Chen, M. X., and Coauthors, 2018: Enhanced weather research and forecasting in support of the Beijing 2022 Winter Olympic and Paralympic Games. WMO Bulletin, 67 (2), 58−61.
Deng, G., L. L. Dai, Y. S. Zhou, J. Chen, H. Q. Li, F. J. Chen, and J. Z. Wang, 2022: Evaluation and analysis of meteorological service for Beijing Winter Olympic Games supported by CMA high-resolution regional ensemble prediction system. Meteorological Monthly, 48 (2), 129−148, https://doi.org/10.7519/j.issn.1000-0526.2021.092901. (in Chinese with English abstract
Deng, G., J. Du, Y. S. Zhou, L. Yan, J. Chen, F. J. Chen, H. Q. Li, and J. Z. Wang, 2023: A comparison between 2D and 3D rescaling masks of initial condition perturbation in a 3-km storm-scale ensemble prediction system. Wea. Forecasting, 38 (1), 199−222, https://doi.org/10.1175/WAF-D-22-0073.1.
Di, D., R. L. Zhou, and R. Z. Lai, 2022: Parallax shift effect correction and analysis based on Fengyun-4A advanced imager. Acta Meteorologica Sinica, 80 (4), 632−642, https://doi.org/10.11676/qxxb2022.044. (in Chinese with English abstract
Du, J., and Coauthors, 2018: Ensemble methods for meteorological predictions. Handbook of Hydrometeorological Ensemble Forecasting, Q. Y. Duan et al., Eds., Springer, 1−52, https://doi.org/10.1007/978-3-642-40457-3_13-1.
Fan, Y. E., H. Q. Li, J. Chen, Z. Z. Xu, F. J. Chen, and G. Deng, 2022: Sensitivity experiments of a stochastic kinetic energy backscatter scheme within the CMA-REPS regional ensemble prediction system. Meteorological Monthly, 48 (9), 1077−1089, https://doi.org/10.7519/j.issn.1000-0526.2022.051201. (in Chinese with English abstract
Goger, B., M. W. Rotach, A. Gohm, I. Stiperski, and O. Fuhrer, 2016: Current challenges for numerical weather prediction in complex terrain: Topography representation and parameterizations. Proc. 2016 International Conference on High Performance Computing & Simulation (HPCS), Innsbruck, IEEE, 890−894, https://doi.org/10.1109/HPCSim.2016.7568428.
Joe, P., and Coauthors, 2010: Weather services, science advances, and the Vancouver 2010 Olympic and Paralympic Winter Games. Bull. Amer. Meteor. Soc., 91, 31−36, https://doi.org/10.1175/2009BAMS2998.1.
Joe, P., G. W. Lee, and K. Kim, 2023: The challenges of micro-nowcasting and the Women’s slope style event at the PyeongChang 2018 Olympic winter games. Meteorology, 2, 107−127, https://doi.org/10.3390/meteorology2010008.
Kim, K., W. Bang, E.-C. Chang, F. J. Tapiador, C.-L. Tsai, E. Jung, and G. Lee, 2021: Impact of wind pattern and complex topography on snow microphysics during International Collaborative Experiment for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018). Atmospheric Chemistry and Physics, 21 , 11 955−11 978, https://doi.org/10.5194/acp-21-11955-2021.
Lee, Y.-H., G. Lee, S. Joo, and K.-D. Ahn, 2018: Observational study of surface wind along a sloping surface over mountainous terrain during winter. Adv. Atmos. Sci., 35 (3), 276−284, https://doi.org/10.1007/s00376-017-7075-5.
Li, J., Z. G. Cheng, J. J. Zhang, and Y. J. Dou, 2020: Meteorological field experiment and preliminary analysis result in the winter Olympic venue in Xiaohaituo mountain. Meteorological Monthly, 46 (9), 1178−1188, https://doi.org/10.7519/j.issn.1000-0526.2020.09.005. (in Chinese with English abstract
Li, X. L., M. Charron, L. Spacek, and G. Candille, 2008: a regional ensemble prediction system based on moist targeted singular vectors and stochastic parameter perturbations. Mon. Wea. Rev., 136 (2), 443−462, https://doi.org/10.1175/2007MWR2109.1.
Pokhrel, R., and H. Lee, 2019: Comparison of Gaussian plume model and lagrangian particle model for the application of coastal air quality modelling. American Journal of Environmental and Resource Economics, 4 (4), 152−158, https://doi.org/10.11648/j.ajere.20190404.16.
Roberts, N., and Coauthors, 2023: IMPROVER: The new probabilistic postprocessing system at the met office. Bull. Amer. Meteor. Soc., 104, E680−E697, https://doi.org/10.1175/BAMS-D-21-0273.1.
Scheuerer, M., and G. König, 2014: Gridded, locally calibrated, probabilistic temperature forecasts based on ensemble model output statistics. Quart. J. Roy. Meteor. Soc., 140, 2582−2590, https://doi.org/10.1002/qj.2323.
Shen, X. S., X. J. Zhou, J. S. Xue, D. H. Chen, Y. J. Zhang, and Q. L. Wan, 2013: GRAPES Numerical Prediction System for Heavy Rainfall. China Meteorological Press, 186 pp. (in Chinese)
Sports Department of Beijing Winter Olympic Organizing Committee, 2020: Beijing 2022 Weather and Wind Analysis Report. China Meteorological Press, 26 pp. (in Chinese)
Su, Y., X. S. Shen, Z. T. Chen, and H. L. Zhang, 2018: A study on the three-dimensional reference atmosphere in GRAPES_GFS: Theoretical design and ideal test. Acta Meteorologica Sinica, 76 (2), 241−254, https://doi.org/10.11676/qxxb2017.097. (in Chinese with English abstract
Su, Y., X. S. Shen, H. L. Zhang, and Y. Z. Liu, 2020: A study on the three-dimensional reference atmosphere in GRAPES_GFS: Constructive reference state and real forecast experiment. Acta Meteorologica Sinica, 78 (6), 962−971, https://doi.org/10.11676/qxxb2020.075. (in Chinese with English abstract
Tong, H., J. L. Hu, and Y. T. Zhang, 2020: Improvement and application of post-processing technology in GRAPES model. Meteorological Science and Technology, 48 (4), 511−517, https://doi.org/10.19517/j.1671-6345.20190308. (in Chinese with English abstract
Tsai, C. L., K. Kim, Y. C. Liou, and G. W. Lee, 2023: High-resolution 3D winds derived from a modified WISSDOM synthesis scheme using multiple Doppler lidars and observations. Atmospheric Measurement Techniques, 16, 845−869, https://doi.org/10.5194/amt-16-845-2023.
Veenhuis, B. A., 2013: Spread calibration of ensemble MOS forecasts. Mon. Wea. Rev., 141, 2467−2482, https://doi.org/10.1175/MWR-D-12-00191.1.
Wang, W. G., W. J. Shaw, T. E. Seiple, J. P. Rishel, and Y. L. Xie, 2008. An evaluation of a diagnostic wind model (CALMET). J. Appl. Meteorol. Climatol., 47 (6), 1739−1756, https://doi.org/10.1175/2007JAMC1602.1.
Xia, J. J., and Coauthors, 2020: Machine learning−based weather support for the 2022 Winter Olympics. Adv. Atmos. Sci., 37 (9), 927−932, https://doi.org/10.1007/s00376-020-0043-5.
Xin, Y., and H. W. Chen, 2014: Influence of CALMET parameter adjustment in the XJRUC coupling of CALMET over Dabanchen-Xiaocaohu wind area. Plateau Meteorology, 33 (6), 1674−1686, https://doi.org/10.7522/j.issn.1000-0534.2013.00191. (in Chinese with English abstract
Xu, Z. F., and R. C. Wang, 2022: Multiscale separation of background error for multiscale filtering in CMA-MESO 3km resolution system. Meteorological Monthly, 48 (12), 1525−1538, https://doi.org/10.7519/j.issn.1000-0526.2022.081501. (in Chinese with English abstract
Xu, Z. F., Y. Wu, J. D. Gong, and Y. Cai, 2021: Assimilation of 2 m relative humidity observations in CMA-MESO 3DVar system. Acta Meteorologica Sinica, 79 (6), 943−955, https://doi.org/10.11676/qxxb2021.060. (in Chinese with English abstract
Xu, Z. F., L. Zhang, R. C. Wang, and J. D. Gong, 2023: Effect of 2-m temperature data assimilation in the CMA-MESO 3DVAR system. Journal of Meteorological Research, 37 (2), 218−233, https://doi.org/10.1007/s13351-023-2115-9.
Xue, J. S., and D. H. Chen, 2008: Scientific Design and Application of GRAPES Numerical Prediction System. Science Press, 383 pp. (in Chinese)
Yang, L., M. X. Chen, X. L. Wang, L. Y. Song, M. L. Yang, R. Qin, C. L. Cheng, and S. T. Li, 2021a: Classification of precipitation type in North China using model-based explicit fields of hydrometeors with modified thermodynamic conditions. Wea. Forecasting, 36 (1), 91−107, https://doi.org/10.1175/WAF-D-20-0005.1.
Yang, L., G. Q. Nan, M. X. Chen, L. Y. Song, R. T. Liu, C. L. Cheng, and W. H. Cao, 2021b: The construction and comparison of high resolution precipitation type prediction models based on three machine learning methods. Acta Meteorologica Sinica, 79 (6), 1022−1034, https://doi.org/10.11676/qxxb2021.059. (in Chinese with English abstract
Zhang, H. L., X. S. Shen, and Y. Su., 2022: A semi-implicit semi-Lagrangian time integration schemes with a predictor and a corrector and their applications in CMA-GFS. Acta Meteorologica Sinica, 80 (2), 280−288, https://doi.org/10.11676/qxxb2022.021. (in Chinese with English abstract
Zhang, Y. T., H. Tong, and J. Sun, 2020: Application of a bias correction method to meteorological forecast for the Pyeongchang Winter Olympic Games. Journal of Applied Meteorological Science, 31 (1), 27−41, https://doi.org/10.11898/1001-7313.20200103. (in Chinese with English abstract
Zhi, X. F., and W. Huang, 2019: Multimodel ensemble forecasts of surface air temperature and precipitation over China by using Kalman filter. Transactions of Atmospheric Sciences, 42 (2), 197−206, https://doi.org/10.13878/j.cnki.dqkxxb.20181108001. (in Chinese with English abstract
Zhi, X. F., B. Y. Cui, Y. Ji, S. P. Zhu, Z. Q. Ma, and X. W. Zhang, 2022: Prediction of water level in urban waterlogging area based on deep learning approach. Proc. 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA), Dalian, IEEE, 548−551, https://doi.org/10.1109/AEECA55500.2022.9919102.