Mixture probabilistic model for precipitation ensemble forecasting
文献类型：期刊论文
| 作者 | Wu, Yajing1,2 ; Yang, Xuebing1; Zhang, Wensheng1; Kuang, Qiuming3
|
| 刊名 | QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
 |
| 出版日期 | 2019-09-13 |
| 页码 | 19 |
| ISSN号 | 0035-9009 |
| 关键词 | ensemble forecast post-processing precipitation probabilistic forecast |
| DOI | 10.1002/qj.3637 |
| 通讯作者 | Yang, Xuebing(yangxuebing2013@ia.ac.cn) ; Zhang, Wensheng(zhangwenshengia@hotmail.com) |
| 英文摘要 | Statistical post-processing approaches are widely employed to construct improved probabilistic meteorological forecasts from numerical weather prediction. However, generating calibrated and sharp probabilistic forecasts is challenging. In this article, a post-processing approach, Mixture Probabilistic Model (MPM), is proposed to calibrate probabilistic ensemble forecasts subject to sharpness. In particular, the proposed MPM is applied to precipitation forecasting. First, the Censored and Shifted Gamma (CSG0) distribution is considered as the probability density function (PDF) for precipitation. Then, the predictive PDF of MPM is mixed by the individual PDFs which are fitted from raw ensemble members. Finally, to estimate optimal weight parameters for the mixture of individual PDFs, the Dirichlet distribution is utilized and the skills of the mixture model and individuals are both taken into consideration. The proposed MPM was tested using Innsbruck ensemble precipitation data and 6 h accumulated precipitation ensemble forecast data in east China from August to November 2017. Compared with raw forecasts and three state-of-the-art post-processing approaches, MPM showed improved performance for all verification scores. The quantitative and qualitative analyses of results in both cases indicate the potential and effectiveness of MPM for precipitation ensemble forecasting. |
| WOS关键词 | CALIBRATION ; PREDICTION ; WEATHER |
| 资助项目 | National Natural Science Foundation of China[61532006] ; National Natural Science Foundation of China[61602482] ; National Natural Science Foundation of China[U1636220] |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| 出版者 | WILEY |
| WOS记录号 | WOS:000486524400001 |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27278]  |
| 专题 | 精密感知与控制研究中心_人工智能与机器学习 |
| 通讯作者 | Yang, Xuebing; Zhang, Wensheng |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.China Meteorol Adm, Publ Meteorol Serv Ctr, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Yajing,Yang, Xuebing,Zhang, Wensheng,et al. Mixture probabilistic model for precipitation ensemble forecasting[J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY,2019:19. |
| APA | Wu, Yajing,Yang, Xuebing,Zhang, Wensheng,&Kuang, Qiuming.(2019).Mixture probabilistic model for precipitation ensemble forecasting.QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY,19. |
| MLA | Wu, Yajing,et al."Mixture probabilistic model for precipitation ensemble forecasting".QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY (2019):19. |
入库方式： OAI收割
来源：自动化研究所
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