[1]黄启桥,麦雄发,李玲,等.基于ConvLSTM的广西短临降水预报[J].气象研究与应用,2021,42(04):44-49.[doi:10.19849/j.cnki.CN45-1356/P.2021.4.08]
 Huang Qiqiao,Mai Xiongfa,Li Ling,et al.Forecast of short-term precipitation in Guangxi based on ConvLSTM[J].Journal of Meteorological Research and Application,2021,42(04):44-49.[doi:10.19849/j.cnki.CN45-1356/P.2021.4.08]
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基于ConvLSTM的广西短临降水预报()
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气象研究与应用[ISSN:1673-8411/CN:45-1356/P]

卷:
第42卷
期数:
2021年04期
页码:
44-49
栏目:
研究论文
出版日期:
2022-01-27

文章信息/Info

Title:
Forecast of short-term precipitation in Guangxi based on ConvLSTM
作者:
黄启桥1 麦雄发1 李玲2 唐菁2 唐飞笼1
1. 南宁师范大学数学与统计学院,南宁 530001;
2. 南宁师范大学地理科学与规划学院,南宁 530001
Author(s):
Huang Qiqiao1 Mai Xiongfa1 Li Ling2 Tang Jing2 Tang Feilong1
1. School of Mathematics and Statistics, Nanning Normal University, Nanning 530001, China;
2. School of Geography and Planning, Nanning Normal University, Nanning 530001, China
关键词:
短临预报雷达回波ConvLSTM光流法
Keywords:
nowcastingradar echoConvLSTMoptical flow
分类号:
P457.6
DOI:
10.19849/j.cnki.CN45-1356/P.2021.4.08
摘要:
针对传统雷达回波外推算法在快速增长或消散降水过程预报精度较低的问题,利用华南雷达回波拼图资料数据,建立ConvLSTM回波外推模型,对广西区域范围进行短临降水预报研究。采用气象业务中的正确率(POD)、临界成功指数(CSI)及误报率(FAR)评判标准检验预报模型,并将ConvLSTM与光流法的预报结果进行对比分析。结果表明,ConvLSTM模型的CSI、POD分别比光流法提高0.06和0.059,而FAR下降了0.058。ConvLSTM方法比光流法的回波外推预报准确率高,该方法可为广西短临降水预报提供新的参考。
Abstract:
Aiming at the problem of low prediction accuracy of traditional radar echo extrapolation algorithms in the process of rapid growth or dissipation of precipitation, the paper established a ConvLSTM echo extrapolation model by using the South China radar echo mosaic data to study short-term precipitation in Guangxi. The accuracy rate(POD), critical success index(CSI)and false alarm rate(FAR)evaluation models in meteorological services were used, and ConvLSTM was compared with the optical flow method. The experimental results show that the CSI and POD of the ConvLSTM prediction result are 0.06 and 0.059 higher than that of the optical flow method, respectively, while the FAR decreases by 0.058. This shows that ConvLSTM has a higher accuracy of echo extrapolation than the optical flow method, which can provide a new method reference for the forecast of short-term precipitation in Guangxi.

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备注/Memo

备注/Memo:
收稿日期:2021-07-05。
基金项目:广西自然科学基金项目(2018GXNSFAA294079)、广西教育厅科研基础能力提升项目(2021KY1751)、北部湾环境演变与资源利用教育部重点实验室(南宁师范大学)开放基金项目(NNNU-KLOP-K2103)
作者简介:黄启桥(1991—),男,在读硕士研究生,研究方向:人工智能应用研究。E-mail:huangqiqiao163@163.com
通讯作者:麦雄发(1974—),男,副教授,研究方向:智能计算与机器学习。E-mail:maixf@nnnu.edu.cn
更新日期/Last Update: 1900-01-01