Cloud-resolving hurricane initialization and prediction through assimilation of doppler radar observations with an ensemble kalman filter
文献类型：期刊论文
| 作者 | Zhang, Fuqing1; Weng, Yonghui2,3,4; Sippel, Jason A.4; Meng, Zhiyong5; Bishop, Craig H.6 |
| 刊名 | Monthly weather review
 |
| 出版日期 | 2009-07-01 |
| 卷号 | 137期号:7页码:2105-2125 |
| ISSN号 | 0027-0644 |
| DOI | 10.1175/2009mwr2645.1 |
| 通讯作者 | Zhang, fuqing(fzhang@psu.edu) |
| 英文摘要 | This study explores the assimilation of doppler radar radial velocity observations for cloud-resolving hurricane analysis, initialization, and prediction with an ensemble kalman filter (enkf). the case studied is hurricane humberto (2007), the first landfalling hurricane in the united states since the end of the 2005 hurricane season and the most rapidly intensifying near-landfall storm in u. s. history. the storm caused extensive damage along the southeast texas coast but was poorly predicted by operational models and forecasters. it is found that the enkf analysis, after assimilating radial velocity observations from three weather surveillance radars-1988 doppler (wsr-88ds) along the gulf coast, closely represents the best-track position and intensity of humberto. deterministic forecasts initialized from the enkf analysis, despite displaying considerable variability with different lead times, are also capable of predicting the rapid formation and intensification of the hurricane. these forecasts are also superior to simulations without radar data assimilation or with a three-dimensional variational scheme assimilating the same radar observations. moreover, nearly all members from the ensemble forecasts initialized with enkf analysis perturbations predict rapid formation and intensification of the storm. however, the large ensemble spread of peak intensity, which ranges from a tropical storm to a category 2 hurricane, echoes limited predictability in deterministic forecasts of the storm and the potential of using ensembles for probabilistic forecasts of hurricanes. |
| WOS关键词 | SCALE DATA ASSIMILATION ; VARIATIONAL DATA ASSIMILATION ; ATMOSPHERIC DATA ASSIMILATION ; MOIST BAROCLINIC WAVES ; MESOSCALE PREDICTABILITY ; MULTIMODEL SUPERENSEMBLE ; TROPICAL CYCLOGENESIS ; MODEL EXPERIMENTS ; ERROR COVARIANCE ; FORECAST SYSTEM |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| WOS类目 | Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000268772700004 |
| 出版者 | AMER METEOROLOGICAL SOC |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2396949 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Zhang, Fuqing |
| 作者单位 | 1.Penn State Univ, Dept Meteorol, University Pk, PA 16802 USA 2.Chinese Acad Sci, Inst Atmospher Phys, Beijing, Peoples R China 3.Chinese Acad Sci, Grad Sch, Beijing, Peoples R China 4.Texas A&M Univ, Dept Atmospher Sci, College Stn, TX USA 5.Peking Univ, Sch Phys, Dept Atmospher Sci, Beijing 100871, Peoples R China 6.USN, Res Lab, Marine Meteorol Div, Monterey, CA USA |
| 推荐引用方式 GB/T 7714 | Zhang, Fuqing,Weng, Yonghui,Sippel, Jason A.,et al. Cloud-resolving hurricane initialization and prediction through assimilation of doppler radar observations with an ensemble kalman filter[J]. Monthly weather review,2009,137(7):2105-2125. |
| APA | Zhang, Fuqing,Weng, Yonghui,Sippel, Jason A.,Meng, Zhiyong,&Bishop, Craig H..(2009).Cloud-resolving hurricane initialization and prediction through assimilation of doppler radar observations with an ensemble kalman filter.Monthly weather review,137(7),2105-2125. |
| MLA | Zhang, Fuqing,et al."Cloud-resolving hurricane initialization and prediction through assimilation of doppler radar observations with an ensemble kalman filter".Monthly weather review 137.7(2009):2105-2125. |
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来源：中国科学院大学
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