干旱气象 ›› 2020, Vol. 38 ›› Issue (1): 157-163.

• 技术应用 • 上一篇    下一篇

宁夏贺兰山东麓酿酒葡萄采收期降水客观预测方法研究

朱晓炜1,2, 王璠1,2,孙银川1,2,王岱1,2,郑广芬1,2,王素艳1,2   

  1. (1.中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室,宁夏银川750002;2.宁夏气候中心,宁夏银川750002)



  • 出版日期:2020-02-29 发布日期:2020-03-13
  • 作者简介:朱晓炜(1985—),男,工程师,主要从事气象灾害风险管理方面的工作. E-mail: zhxw1029@163.com。
  • 基金资助:
    中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室开放研究基金(贺兰山东麓酿酒葡萄采收期阴雨过程预测技术研究)、中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室指令性项目(CAMP-201905)和宁夏回族自治区重点研发项目(2018BEG03066)共同资助

Study on Objective Precipitation Prediction Method DuringWine Grape Harvest Period in East Foothills Region of Helan Mountain Located in Ningxia

ZHU Xiaowei1,2, WANG Fan1,2, SUN Yinchuan1,2,WANG Dai1,2, ZHENG Guangfen1,2, WANG Suyan1,2   

  1. (1. Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk
     Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002, China;
    2. Ningxia Climate Center, Yinchuan 750002, China)

  • Online:2020-02-29 Published:2020-03-13

摘要: 利用1972—2016年宁夏贺兰山东麓酿酒葡萄种植区气象资料及全球大气环流及海冰、海温资料,开展酿酒葡萄采收期降水及降水过程预测研究,并采用距平符号一致率对预测结果进行评估。结果表明:利用200 hPa位势高度场、海温、海冰等预测因子建立的宁夏贺兰山东麓酿酒葡萄采收期降水预测模型距平符号一致率为67%,尤其降水空间分布一致偏多或偏少年份距平符号一致率达86%以上。进一步建立候尺度降水过程预测模型,其降水过程预测准确率为54.2%,空报率为32.3%,漏报率为13.5%。

关键词: 酿酒葡萄采收期, 降水, 预测模型, 距平符号一致率

Abstract: The rainfall and its process prediction during wine grape harvest period were analyzed by using rainfall data in the east foothills region of  Helan Mountain located in Ningxia during 1972-2016 and the atmospheric circulation, sea ice and SST data. Prediction results had been evaluated by using anomaly symbol consistence rate. The results show that the anomaly symbol consistence rate of the model established based on 200 hPa geopotential height, sea temperature and sea ice prediction factors was 67.0%, especially in concurrent rich or seldom rainfall years, it could reach 86.0%. Further, pentad rainfall prediction model had been built, the forecast accuracy was 54.2%, false alarm rate was 32.3%, false negative probability was 13.5%.

Key words:  wine grape harvest period, precipitation, prediction model, anomaly symbol consistence rate

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