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Yubao Liu
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Paper Publications
[1] Wen W., Liu* Y., Sun R., and Liu Yue, 2022: Research on Anomaly Detection of Wind Farm SCADA Wind Speed Data. Energies, 2022, 15, 5869. https://doi.org/10.3390/en15165869
[2] Lu Z., Han* Y., Liu* Y., Liu S., Liu Z., Tang Y., and Jing W., 2022: An improvement of wind gust estimate (WGE) method for squall lines. Geomatics, Natural Hazards and Risk.13:1, 993-1013, DOI: 10.1080/19475705.2022.2064773.
[3] Zhou* Y., Liu* Y., Huo Z. and Li Y., 2022: Preliminary evaluation of FY-4A visible radiance data assimilation by the WRF/DART-RTTOV system for a tropical storm case. Geosci. Model Dev., 15, 7397–7420, 2022 https://doi.org/10.5194/gmd-15-7397-2022.
[4] Li Y., Liu* Y., Sun R., Guo F., Xu X., and Xu H, 2022: Convective storm VIL and lightning nowcasting using satellite and weather radar measurements based on multi-task learning models. Advances in Atmospheric Sciences. (In press)
[5] Hua S., Chen* B., Liu* Y., Chen G., Yang Y., Dong X., Zhao Z., Gao Y., Zhou X., Zhong R. and Duan J., 2022: Evaluation of the ice particle simulation of microphysics schemes with aircraft measurements of a stratiform cloud in North China. J. Atmos. Sci. (submitted).
[6] Li Y., Liu* Y., Shi Y., Chen B., Zeng F., Huo Z. and Fan H., 2022: Probablistic convective initiation nowcasting using Himawari-8 AHI with explanable deep learning models. Mon. Wea. Rev. (submitted)
[7] Wang H., Yuan S., Liu* Y., Li. Yang, 2022: Comparison of the WRF-FDDA-Based Radar Reflectivity and Lightning Data Assimilation for Short-Term Precipitation and Lightning Forecasts of Severe Convection, Remote Sensing, (submitted).
[8] Fan H., Liu* Y., Li Y., Liu Yue., Duan J., Li L., Z. Huo, 2022: A deep learning method for predicting lower troposphere temperature using surface analysis. Boundary-Layer Meteorology. (submitted)
[9] Zhou Y., and Liu Y., 2022: Impact of FY-4A visible radiance on forecast of cloud and precipitation with a partical filter. Mon. Wea. Rev. (submitted)
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