Bouttier, F., B. Vié, O. Nuissier, and L. Raynaud, 2012: Impact of stochastic physics in a convection-permitting ensemble. Mon. Wea. Rev., 140(11), 3706−3721, https://doi.org/10.1175/MWR-D-12-00031.1.
Buizza, R., and T. N. Palmer, 1995: The singular-vector structure of the atmospheric global circulation. J. Atmos. Sci., 52, 1434−1456, https://doi.org/10.1175/1520-0469(1995)052<1434:TSVSOT>2.0.CO;2.
Buizza, R., M. Milleer, and T. N. Palmer, 1999: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system. Quart. J. Roy. Meteor. Soc., 125, 2887−2908, https://doi.org/10.1002/qj.49712556006.
Buizza, R., P. L. Houtekamer, G. Pellerin, Z. Toth, Y. J. Zhu, and M. Z. Wei, 2005: A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems. Mon. Wea. Rev., 133, 1076−1097, https://doi.org/10.1175/MWR2905.1.
Cannon, A. J., and P. H. Whitfield, 2002: Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models. J. Hydrol., 259, 136−151, https://doi.org/10.1016/S0022-1694(01)00581-9.
Chen, D. H., and X. S. Shen, 2006: Recent progress on GRAPES research and application. Journal of Applied Meteorological Science, 17(6), 773−777, https://doi.org/10.3969/j.issn.1001-7313.2006.06.014. (in Chinese with English abstract
Chen, J., J. S. Xue, and H. Yan, 2005: A new initial perturbation method of ensemble mesoscale heavy rain prediction. Chinese Journal of Atmospheric Sciences, 29(5), 717−726. (in Chinese with English abstract)
Chen, K. K., L. Y. Song, L. Yang, M. X. Chen, M. Chen, L. Han, and W. H. Cao, 2020: Research and application of a three-dimensional interpolation method for high-resolution temperature in complex terrain based on gaussian fuzzy. Plateau Meteorology, 39(2), 367−377, https://doi.org/10.7522/j.issn.1000-0534.2019.00108. (in Chinese with English abstract
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, 58−61.
Cheng, C. L., M. Chen, M. X. Chen, F. Gao, L. Y. Song, R. Qin, L. Yang, and Y. Wang, 2019: Comparative experiments on two high spatiotemporal resolution blending algorithms for quantitative precipitation nowcasting. Acta Meteorologica Sinica, 77(4), 701−714, https://doi.org/10.11676/qxxb2019.017. (in Chinese with English abstract
Clark, A. J., 2017: Generation of ensemble mean precipitation forecasts from convection-allowing ensembles. Wea. Forecasting, 32(4), 1569−1583, https://doi.org/10.1175/WAF-D-16-0199.1.
Clark, A. J., W. A. Gallus Jr., M. Xue, and F. Y. Kong, 2009: A comparison of precipitation forecast skill between small convection-allowing and large convection-parameterizing ensembles. Wea. Forecasting, 24(4), 1121−1140, https://doi.org/10.1175/2009WAF2222222.1.
Clark, A. J., W. A. Gallus Jr., and M. L. Weisman, 2010: Neighborhood-based verification of precipitation forecasts from convection-allowing NCAR WRF Model simulations and the operational NAM. Wea. Forecasting, 25, 1495−1509, https://doi.org/10.1175/2010WAF2222404.1.
Dance, S., E. Ebert, and D. Scurrah, 2010: Thunderstorm strike probability nowcasting. J. Atmos. Oceanic Technol., 27, 79−93, https://doi.org/10.1175/2009JTECHA1279.1.
Deng, G., and Coauthors, 2010: Development of mesoscale ensemble prediction system at national meteorological center. Journal of Applied Meteorological Science, 21(5), 513−523, https://doi.org/10.3969/j.issn.1001-7313.2010.05.001. (in Chinese with English abstract
Gao, L., J. Chen, J. W. Zheng, and Q. L. Chen, 2019: Progress in researches on ensemble forecasting of extreme weather based on numerical models. Advances in Earth Science, 34(7), 706−716, https://doi.org/10.11867/j.issn.1001-8166.2019.07.0706. (in Chinese with English abstract
Gneiting, T., and A. E. Raftery, 2007: Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association, 102, 359−378, https://doi.org/10.1198/016214506000001437.
Haiden, T., A. Kann, C. Wittmann, G. Pistotnik, B. Bica, and C. Gruber, 2011: The Integrated Nowcasting through Comprehensive Analysis (INCA) system and its validation over the Eastern Alpine region. Wea. Forecasting, 26, 166−183, https://doi.org/10.1175/2010WAF2222451.1.
Hamill, T. M., 2001: Interpretation of rank histograms for verifying ensemble forecasts. Mon. Wea. Rev., 129, 550−560, https://doi.org/10.1175/1520-0493(2001)129<0550:IORHFV>2.0.CO;2.
He, J., M. Chen, J. Q. Zhong, and X. Y. Hong, 2019: A study of three-dimensional radar reflectivity mosaic assimilation in the regional forecasting model for North China. Acta Meteorologica Sinica, 77, 210−232, https://doi.org/10.11676/qxxb2019.005. (in Chinese with English abstract
Hersbach, H., 2000: Decomposition of the continuous ranked probability score for ensemble prediction systems. Wea. Forecasting, 15, 559−570, https://doi.org/10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2.
Holton, J. R., 2004: An Introduction to Dynamic Meteorology. 4th ed. Academic Press, 535 pp.
Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126, 796−811, https://doi.org/10.1175/1520-0493(1998)126<0796:DAUAEK>2.0.CO;2.
Houtekamer, P. L., L. Lefaivre, J. Derome, H. Ritchie, and H. L. Mitchell, 1996: A system simulation approach to ensemble prediction. Mon. Wea. Rev., 124, 1225−1242, https://doi.org/10.1175/1520-0493(1996)124<1225:ASSATE>2.0.CO;2.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res.: Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944.
Johnson, A., and Coauthors, 2014: Multiscale characteristics and evolution of perturbations for warm season convection-allowing precipitation forecasts: Dependence on background flow and method of perturbation. Mon. Wea. Rev., 142(3), 1053−1073, https://doi.org/10.1175/MWR-D-13-00204.1.
Kain, J. S., and J. M. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain-Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, K. A. Emanuel and D. J. Raymond, Eds., American Meteorological Society, 165−170,
Kiktev, D., and Coauthors, 2017: FROST-2014: The sochi winter olympics international project. Bull. Amer. Meteor. Soc., 98(9), 1908−1929, https://doi.org/10.1175/BAMS-D-15-00307.1.
Kim, S. H., and H. M. Kim, 2017: Effect of considering sub-grid scale uncertainties on the forecasts of a high-resolution limited area ensemble prediction system. Pure Appl. Geophys., 174(5), 2021−2037, https://doi.org/10.1007/s00024-017-1513-2.
Kühnlein, C., C. Keil, G. C. Craig, and C. Gebhardt, 2014: The impact of downscaled initial condition perturbations on convective-scale ensemble forecasts of precipitation. Quart. J. Roy. Meteor. Soc., 140(682), 1552−1562, https://doi.org/10.1002/qj.2238.
Leith, C. E., 1974: Theoretical skill of Monte Carlo forecasts. Mon. Wea. Rev., 102, 409−418, https://doi.org/10.1175/1520-0493(1974)102<0409:TSOMCF>2.0.CO;2.
Li, Z. C., and D. H. Chen, 2002: The development and application of the operational ensemble prediction system at national meteorological center. Journal of Applied Meteorological Science, 13(1), 1−15. (in Chinese with English abstract)
Lorenz, E. N., 1965: A study of the predictability of a 28-variable atmospheric model. Tellus, 17(3), 321−333, https://doi.org/10.3402/tellusa.v17i3.9076.
Lorenz, E. N., 1969: The predictability of a flow which possesses many scales of motion. Tellus, 21, 289−307, https://doi.org/10.1111/j.2153-3490.1969.tb00444.x.
Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys., 20, 851−875, https://doi.org/10.1029/RG020i004p00851.
Molteni, F., R. Buizza, T. N. Palmer, and T. Petroliagis, 1996: The ECMWF ensemble prediction system: Methodology and validation. Quart. J. Roy. Meteor. Soc., 122, 73−119, https://doi.org/10.1002/qj.49712252905.
Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747−1763, https://doi.org/10.1175/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2.
Peralta, C., Z. Ben Bouallègue, S. E. Theis, C. Gebhardt, and M. Buchhold, 2012: Accounting for initial condition uncertainties in COSMO-DE-EPS. J. Geophys. Res.: Atmos., 117(D7), D07108, https://doi.org/10.1029/2011JD016581.
Song, L. Y., M. X. Chen, C. L. Cheng, F. Gao, and M. Chen, 2019b: Characteristics of summer QPE error and a climatological correction method over Beijing-Tianjin-Hebei region. Acta Meteorologica Sinica, 77(3), 497−515, https://doi.org/10.11676/qxxb2019.022. (in Chinese with English abstract
Song, L. Y., M. X. Chen, F. Gao, C. L. Cheng, M. Chen, L. Yang, and Y. Wang, 2019a: Elevation influence on rainfall and a parameterization algorithm in the Beijing area. J. Meteor. Res., 33(6), 1143−1156, https://doi.org/10.1007/s13351-019-9072-3.
Stensrud, D. J., and N. Yussouf, 2007: Reliable probabilistic quantitative precipitation forecasts from a short-range ensemble forecasting system. Wea. Forecasting, 22, 3−17, https://doi.org/10.1175/WAF968.1.
Suklitsch, M., A. Kann, and B. Bica, 2015: Towards an integrated probabilistic nowcasting system (En-INCA). Advances in Science and Research, 12, 51−55, https://doi.org/10.5194/asr-12-51-2015.
Talagrand, O., R. Vautard, and B. Strauss, 1997: Evaluation of probabilistic prediction systems. Proc. Workshop on Predictability, Reading, United Kingdom, ECMWF, 1−25.
Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Mon. Wea. Rev., 136, 5095−5115, https://doi.org/10.1175/2008MWR2387.1.
Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of perturbations. Bull. Amer. Meteor. Soc., 74, 2317−2330, https://doi.org/10.1175/1520-0477(1993)074<2317:EFANTG>2.0.CO;2.
Wang, Y., and Z. H. Yan, 2007: Effect of different verification schemes on precipitation verification and assessment conclusion. Meteorological Monthly, 33(12), 53−61, https://doi.org/10.3969/j.issn.1000-0526.2007.12.008. (in Chinese with English abstract
Weidle, F., Y. Wang, and G. Smet, 2016: On the impact of the choice of global ensemble in forcing a regional ensemble system. Wea. Forecasting, 31(2), 515−530, https://doi.org/10.1175/WAF-D-15-0102.1.
Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed., Academic Press, 467 pp.
Xie, Y. H., S. Y. Fan, M. Chen, J. C. Shi, J. Q. Zhong, and X. Y. Zhang, 2019: An assessment of satellite radiance data assimilation in RMAPS. Remote Sensing, 11, 54, https://doi.org/10.3390/rs11010054.
Yang, L., M. Chen, M. X. Chen, F. Gao, R. Qin, L. Y. Song, and C. L. Cheng, 2019: Fusion of 3D high temporal and spatial resolution wind field and its application in nowcasting of severe convective weather. Acta Meteorologica Sinica, 77(2), 243−255. (in Chinese with English abstract)
Yang, L., M. X. Chen, X. L. Wang, L. Y. Song, M. L. Yang, R. Qin, C. L. Cheng, and S. T. Li, 2021: Classification of precipitation type in North China using model-based explicit fields of hydrometeors with modified thermodynamic conditions. Wea. Forecasting, 36, 91−107, https://doi.org/10.1175/WAF-D-20-0005.1.
Yang, L., L. Y. Song, H. Jing, M. X. Chen, W. H. Cao, and J. K. Wu, 2022: Fusion prediction and correction technique for high-resolution wind field in Winter Olympic Games area under complex terrain. Meteorological Monthly, 48(2), 162−176, https://doi.org/10.7519/j.issn.1000-0526.2021.092902. (in Chinese with English abstract
Zhang, H. B., J. Chen, X. F. Zhi, Y. L. Li, and Y. Sun, 2014: Study on the application of GRAPES regional ensemble prediction system. Meteorological Monthly, 40, 1076−1087, https://doi.org/10.7519/j.issn.1000-0526.2014.09.005. (in Chinese with English abstract
Zhang, H. B., Y. H. Li, S. Y. Fan, J. Q. Zhong, and B. Lu, 2017: Study on initial perturbation construction method for regional ensemble forecast based on dynamical downscaling. Meteorological Monthly, 43(12), 1461−1472, https://doi.org/10.7519/j.issn.1000-0526.2017.12.002. (in Chinese with English abstract
Zhang, H. B., S. Y. Fan, M. Chen, and X. Sun, 2019: Study on a synthetic model perturbation method based on SKEB and multi physics for regional ensemble forecast. Meteorological Monthly, 45(1), 17−28, https://doi.org/10.7519/j.issn.1000-0526.2019.01.002. (in Chinese with English abstract
Zhang, H. B., Y. X. Ji, M. Chen, X. Sun, and Y. Xia, 2022: Study on the EDA initial condition perturbation method for ensemble prediction system based on observation perturbation. Meteorological Monthly, 48(4), 406−417, https://doi.org/10.7519/j.issn.1000-0526.2021.102301. (in Chinese with English abstract
Zhang, R. H., and X. S. Shen, 2008: Development of new generation operational numerical prediction system GRAPES. Chinese Science Bulletin, 53(20), 2393−2395. (in Chinese)
Zhong, Y. L., J. Chen, J. Wang, K. Lü, and X. L. Li, 2017: Evaluation of the forecast for landed Typhoons by GRAPES-REPS regional ensemble prediction system. Journal of Tropical Meteorology, 33(6), 953−964, https://doi.org/10.16032/j.issn.1004-4965.2017.06.016. (in Chinese with English abstract