A precipitation combined forecasting model based on atmospheric circulation and sea surface temperature

被引:0
|
作者
Wu X. [1 ]
Wang Z. [1 ]
Chen K. [2 ]
Qian S. [3 ]
Wang J. [3 ]
Chen X. [4 ]
机构
[1] School of Civil Engineering and Transportation, South China University of Technology, Guangzhou
[2] Hydrologic Bureau of Yangtze River Water Resources Commission, Wuhan
[3] State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan
[4] School of Civil Engineering, Sun Yat-sen University, Zhuhai
来源
Water Resources Protection | 2022年 / 38卷 / 06期
关键词
Atmospheric circulation; Combined forecasting model; Factor prediction opinion index; Long-term precipitation forecast; Multiple time-varying sea-temperature index; Sea surface temperature field; Three Gorges Reservoir Basin;
D O I
10.3880/j.issn.1004-6933.2022.06.011
中图分类号
学科分类号
摘要
In view of the chaos and randomness of precipitation and the high difficulty of accurate long-term precipitation prediction, the multiple time-varying sea-temperature index and factor prediction opinion index were proposed. Based on the atmospheric circulation and sea surface temperature (SST) field, a long-term combined precipitation forecasting model was constructed, which is verified by taking the Three Gorges Reservoir Basin as an example. The results show that the combined forecasting model has good applicability in the monthly precipitation forecast of the flood season from 1961 to 2020 in the Three Gorges Reservoir Basin, especially in June and September. Compared with multi-factor regression, random forest mathematical statistical model and CFSv2, ECMWF system 4 dynamic numerical models, this model is more robust and has significantly improved prediction accuracy. © 2022, Editorial Board of Water Resources Protection. All rights reserved.
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页码:81 / 87
页数:6
相关论文
共 25 条
  • [1] Gu Wei, Chen Lijuan, The characteristics of the ocean atmosphere in summer 2018 and its impact on China's climate, Meteorology, 45, 1, pp. 126-134, (2019)
  • [2] Chen Lijuan, Yuan Yuan, Yang Mingzhu, Et al., Research progress on the mechanism of sea temperature anomalies affecting the East Asian summer monsoon, Journal of Applied Meteorology, 24, 5, pp. 521-532, (2013)
  • [3] Zhao Junhu, Feng Guolin, Circulation characteristics and forecast signals of two types of rain patterns in the middle and lower reaches of the Yangtze River and South China in summer, Atmospheric Science, 40, 6, pp. 1182-1198, (2016)
  • [4] GUO Yan, LI Jianping, ZHU Jiangshan, A moving updated statistical prediction model for summer rainfall in the middle-lower reaches of the Yangtze River valley [J], Journal of Applied Meteorology and Climatology, 56, pp. 2275-2287, (2014)
  • [5] BAKER LH, SHAFFREY LC, SCAIFE A A., Improved seasonal prediction of UK regional precipitation using atmospheric circulation [J], International Journal of Climatology, 38, pp. 437-453, (2018)
  • [6] Sun Zhaobo, Tan Guirong, Zhao Zhenguo, Et al., Artificial neural network ensemble prediction of summer rain patterns in eastern China, Journal of Atmospheric Sciences, 36, 1, pp. 1-6, (2013)
  • [7] ZWIERS FW, VON STORCH H., On the role of statistics in climate research [J], International Journal of Climatology, 24, pp. 665-680, (2004)
  • [8] Zhang Banglin, Chou Jifan, Sun Zhaobo, An EOF iterative scheme for forecasting China's summer precipitation using the previous atmospheric circulation, Science Bulletin, 23, pp. 1797-1798, (1991)
  • [9] DING Ting, KE Zongjian, A comparison of statistical approaches for seasonal precipitation prediction in Pakistan, Weather and Forecasting, 28, pp. 1116-1132, (2013)
  • [10] Zou Lei, Xia Jun, Zhang Yin, Et al., Analysis of the spatiotemporal evolution characteristics and driving forces of precipitation in the Haihe River Basin, Water Resources Protection, 37, 1, pp. 53-60, (2021)