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DOI | 10.1029/2018JD028494 |
Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model | |
Wang, Haoliang1,2; Liu, Yubao2,3; Zhao, Tianliang1; Liu, Yuewei2; Xu, Mei2; Shen, Si2; Jiang, Yin4; Yang, Honglong4; Feng, Shuanglei3 | |
2018-09-16 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2018 |
卷号 | 123期号:17页码:9652-9673 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; USA |
英文摘要 | In this study, a lightning data assimilation method based on the time-lagged ensembles for predicting severe convection is presented. With the lightning data assimilation scheme, the background error covariances are computed using time-lagged ensembles, which consist of deterministic forecasts from eight forecast cycles initialized every 3hr. Pseudo-observations of graupel mixing ratio (q(g)) are retrieved from total lightning rates by utilizing empirical vertical profiles obtained from the simulation results of the previous forecast cycles, and the corresponding observation errors are estimated according to the uncertainties in the lightning observations and the empirical vertical profiles of q(g). The increments of the model state variables are computed with the Kalman gain matrices and are continuously ingested into the Weather Research and Forecasting model via nudging terms acting on the prognostic equations over each time step during model integration. The effect of the lightning data assimilation scheme on convection analysis and forecast was assessed through a case study of a severe convective event, which took place in the Guangdong of China. Assimilating lightning data recovered many of the observed convective cells, suppressed the spurious convection, and corrected the displacement errors of the convective systems. Quantitative verifications indicate that forecast skills were improved mainly in the convective regions with the impact of assimilating lightning data on stratiform regions being overall less effective. |
英文关键词 | Data assimilation Lightning data Convection-allowing scales Time-lagged ensembles EnKF |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000445617500042 |
WOS关键词 | KALMAN FILTER ASSIMILATION ; BACKGROUND-ERROR COVARIANCES ; STORM-SCALE ANALYSES ; FLASH-EXTENT DATA ; PART I ; SIMULATED ELECTRIFICATION ; BULK MICROPHYSICS ; PRECIPITATION FORECASTS ; EXPLICIT FORECASTS ; TORNADO OUTBREAK |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/33371 |
专题 | 气候变化 |
作者单位 | 1.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing, Jiangsu, Peoples R China; 2.Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA; 3.China Elect Power Res Inst, Beijing, Peoples R China; 4.Shenzhen Municipal, Meteorol Bur, Shenzhen, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Haoliang,Liu, Yubao,Zhao, Tianliang,et al. Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(17):9652-9673. |
APA | Wang, Haoliang.,Liu, Yubao.,Zhao, Tianliang.,Liu, Yuewei.,Xu, Mei.,...&Feng, Shuanglei.(2018).Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(17),9652-9673. |
MLA | Wang, Haoliang,et al."Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.17(2018):9652-9673. |
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