Author:
Gao Shibo,Yu Haiqiu,Ren Chuanyou,Liu Limin,Min Jinzhong
Publisher
Springer Science and Business Media LLC
Reference60 articles.
1. Barker, D., and Coauthors, 2012: The weather research and forecasting model’s community variational/ensemble data assimilation system: WRFDA. Bull. Amer. Meteor. Soc., 93, 831–843, https://doi.org/10.1175/BAMS-D-11-00167.1.
2. Brewster, K. A., M. Hu, M. Xue, and J. Gao, 2005: Efficient assimilation of radar data at high resolution for short range numerical weather prediction. International Symp. on Nowcasting and Very Short Range Forecasting, Toulouse, France, World Weather Res. Prog., CDROM 3. 06.
3. Buehner, M., 2005: Ensemble-derived stationary and flow-dependent background-error covariances: Evaluation in a quasi-operational NWP setting. Quart. J. Roy. Meteor. Soc., 131, 1013–1043, https://doi.org/10.1256/qj.04.15.
4. Buehner, M., P. L. Houtekamer, C. Charette, H. L. Mitchell, and B. He, 2010a: Intercomparison of variational data assimilation and the ensemble Kalman filter for global deterministic NWP. Part I: Description and single-observation experiments. Mon. Wea. Rev., 138, 1550–1566, https://doi.org/10.1175/2009MWR3157.1.
5. Buehner, M., P. L. Houtekamer, C. Charette, H. L. Mitchell, and B. He, 2010b: Intercomparison of variational data assimilation and the ensemble Kalman filter for global deterministic NWP. Part II: One-Month experiments with real observations. Mon. Wea. Rev., 138, 1567–1586, https://doi.org/10.1175/2009MWR3158.1.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献