the drylands of Asia under the 1.5° C and 2.0° C warming scenarios. Earth's Future, e2019EF001337. https://doi.org/10.1029/2019EF001337
[19]. Liang, C., Chen, T.*, Dolman, H., Shi, T.*, Wei, X., Xu, J., & Hagan, D. F. T., 2020. Drying and Wetting Trends and Vegetation Covariations in the Drylands of China. Water, 12(4), 933. https://doi.org/10.3390/w12040933
[18]. 朱浩朋,伍玉梅,陈铁喜* 2020. 基于MODIS数据的洞庭湖水域面积变动研究[J].渔业信息与战略,35(02):147-153. https://doi.org/10.13233/j.cnki.fishis.2020.02.009
[17]. Chen, T.*, Zhou, S., Liang, C., Hagan, D.F.T., Zeng, N., Wang, J., Shi, T., Chen, X., Dolman, A., 2020. The Greening and Wetting of the Sahel Have Leveled off since about 1999 in Relation to SST. Remote Sensing, 12, 2723. https://doi.org/10.3390/rs12172723
[16]. Wei, X., Wang, G., Chen, T., Hagan, D.F.T., Ullah, W., 2020. A Spatio-Temporal Analysis of Active Fires over China during 2003–2016. Remote Sens., 12, 1787. https://doi.org/10.3390/rs12111787
[15]. Wang, G., Gong, T., Lu, J., Lou, D., Hagan, D. F. T., Chen, T., 2018. On the long‐term changes of drought over China (1948–2012) from different methods of potential evapotranspiration estimations. International Journal of Climatology, 38(7), 2954-2966. https://doi.org/10.1002/joc.5475
[14]. Chen, T.*, Zhang, H., Chen, X., Hagan, D.F., Wang, G., Gao, Z., Shi, T., 2017. Robust drying and wetting trends found in regions over China based on Köppen climate classifications. Journal of Geophysical Research: Atmospheres, 122, 4228-4237, https://doi.org/10.1002/2016JD026168
(建立基于多干旱指数的区域干湿变化确定性方法)
[13]. Wang, G., Hagan, D.F.T., Lou, D., Chen, T., 2016. Evaluation of soil moisture derived from FY3B microwave brightness temperature over the Tibetan Plateau. Remote Sensing Letters, 7, 817-826. https://doi.org/10.1080/2150704X.2016.1192303
[12]. Chen, T.*, McVicar, T.R., Wang, G., Chen, X., de Jeu, R.A., Liu, Y.Y., Shen, H., Zhang, F., & Dolman, A.J., 2016. Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape. Remote Sensing, 8, 428. https://doi.org/10.3390/rs8050428
(证明了表层土壤湿度在侧向流地区研究生态水文过程中相比降水的优势)
[11]. Chen, T., Wang, G.*, Yuan, W., Li, A., & Liu, Y.Y.. 2016. Asymmetric NDVI trends of the two cropping seasons in the Huai River basin. Remote Sensing Letters, 7, 61-70. https://doi.org/10.1080/2150704X.2015.1109156
[10]. Shen, L., Wu, H., Gao, Z., Xu, X., Chen, T., Liu, S., & Cheng, H., 2015. Occurrence and importance of anaerobic ammonium-oxidising bacteria in vegetable soils. Applied Microbiology and Biotechnology, 99, 5709-5718. https://doi.org/10.1007/s00253-015-6454-z
[9]. Chen, T.*, van der Werf, G., Gobron, N., Moors, E., & Dolman, A., 2014. Global cropland monthly gross primary production in the year 2000. Biogeosciences, 11, 3871-3880. https://doi.org/10.5194/bg-11-3871-2014
(建立了全球26种农田的初级生产力数据集)
[8]. Chen, T.*, de Jeu, R., Liu, Y., van der Werf, G., & Dolman, A., 2014. Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia. Remote Sensing of Environment, 140, 330-338. https://doi.org/10.1016/j.rse.2013.08.022
(首次证明表层土壤湿度在植被对水分响应过程研究的有效性)
[7]. Chen, T., Werf, G., Jeu, R., Wang, G., & Dolman, A.*, 2013. A global analysis of the impact of drought on net primary productivity. Hydrology and Earth System Sciences, 17, 3885-3894. https://doi.org/10.5194/hess-17-3885-2013
[6]. Dolman, A., Shvidenko, A., Schepaschenko, D., Ciais, P., Tchebakova, N., Chen, T., Van Der Molen, M., Belelli Marchesini, L., Maximov, T., & Maksyutov, S., 2012. An estimate of the terrestrial carbon budget of Russia using inventory-based, eddy covariance and inversion methods. Biogeosciences, 9, 5323-5340. https://doi.org/10.5194/bg-9-5323-2012
[5]. van der Molen, M.K., Dolman, A.J., Ciais, P., Eglin, T., Gobron, N., Law, B.E., Meir, P., Peters, W., Phillips, O.L., Reichstein, M., Chen, T., Dekker, S.C., Doubková, M., Friedl, M.A., Jung, M., van den Hurk, B.J.J.M., de Jeu, R.A.M., Kruijt, B., Ohta, T., Rebel, K.T., Plummer, S., Seneviratne, S.I., Sitch, S., Teuling, A.J., van der Werf, G.R., & Wang, G., 2011. Drought and ecosystem carbon cycling. Agricultural and Forest Meteorology, 151, 765-773. https://doi.org/10.1016/j.agrformet.2011.01.018
[4]. Dong, Q., Chen, X., & Chen, T., 2011. Characteristics and Changes of Extreme Precipitation in the Yellow-Huaihe and Yangtze-Huaihe Rivers Basins, China. Journal of Climate, 24, 3781-3795. https://doi.org/10.1175/2010JCLI3653.1
[3]. Chen, T.*, van der Werf, G.R., Dolman, A., Groenendijk, M., 2011. Evaluation of cropland maximum light use efficiency using eddy flux measurements in North America and Europe. Geophysical Research Letters, 38. https://doi.org/10.1029/2011GL047533
[2]. 董全, 陈星, 陈铁喜, 程兴无, 2009. 淮河流域极端降水与极端流量关系的研究. 南京大学学报自然科学, 45, 790-801.
[1]. 陈铁喜, 陈星*, 2007. 近 50 年中国气温日较差的变化趋势分析. 高原气象, 26, 150-157.