Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2020.104880 |
Data assimilation of a dense wind profiler network and its impact on convective forecasting | |
Wang, Cheng1; Chen, Yaodeng1; Chen, Min2; Shen, Jie1 | |
2020-07-01 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2020 |
卷号 | 238 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
英文摘要 | Two momentum control variable schemes are typically used in most data assimilation systems: stream function and unbalanced velocity potential (psi/chi(u) scheme) and eastward and northward velocity (U/V scheme). The wind profiler radar (profiler) plays an important role in the expansion of meteorological observations networks. In this study, the impacts of two momentum control variable schemes on assimilating a dense wind profiler network are discussed based on the single profiler station observation tests and six convective rainfall events cycling experiments. Single profiler station observation tests indicate that profiler data assimilation is sensitive to control variables. The dynamical increments using U/V scheme contain more elaborate structure, which contributes to valuing the straightforward effects of profiler observations objectively. By contrast, unrealistic increments occur around the observation station in the experiment using psi/chi(u) scheme. Six continuous cycling experiments further demonstrate that, for convective rainfall events, experiment using U/V scheme leads to more skillful quantitative precipitation forecasts of convective rainfall. Diagnostic analysis results show that analysis using psi/chi(u) scheme prevents a good fitting to the profiler data, and accurate dynamical analysis containing abundant small-scale disturbances are the main reason for improving precipitation prediction of convective rainfall when U/V scheme is adopted. |
英文关键词 | Data assimilation Wind profiler radar observation Momentum control variables Numerical weather prediction |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000525323500013 |
WOS关键词 | VARIATIONAL DATA ASSIMILATION |
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/289271 |
专题 | 地球科学 |
作者单位 | 1.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Key Lab Meteorol Disaster,Minist Educ KLME, Joint Int Res Lab Climate & Environm Change ILCEC, Nanjing 210044, Peoples R China; 2.CMA, Inst Urban Meteorol, Beijing 100089, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Cheng,Chen, Yaodeng,Chen, Min,et al. Data assimilation of a dense wind profiler network and its impact on convective forecasting[J]. ATMOSPHERIC RESEARCH,2020,238. |
APA | Wang, Cheng,Chen, Yaodeng,Chen, Min,&Shen, Jie.(2020).Data assimilation of a dense wind profiler network and its impact on convective forecasting.ATMOSPHERIC RESEARCH,238. |
MLA | Wang, Cheng,et al."Data assimilation of a dense wind profiler network and its impact on convective forecasting".ATMOSPHERIC RESEARCH 238(2020). |
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