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英文期刊 (标*的为通讯作者）
Zhong, L., L. Hua, Y. Yao, J., T. Zhao, 2021: Moisture transport to a typical transitional climate zone in North China forced by atmospheric and oceanic internal variability under the background of global warming. Int J Climatol., 1–21. https://doi.org/10.1002/joc.6999.
Liu, X., C. Li, and T. Zhao, 2020: Future changes of global potential evapotranspiration simulated from CMIP5 to CMIP6 models. Atmospheric and Oceanic Science Letters, doi: 10.1080/16742834.2020.1824983.
Lu, C., T. Zhao*, and C. Zhou, 2020: Evaluation of the Antarctic Circumpolar Wave simulated by CMIP5 and CMIP6 models. Atmosphere, doi: 10.3390/ATMOS11090931. 【SCI】
Yang, T., Q. Li, X. Chen, P. D. Maeyer, X. Yan,Y. Liu, T. Zhao, and L. Li, 2020: Spatiotemporal variability of the precipitation concentration and diversity in Central Asia. Atmospheric Research, https://doi.org/10.1016/j.atmosres.2020.104954. 【SCI】
Zhang, J., T. Zhao*, A. Dai, and W. Zhang, 2019: Detection and attribution of atmospheric precipitable water changes since the 1970s over China. Scientific Reports, doi: 10.1038/s41598-019-54185-z. 【SCI】
Li, C., T. Zhao*, C. Shi, and Z.-Q., Liu, 2019: Evaluation of precipitation from the China Meteorological Administration Global Atmospheric Interim Reanalysis on the daily scale in China. Journal of Meteorological Research, doi: 10.1007/s13351-020-8196-9. 【SCI】
Li, C., C. Wang, and T. Zhao, 2019: Seasonal co-variability of dryness/wetness in China and global sea surface temperature. J. Climate. , 33 (2), 727-747 【SCI】
Li, C., and T. Zhao*, 2019: Seasonal responses of precipitation in China to El Niño and positive Indian Ocean dipole modes. Atmospere, 10, 372, doi: 10.3390/atmos10070372. 【SCI】
Zhang, J. and T. Zhao*, 2019: Historical and future changes of atmospheric precipitable water over China simulated by CMIP5 models. Climate Dynamics, 52(11), 6969-6988, doi: http://orcid.org/0000-0002-8295-6537. 【SCI】
Forbes,W. L., and 11 coauthors (including T. Zhao), 2019: Streamflow in the Columbia River Basin: Quantifying changes over the period 1951-2008 and determing the drivers of those changes. Water Resources Research, 55, doi: https://doi.org/10.1029/2018wWR024256. 【SCI】
Dai, A., T. Zhao, and J. Chen, 2018: Climate change and drought: a precipitation and evaporation perspective. Current Climate Change Reports, doi: https://doi.org/10.1007/s40641-018-0101-6. 【SCI】
Forbes, W. L., and 21 Coauthors (including T. Zhao), 2018: Contribution of environmental forcings to US runoff changes for the period 1950–2010. Environmental Research Letters, doi: https://doi.org/10.1088/1748-9326/aabb41. 【SCI】
Ying, K., C. Frederiksen, X. Zheng, J. Lou, and T. Zhao*, 2018:Variability and predictability of decadal mean temperature and precipitation over China in the CCSM4 Last Millennium simulation. Clim. Dyn., doi: 10.1007/s00382-017-4060-8. 【SCI】
Zuo, Z., S. Yang, K. Xu, R. Zhang, Q. He, T. Zhao, and J. Cong, 2017: Land surface air temperature variations overEurasia and possible causes in the past century. Int. J. Climatol.. doi: 10.1002/joc.5306. 【SCI】
Ying, K., C. Frederiksen, T. Zhao, X. Zheng, Z. Xiong, Y. Xue, and C. Li, 2017: Predictable and unpredictable modes of seasonal mean precipitation over Northeast China. Clim. Dyn., doi: 10.1007/s00382-017-3795-6. 【SCI】
Tang,Y., X. Song, Y. Zhang, D. Han, L. Ai, T. Zhao, and Y. Wang, 2017: Using stable isotopes to understand seasonal and interannual dynamics in moisture sources and atmospheric circulation inprecipitation. Hydrological Processes,doi: 10.1002/hyp.11388. 【SCI】
Li, C., T. Zhao*, and K. Ying, 2017: Quantifying the contributions of anthropogenic and natural forcings to climate changes overland during 1946–2005.Climatic Change,. Climatic, doi: 10.1007/s10584-017-2028-7.【SCI】
Li, C., C. Wang, and T. Zhao, 2017: Influence of two types of ENSO events ontropical cyclones in the western North Pacific during the subsequent year: asymmetric response. Clim. Dyn., doi:10.1007/s 00382-017-4033-y. 【SCI】
Chen, L., Z. Ma,T. Zhao, Z. Li, and Y. Li, 2017: Simulation of the regional climatic effect of irrigation over the Yellow River Basin. Atmos. Oceanic Sci. Lett., doi:10.1080/16742834.2017.1313681.
Chen, L., Z. Ma, andT. Zhao, 2016: Modeling and analysis of the potential impacts on regional climate due to vegetation degradation over arid and semi-arid regions of China. Climatic Change, doi: 10.1007/s10584-016-1847-2. 【SCI】
Chen, L., Z. Ma, R. Mahmood, T. Zhao, Z. Li, and Y. Li, 2016: Recent Land Cover Changes and Sensitivity of the Model Simulations to Various Land Cover Datasets for China. Meteorology and Atmospheric Physics, doi: 10.1007/s00703-016-0478-5. 【SCI】
Zhao, T., and A. Dai, 2017: Uncertainties in historical changes and future projections of drought. Part II: Model simulated historical and future drought changes. Climatic Change, doi:10.1007/s10584-016-1742-x. 【SCI】
Dai, A., and T. Zhao, 2017: Uncertainties in historical changes and future projections of drought. Part I: Estimates of historical drought changes. Climatic Change, doi:10.1007/s10584-016-1705-2. 【SCI】
Ying, K., X. Zheng,T . Zhao*, X. W. Quan, C. S. Frederiksen, 2016: Identifying the predictable and unpredictable patterns of spring-to-autumn precipitation over eastern China. Climate Dynamics, doi:10.1007/s00382-016-3258-5. 【SCI】
Fu, S., J. Zhang, J. Sun,T. Zhao, 2016: Composite analysis of long-lived mesoscle vortices over the middle reaches of the Yangtze River valley: Octant features and evolution mechanisms. J. Climate,2 9, 761-781, doi:10.1175/JCLI-D-15-0175.1. 【SCI】
Ying, K., T. Zhao*, X. Zheng, X.-W. Quan, C.S. Frederiksen, M. Li, 2016:Predictable signals in seasonal mean soil moisture simulated with observation-based atmospheric forcing over China.Climate Dynamics,47, 2373-2395,doi:10.1007/s00382-014-2411-2. 【SCI】
Zhao, T., C. Li, and Z. Zuo, 2016: Contributions of human activities and external natural forcings to climate changes over China based on the CMIP5 simulations. Science in China (D), 59, 503-517, doi: 10.1007/s11430-015-5207-2. 【SCI】
Li, C.,T. Zhao*, and K. Ying, 2016: Effects of anthropogenic aerosols on temperature changes in China during the 20th century based on CMIP5 models. Theor. Appl. Climatology,125, 529-540, doi:10.1007/s00704-015-1527-6. 【SCI】
Zhao, T, J. Wang, and A. Dai, 2015: Evaluation of atmospheric precipitable water from reanalysis products using homogenized radiosonde observations over China. J. Geophys. Res.- Atmospheres,120, 1070–10727, doi: 10.1002/2015JD023906. 【SCI】
Zhao, T., A. Dai, 2015: The magnitude and causes of global drought changes in the 21st century under a lo–moderate emissions scenario. J. Climate, 28, 4490-4512, doi:10.1175/JCLI-D-14-00363.1. 【SCI】
Ying, K.,T. Zhao, X. Quan, X. Zheng, and S. F. Carsten, 2014: Variability of autumn to spring seasonal precipitation in eastern China. Climate Dynamics, doi:10.1007/s00382-014-2411-2. 【SCI】
Mao, R., D.-Y. Gong,T. Zhao, W. Wang, J. Yang, 2015: Trends in the frequency of high relative humidity over China: 1979 to 2012. J. Climate, doi:10.1175/JCLI-D-14-00840.1.【SCI】
Zhao, T., 2014: Correlations of atmospheric water vapor with the diurnal temperature range over China.Atmos. Oceanic Sci. Lett., 7, 369-375.
Yuan, W., D. Liu, W. Dong, S. Liu, G. Zhou, G. Yu, T. Zhao, J. Feng, Z. Ma, J. Chen, Y. Chen, S. Chen, S. Han, J. Huang, L. Li, H. Liu, S. Liu, M. Ma, Y. Wang, J. Xia, W. Xu, Q. Zhang, X. Zhao, and L. Zhao, 2014: Multiyear precipitation reduction strongly decreases carbon uptake over northern China. J. Geophys. Res. -Biogeosciences, 119, 881–896, doi: 10.1002/2014JG002608. 【SCI】
Xia, J., W. Yuan, S. Liang, J. Chen, S. Liu, L. Li, X. Li, L. Zhang, Y. Fu, T. Zhao, J. Feng, Z. Ma, M. Ma, S. Liu, G. Zhou, J. Asanuma, S. Chen, M. Du, G. Dava, T. Kato, Q. Liu, S. Liu, S. Li, C. Shao, Y. Tang, X. Zhao, 2014: Satellite-Based Analysis of Evapotranspiration and Water Balance in the Grassland Ecosystems of Dryland East Asia. PLoS ONE, 9, e97295. doi:10.1371/journal.pone.0097295. 【SCI】
Zhang, L., H. Guo, G. Jia, B. Wylie, T. Gilmanov, D. Howard, L. Ji, J. Xiao, J. Li, W. Yuan, T. Zhao,S. Chen, G. Zhou, and T. Kato, 2014: Net ecosystem productivity of temperate grasslands in northern China: An upscaling study. Agricultural and Forest Meteorology, 184, 71–81. 【SCI】
Chen, Y., J. Xia, S. Liang, J. Feng, J. B. Fisher, X. Li, X. Li, S. Liu, Z. Ma, A. Miyata, Q. Mu, L. Sun, J. Tang, K. Wang, J. Wen, Y. Xue, G. Yu, T. Zha, L. Zhang, Q. Zhang, T. Zhao, L. Zhao, W. Yuan, 2014: Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China. Remote Sens. Environ., 140, 279-293. 【SCI】
Zhao, T., and A. Yatagai, 2014: Evaluation of TRMM 3B42 products using a new gauge-based analysis of daily precipitation over China. Int. J. Climatol., doi: 10.1002/joc.3872. 【SCI】
Zhao, T., L. Chen, and Z. Ma, 2014: Simulation of historical and projected climate change in arid and semi-arid areas by CMIP5 models. Chin. Sci. Bull., doi: 10.1007/s11434-013-0003-x. 【SCI】
Ying, K.,T. Zhao, and X. Zheng, 2013: Slow and intraseasonal modes of the boreal winter atmospheric circulation simulated by CMIP5 models. Atmos. Oceanic Sci. Lett., doi:10.3878/j.issn.1674-2834.13.0058.
Hou, J., G. Jia,T. Zhao, H. Wang, and B. Tang, 2014: Satellite based estimation of daily average net radiation under clear-sky conditions. Adv. Atmos. Sci., 31, 705–720, doi: 10.1007/s00376-013-3047-6. 【SCI】
Huang, G., W. Wang, X. Zhang, S. Liang, S. Liu, T. Zhao.J. Feng, and Z. Ma, 2013: Preliminary validation of GLASS-DSSR products using surface measurements collected in arid and semi-arid regions of China. Int. J. of Digit. Earth, doi:10.1080/17538947.2013.825655. 【SCI】
Wang, X., M. Ma, X. Li, Y. Song, J. Tan, G. Huang, Z. Zhang, T. Zhao, J. Feng, Z. Ma, W. Wei, and Y. Bai, 2013: Validation of MODIS GPP product at ten flux sites in northern China. Int. J. Remote Sens., 34, 587-599.【SCI】
Li, X., S. Liang, G. Yu, W. Yuan, X. Cheng, J. Xia, T. Zhao,J. Feng, Z. Ma, et al., 2013: Estimation of gross primary production over the terrestrial ecosystems in China. Ecological Modelling, 261–262, doi:10.1016/j.ecolmodel.2013.03.024. 【SCI】
Zhao, T., A. Dai, and J. Wang, 2012: Trends in tropospheric humidity from 1970 to 2008 over China from a homogenized radiosonde dataset. J. Climate, 25, 4549–4567.【SCI】
Li, X., S. Liang, W. Yuan, G. Yu, X. Cheng, Y. Chen,T. Zhao, et al., 2012: Estimation of evapotranspiration over the terrestrial ecosystems in China. Ecohydrology, doi: 10.1002/eco.1341.【SCI】
Zhao, T., and D. Zhao, 2011: Can artificial climate trends in global reanalysis be reduced by dynamical downscaling: a case study over China.Atmos. Oceanic Sci. Lett., 4(1), 1−6.
Wang, J., T. Zhao, E. Wang, et al., 2010: Measurement and simulation of diurnal variations in water use efficiency and radiation use efficiency in an irrigated wheat-maize field in the North China Plain. New Zeal. J. Crop Hort., 38, 119-135. 【SCI】
Zhang, A., G. Jia, H. Wang, and T. Zhao, 2011: Validation of land surface temperature derived from 37-GHz AMSR-E over northern China. Atmos. Oceanic Sci. Lett., 4, 257-263.
Zhang, A., G. Jia, H. Wang,T. Zhao, J. Feng, and Z. Ma, 2011: Evaluation of AMSR-E derived soil moisture over northern China. Atmos. Oceanic Sci. Lett., 4, 2 23-228.
Wang, H., G. Jia, C. Fu, J. Feng, T. Zhao, and Z. Ma, 2010: Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling. Remote Sens., doi:10.1016/j.rse.2010.05.001. 【SCI】
Wang, H., G. Jia, J. Feng,T. Zhao, and Z. Ma, 2010: Modeling gross primary production by integrating satellite data and coordinated flux measurements in arid and semi-arid China. Atmos. Oceanic Sci. Lett., 3, 7−13.
Zhao, T., and C. Fu, 2009: Intercomparison of the summertime subtropical high from the ERA-40 and NCEP/NCAR over east Eurasia and the western North Pacific.Adv. Atmos. Sci.,26, 119-131. 【SCI】
Ke, Z., W. Dong, P. Zhang, J. Wang, andT. Zhao, 2009: An analysis of the difference between the multiple linear regression approach and the multi-model ensemble mean. Adv. Atmos. Sci., 26, 1157-1168. 【SCI】
Jiang,Y., S. Wang, S. Yang, W. Dong, C. Fu, andT. Zhao,2009: Future trends of climatic belts and seasons in China. Int. J. Climatol., 28, 1483–1491. doi: 10.1002/joc.1658.
Zhao, T., W. Guo, and C. Fu, 2008: Calibrating and evaluating reanalysis surface temperature error by topographic correction. J. Climate, 21, 1442-1448. 【SCI】
Zhao, T., and C. Fu, 2006: Comparison of products from ERA-40, NCEP-2, and CRU with station data for summer precipitation over China. Adv. Atmos. Sci., 23,593–604. 【SCI】
中文期刊
赵倩倩, 张京朋, 赵天保, 李建华, 2019:2000年以来中国区域植被变化及其对气候变化的响应. 高原气象, doi:10.7522/j.issn.1000-0534.2020.00025.
赵天保*, 从靖, 2017:基于CCSM4.0长期积分试验评估不同辐射强迫对中国干旱半干旱区降水的影响. 大气科学, doi:10.3878/j.issn.1006-989 5.1706.16167.
赵天保, 李春香, 左志燕, 2016:基于CMIP5 多模式评估人为和自然因素外强迫在中国区域气候变化中的相对贡献. 中国科学: 地球科学, 46, 237–252, doi: 10.1360/N072015-00075.
从靖, 赵天保*, 马玉霞, 2016:中国北方干旱半干旱区降水的多年代际变化特征及其与太平洋年代际振荡的关系.气候与环境研究, 22, 643-657,doi: 10.3878/j.issn.1006-9585.2016.16036.
肖冰霜, 马玉霞, 赵天保, 颜书豪, 2016:基于均一化资料的中国大陆极端温度的长期趋势. 气象，42, 339-346.
张驰, 范广洲, 马柱国, 程炳岩, 赵天保, 冯 锦明, 王鹤松, 2015:半干旱区典型下垫面反照率特征的初步分析. 高原气象, 34, 1029-1040.
刘斌，孙艳玲，王中良，赵天保，2015:华北地区植被覆盖变化及其影响因子的相对作用分析.自 然资源学报, doi: 10.11849/zrzyxb.2014.
王娟怀, 赵天保, 马玉霞, 2015:西安市空气污染特征及其与气象因子的关系. 环境化学, 34, 386-387.
李春香, 赵天保*, 马柱国, 2014:基于CMIP5多模式结果评估人类活动对全球典型干旱半干旱区气候变化的影响. 科学通报，59，2972-2988.
赵天保*, 陈亮, 马柱国, 2014:CMIP5多模式对全球典型干旱半干旱区气候变化的模拟与预估. 科学通报，59, 412-429, doi:10.1007/s11434-013-0003-x.
夏江江，杨庆，郑子彦, 赵天保，严中伟，马柱国, 2014:土地利用变化对20世纪中国地区气候干湿变化的影响.气候与环境研究, 20, 154-166.
赵天保, 涂锴, 严中伟, 2013:大气水汽变化及其反馈效应研究进展.气候变化研究进展, 9, 79-88.
王筝, 赵天保, 延晓冬, 侯美亭, 2013:21世纪初中国北方地区植被变化特征分析.气候与环境研究, 18(2), 156-164.
赵天保, 钱诚, 2010: 传统距平与变年循环参照系下的中国气温变率比较.气候与环境研究, 14(6), 1-11.
赵天保, 符淙斌, 柯宗建, 郭维栋, 2010:全球大气再分析资料的研究现状与进展.地球科学进展, 25(3), 242-254.
王鹤松, 贾根锁, 冯锦明, 赵天保, 马柱国, 2010:我国北方地区植被总初级生产力的空间分布与季节变化. 大气科学, 34(5), 882-890.
赵天保, 符淙斌, 2009:应用探空观测资料评估几类再分析资料在中国区域的适用性.大气科学,33(3), 634-648.
赵天保, 符淙斌, 2009:几种再分析地表气温资料在中国区域的适用性评估.高原气象, 28(3), 594-605.
赵天保, 华丽娟, 2009:几种再分析地表气压资料在中国区域的适用性评估.应用气象学报, 20(1), 70-79.
赵天保,符淙斌, 2006:中国区域ERA-40、NCEP-2再分析资料与观测资料的初步比较与分析.气候与环境研究, 11(1), 14-32.
赵天保,艾丽坤, 冯锦明，2004:NCEP再分析料和中国站点观测资料的分析比较.气候与环境研究，9(2), 278–294.
冯锦明, 赵天保, 张英娟, 2004:基于台站观测资料对几种空间内插方法的比较研究.气候与环境研究，9(2)，261–277.
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