雷小途, 李永平, 于润玲, 李泓, 汤杰, 段自强, 郑运霞, 方平治, 赵兵科, 曾智华, 黄伟, 鲍旭炜, 喻自凤, 陈国民, 马雷鸣, 骆婧瑶, 张帅, 林立旻, 2019: 新一代区域海-气-浪耦合台风预报系统, 海洋学报, 41(06), 123-134, https://doi.org/10.3969/j.issn.0253-4193.2019.06.012.
雷小途, 雷明, 赵兵科等, 2017: 火箭弹下投探测台风气象参数新技术及初步试验, 科学通报, 62(32), 3, https://doi.org/10.1360/N972017-00160.
方平治, 赵兵科, 张帅, 曾智华, 林雯, 2015: 中等到强风条件下近海拖曳系数随风速变化的观测, 热带气象学报, 31(05), 713-720.
顾凯华, 史红仙, 张帅等, 2015: 上海崇明岛近三年 PM2.5 浓度变化特征与气象条件的关系, 长江流域资源与环境, 24(12), 2108-2116, https://doi.org/10.11870/cjlyzyyhj201512015.
方平治, 赵兵科, 张帅, 曾智华, 林雯, 2015: 中等到强风条件下近海拖曳系数随风速变化的观测, 热带气象学报, 31(05), 713-720.
焦鹏程, 王振会, 楚志刚, 韩静, 张帅, 朱艺青, 2016: 基于傅里叶谱分析的天气雷达图像插值方法, 高原气象, 35(06), 1683-1693, https://doi.org/10.7522/j.issn.1000-0534.2015.00108.
张帅, 王振会, 赵兵科, 陈羿辰, 2019: 星载雷达在订正地基天气雷达标定误差中的应用, 气候与环境研究, 24(05), 576-584, https://doi.org/10.3878/j.issn.1006-9585.2019.18118.
张帅, 王振会, 赵兵科, 冷亮, 2019: 星载雷达在评估地基天气雷达非降水回波识别算法效果中的应用, 遥感技术与应用, 34(05), 1101-1110, https://doi.org/10.11873/j.issn.1004-0323.2019.5.1011.
Wang, L., X. Bao, Y. Hu, S. Zhang, W. Lin and Y. Zhuang, 2023: Microphysics of heavy rain associated with the eyewall and inner rainbands of Typhoon Meranti (2016). J. Geophys. Res.: Atmos., 128, e2022JD037288, https://doi.org/10.1029/2022JD037288.
Duan, Z., B. Zhao, S. Fu, S. Zhang, L. Lin and J. Tang, 2023: Investigating the Diurnal Variation in Coastal Boundary Layer Winds on Hainan Island Using Three Tower Observations. Atmosphere, 14, 751, https://doi.org/10.3390/atmos14040751.
Xia, T., Y. Wang and S. Zhang, 2023: Spatio-Temporal Coupling Analysis of Differences in Regional Grain-Economy-Population and Water Resources. Atmosphere, 14, 431, https://doi.org/10.3390/atmos14030431.
Jiang, S.H., H.L. Zhi, Z.Z. Wang and S. Zhang, 2023: Enhancing flood risk assessment and mitigation through numerical modeling: A case study. Nat. Hazards Rev., 24(01), 04022046, https://doi.org/10.1061/NHREFO.NHENG-1687.
Wu, J., Y. Liu, Y.S. Li, et al., 2022: The extreme Northeast China cold vortex activities in the late spring of 2021 and possible causes involved. Adv. Clim. Change Res., 13(06), 787-796, https://doi.org/10.1016/j.accre.2022.09.002.
Lu, Y., J. Yin, D. Wang, Y. Yang, H. Yu, P. Chen and S. Zhang, 2022: Evaluating the influence of multisource typhoon precipitation data on multiscale urban pluvial flood modeling. Int. J. Disaster Risk Sci., 13(06), 974-986, https://doi.org/10.1007/s13753-022-00446-x.
Tao, F., Y. Li, Y. Chen, L. Yin and S. Zhang, 2022: Daily, seasonal and inter-annual variations in CO2 fluxes and carbon budget in a winter-wheat and summer-maize rotation system in the North China Plain. Agric. For. Meteorol., 324, 109098, https://doi.org/10.1016/j.agrformet.2022.109098.
Lin, L., H. Yuan, X. Bao, W. Chen, S. Zhang and F. Xu, 2022: Evaluation of the raindrop size distribution representation of microphysics schemes in Typhoon Lekima using disdrometer network observations. Atmos. Res., 278, 106346, https://doi.org/10.1016/j.atmosres.2022.106346.
Zhang, S., X. Bao, L. Wu, et al., 2022: Dual-polarization radar retrieval during Typhoon Lekima (2019): Seeking the best-fitting shape-slope relationship depending on the differential-horizontal reflectivity relationship. Atmos. Res., 267, 105978, https://doi.org/10.1016/j.atmosres.2021.105978.
Zhang, S., Z. Yu, X. Gong, et al., 2021: Precession cycles of the El Niño/Southern oscillation-like system controlled by Pacific upper-ocean stratification. Commun. Earth Environ., 2, 239, https://doi.org/10.1038/s43247-021-00305-5.
Lin, L., X. Bao, S. Zhang, et al., 2021: Correction to raindrop size distributions measured by PARSIVEL disdrometers in strong winds. Atmos. Res., 260, 105728, https://doi.org/10.1016/j.atmosres.2021.105728.
Zhang, S., T.M. Pavelsky, C.D. Arp, et al., 2021: Remote sensing of lake ice phenology in Alaska. Environ. Res. Lett., 16(06), 064007, https://doi.org/10.1088/1748-9326/abf965.
Zhang, S., J.Z. Min, C.A. Zhang, X.Y. Huang, J. Liu and K.H. Wei, 2021: Hybrid method to identify second-trip echoes using phase modulation and polarimetric technology. Adv. Atmos. Sci., 38(03), 480-492, https://doi.org/10.1007/s00376-020-0223-3.
Lu, X.Q., H. Yu, M. Ying, B.K. Zhao, S. Zhang, L.M. Lin, L.N. Bai and R.J. Wan, 2021: Western North Pacific tropical cyclone database created by the China Meteorological Administration. Adv. Atmos. Sci., 38(04), 690-699, https://doi.org/10.1007/s00376-020-0211-7.
Zhang, S., C. Li, J. Peng, D. Peng, Q. Xu, Q. Zhang and B. Bate, 2021: GIS-based soil planar slide susceptibility mapping using logistic regression and neural networks: A typical red mudstone area in southwest China. Geomat. Nat. Hazards Risk., 12(01), 852-879, https://doi.org/10.1080/19475705.2021.1896584.
Bian, Q., Z. Xu, H. Zheng, K. Li, J. Liang, W. Fei, et al., 2020: Multiscale changes in snow over the Tibetan Plateau during 1980-2018 represented by reanalysis data sets and satellite observations. J. Geophys. Res.: Atmos., 125, e2019JD031914, https://doi.org/10.1029/2019JD031914.
Wu, J., P.Q. Zhang, L. Li, et al., 2020: Representation and predictability of the East Asia-Pacific teleconnection in the Beijing Climate Center and UK Met Office subseasonal prediction systems. J. Meteorol. Res., 34(05), 941-964, https://doi.org/10.1007/s13351-020-0040-8.
Bao, X., L. Wu, S. Zhang, Q. Li, L. Lin, B. Zhao, et al., 2020: Distinct raindrop size distributions of convective inner- and outer-rainband rain in Typhoon Maria (2018). J. Geophys. Res.: Atmos., 125, e2020JD032482, https://doi.org/10.1029/2020JD032482.
Zhang, S., X. Huang, J. Min, et al., 2020: Improved fuzzy logic method to distinguish between meteorological and non-meteorological echoes using C-band polarimetric radar data. Atmos. Meas. Tech., 13(02), 537-551, https://doi.org/10.5194/amt-13-537-2020.
Zhang, S., & Tao, F. (2019). Improving rice development and phenology prediction across contrasting climate zones of China. Agric. For. Meteorol., 268, 224-233.
Zhang, S., A. Tian, Q. Shi, et al., 2018: Statistical study of ULF waves in the magnetotail by THEMIS observations. Annales Geophysicae, 36(05), 1335-1346, https://doi.org/10.5194/angeo-36-1335-2018.
Zhang, S. and F. Tao, 2019: Improving rice development and phenology prediction across contrasting climate zones of China. Agric. For. Meteorol., 268, 224-233. https://doi.org/10.1016/j.agrformet.2019.01.019