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. |