Prior-Guided gated convolutional networks for rainstorm forecasting
文献类型：期刊论文
| 作者 | Zhang, Tong1; Liu, Jie2; Gao, Chulin1; Wang, Peixiao1,3; Leng, Liang4; Xiao, Yanjiao4 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2024-04-01 |
| 卷号 | 633页码:20 |
| 关键词 | Rainstorm events Prior -informed rainstorm forecasting Substantial derivative Spatio-temporal patterns |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2024.130962 |
| 通讯作者 | Liu, Jie(ise_liuj@ujn.edu.cn) |
| 英文摘要 | Accurate rainstorm forecasting is crucial for the sustainable development of human society. Recently, machine learning-based rainstorm prediction methods have shown promising results. However, these methods often fail to adequately consider the prior knowledge of rainstorms and do not explicitly account for the dynamic spatiotemporal patterns of rainstorm events. This study introduces a novel end-to-end prior-informed rainstorm forecasting model that incorporates both fundamental physical priors and the spatio-temporal development patterns of rainstorms. The model utilizes a gated convolutional encoder-decoder network to effectively represent the spatio-temporal patterns of rainstorm events. A key component of the representation network is the Substantial Derivative-GuIded gated convolutional Unit (SDGiU), which updates latent states under the constraints of physical priors. Additionally, an integrated loss function is designed to minimize reconstruction errors on multiple scales and facilitate the generation of forecasts that reproduce the actual spatio-temporal patterns of rainstorm formation, development and dissipation. Experimental results on two reanalysis datasets show that the proposed forecasting model outperforms competing state-of-the-art baselines by at least 19.7% (15.0%) in overall Critical Success Index (Heidke Skill Score). Qualitative analysis indicates that the proposed model can generate predictions that are both physically consistent and spatially-temporally coherent. |
| WOS关键词 | WEATHER ; RAINFALL ; MODELS |
| 资助项目 | Joint Research Program for Enhancing Meteorological Capabilities by the China Meteorological Administration[22NLTSY015] ; Hubei Provincial Natural Science Foundation of China[2022CFD012] ; Key R&D Program of Hubei Province[2023BCB119] ; China National Postdoctoral Support Program for Innovative Talents[BX20230360] ; Open Project Fund of China Meteorological Administration Basin Heavy Rainfall Key Laboratory[2023BHR-Y13] ; Open Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University[23I03] |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001203872800001 |
| 出版者 | ELSEVIER |
| 资助机构 | Joint Research Program for Enhancing Meteorological Capabilities by the China Meteorological Administration ; Hubei Provincial Natural Science Foundation of China ; Key R&D Program of Hubei Province ; China National Postdoctoral Support Program for Innovative Talents ; Open Project Fund of China Meteorological Administration Basin Heavy Rainfall Key Laboratory ; Open Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/204452]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu, Jie |
| 作者单位 | 1.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China 2.Univ Jinan, Sch Informat Sci & Engn, Jinan 250022, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.China Meteorol Adm, China Meteorol Adm Basin Heavy Rainfall Key Lab, Inst Heavy Rain, Hubei Key Lab Heavy Rain Monitoring & Warning Res, Wuhan 430205, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Tong,Liu, Jie,Gao, Chulin,et al. Prior-Guided gated convolutional networks for rainstorm forecasting[J]. JOURNAL OF HYDROLOGY,2024,633:20. |
| APA | Zhang, Tong,Liu, Jie,Gao, Chulin,Wang, Peixiao,Leng, Liang,&Xiao, Yanjiao.(2024).Prior-Guided gated convolutional networks for rainstorm forecasting.JOURNAL OF HYDROLOGY,633,20. |
| MLA | Zhang, Tong,et al."Prior-Guided gated convolutional networks for rainstorm forecasting".JOURNAL OF HYDROLOGY 633(2024):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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