赵龙个人简历（Email: zhaol04@swu.edu.cn; zhaol04@gmail.com）
教育工作经历
2017/05至今 西南大学地理科学学院，副教授
2013/10–2017/04 德州大学奥斯汀分校，博士后
2008/09–2013/07 中国科学院青藏高原研究所，获自然地理学博士学位
2011/10–2012/09 于利希研究中心（IBG-3，德国），CSC资助联合培养博士生项目
2004/09–2008/07 清华大学水利水电工程系，获工学学士学位
讲授课程
《地理信息系统专业英语》，《遥感概论》，《计量地理学》、《遥感野外综合实习》、《地理学科发展前沿专题》
研究兴趣
主要研究方向为水文气象遥感与陆面数据同化。建立了基于CLM-DART的多源全球陆面数据同化系统，开展区域及全球尺度积雪和土壤水分同化；在青藏高原中部参与设计并建立了包含56个站点的多尺度土壤温湿度观测网（加入国际土壤水分网ISMN），同时在重庆青木关小流域建立土壤水分观测网，开展土壤水分升/降尺度研究。
ResearchGate: https://www.researchgate.net/profile/Long_Zhao5;
Google Scholar: https://scholar.google.com/citations?hl=en&user=NZ_q89cAAAAJ;
参与和主持项目
[1] 科技部国家重点研发计划子课题，全球陆面数据同化系统构建及产品制作，2018/07-2023/06，主持
[2] 国家自然科学基金青年科学基金项目，基于卫星数据同化估计陆面模型静态参数与土壤水分的方法研究，2019/01-2021/12，主持
[3] 重庆市2018年留创计划创新类资助，基于变分和集合同化的模型静态参数与土壤水分估算研究，主持
[4] 国家自然科学基金重大研究计划集成项目，青藏高原地-气耦合系统变化及其全球气候效应，2018/01-2020/12，参加（项目骨干）
[5] 西南大学人才引进项目，基于多源微波遥感的土壤水分陆面数据同化，2017/01-2019/12，主持
指导学生创新项目
[1] 周学谦等，2019，地质学教育软件的开发与理论研究
[2] 黄仲渝等，2019，基于人工神经网络的微波卫星土壤水分校正研究
[3] 李婷婷等，2018，土壤水分观测最小站点数的空间和深度稳定性研究
发表论文
[1] Zhao, L. and Yang, Z.-L., 2018. Multi-sensor land data assimilation: Toward a robust global soil moisture and snow estimation. Remote Sensing of Environment, 216: 13-27.
[2] Zhao, L., Z.-L. Yang, T. J. Hoar, 2016. Global Soil Moisture Estimation by Assimilating AMSR-E Brightness Temperatures in a Coupled CLM4–RTM–DART System, Journal of Hydrometeorology, 17: 2431–2454.
[3] Zhao, L., K. Yang, J. Qin, Y. Y. Chen, W. J. Tang, H. Lu, and Z. L. Yang, 2014. The scale-dependence of SMOS soil moisture accuracy and its improvement through land data assimilation in the central Tibetan Plateau. Remote Sensing of Environment, 152: 345-355.
[4] Zhao, L., K. Yang, J. Qin, Y. Y. Chen, W. J. Tang, C. Montzka, H. Wu, C. G. Lin, M. L. Han, and H. Vereecken., 2013. Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements. Journal of Hydrology, 482: 92-104.
[5] Zhao, L., K. Yang, J. Qin, and Y. Chen, 2013. Optimal Exploitation of AMSR-E Signals for Improving Soil Moisture Estimation through Land Data Assimilation, Geoscience and Remote Sensing, IEEE Transactions on, 51: 399-410.
[6] Bian, Q. Y., Z. F. Xu, L. Zhao, Y. F. Zhang, H. Zheng, C. X. Shi, S. Zhang, C. H. Xie, and Z. L. Yang, 2019, Evaluation and Intercomparison of Multiple Snow Water Equivalent Products over the Tibetan Plateau, Journal of Hydrometeorology, in press.
[7] Song, L. S., Y. Li, Y. H. Ren, X. C. Wu, B. Guo, X. G. Tang, W. Y. Shi, M. G. Ma, X. J. Han, and L. Zhao, 2019. Divergent vegetation responses to extreme spring and summer droughts in Southwestern China, Agricultural and Forest Meteorology, 279, 107703.
[8] Zheng, H., Z.-L. Yang, P.-R. Lin, J.-F. Wei, W.-Y. Wu, L.-C. Li, L. Zhao, and S. Wang, 2019. On the Sensitivity of the Precipitation Partitioning into Evapotranspiration and Runoff in Land Surface Parameterizations. Water Resources Research, 55. https://doi.org/10.1029/2017WR022236
[9] Han, M., Lu, H., Yang, K., Qin, J., Chen, Y., Zhao, L., Lazhu, 2017. A surface soil temperature retrieval algorithm based on AMSR-E multi-frequency brightness temperatures.International Journal of Remote Sensing,38(23): 6735-6754.
[10] Kwon, Y., Z.-L. Yang, L. Zhao, T. J. Hoar, A. M. Toure, 2016. Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation, Journal of Hydrometeorology, 17: 2853–2874.
[11] Yang, K., Z. La, Y.Y. Chen, L. Zhao, J. Qin, H. Lu, W.J. Tang, M.L. Han, B.H. Ding, and N. Fang, 2016. Land surface model calibration through microwave data assimilation for improving soil moisture simulations, Journal of Hydrology, 533: 266-276.
[12] Lu, H., K. Yang, T. Koike, L. Zhao, and J. Qin, 2015. An Improvement of the Radiative Transfer Model Component of a Land Data Assimilation System and its Validation on Different Land Characteristics, Remote Sensing, 7: 6358-6379.
[13] Qin, J., L. Zhao, Y.Y. Chen, K. Yang, Y.P. Yang, Z.Q. Chen, and H. Lu, 2015. Inter-comparison of spatial upscaling methods for evaluation of satellite-based soil moisture, Journal of Hydrology, 523: 170-178.
[14] Han, M.L., K. Yang, J. Qin, R. Jin, Y.M. Ma, J. Wen, Y.Y. Chen, L. Zhao, Lazhu, and W.J. Tang, 2015. An algorithm based on the standard deviation of passive microwave brightness temperature for monitoring soil surface freeze/thaw state on the Tibetan Plateau, Geoscience and Remote Sensing, IEEE Transactions on, 53(5): 2775-2783.
[15] Xu, C., Y.M. Ma, A. Panday, Z.Y. Cong, K. Yang, Z.K. Zhu, J.M. Wang, P.M. Amatya, and L. Zhao, 2014. Similarities and differences of aerosol optical properties between southern and northern sides of the Himalayas. Atmos. Chem. Phys., 14: 3133-3149.
[16] Xue, B. L., L. Wang, K. Yang, L. D. Tian, J. Qin, Y. Y. Chen, L. Zhao, Y. M. Ma, T. Koike, Z. Y. Hu, and X. P. Li., 2013. Modeling the land surface water and energy cycles of a mesoscale watershed in the central Tibetan Plateau during summer with a distributed hydrological model, Journal of Geophysical Research - Atmosphere, 118: 8857-8868.
[17] Qin, J., K. Yang, N. Lv, Y. Y. Chen, L. Zhao, M. L. Han., 2013. Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia. Remote Sens. Environ, 138:1-9.
[18] Yang., K., J. Qin, L. Zhao, Y. Y. Chen, W. J. Tang, M. L. Han, Lazhu., Z. Q. Chen, N. Lv, B. H. Ding, H. Wu, and C. G. Lin,. 2013. A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole for Multi-Sphere Interaction Studies, Bull. Am. Meteorol. Soc., 94(12): 1907–1916.
[19] Chen, Y., K. Yang, J. Qin, L. Zhao, W. Tang, and M. Han.,2013. Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan plateau, Journal of Geophysical Research - Atmospheres, 118: 4466-4475.
[20] Chen, Y. Y., K. Yang, W. J. Tang, J. Qin and L. Zhao, 2012. Parameterizing soil organic carbon's impacts on soil porosity and thermal parameters for Eastern Tibet grasslands, Sci China Earth Sci, 55: 1001–1011.
[21] Yang, W., X. F., Guo, T-D, Yao, K. Yang, L. Zhao, S. Li, M. L. Zhu, 2011. Summertime surface energy budget and ablation modeling in the ablation zone of a maritime Tibetan glacier, JGR-Atmosphere, 116, D14116.
[22] Guo, X. F., K. Yang, L. Zhao, W. Yang, S. H. Li, M. L. Zhu, T. D. Yao, Y. Y. Chen, 2011. Critical Evaluations of Scalar Roughness Length Parameterizations over a Melting Valley Glacier, Boundary-Layer Meteorol., 139: 307–332.