贺兰山东麓半干旱区葡萄园最低气温和晚霜冻预报订正及检验  

Correction and verification of minimum temperature and late frost forecast in vineyards in semi-arid region of eastern foothills region of Helan Mountain

作　　者：杨婧 朱海斌 张亚刚 张晓煜 杨银[2,3,4] YANG Jing;ZHU Haibin;ZHANG Yagang;ZHANG Xiaoyu;YANG Yin(College of Enology and Horticulture,Ningxia University,Yinchuan 750021,China;Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions,China Meteorological Administration,Yinchuan 750002,China;Ningxia Key Laboratory for Meteorological Disaster Prevention and Reduction,Yinchuan 750002,China;Ningxia Meteorological Observatory,Yinchuan 750002,China;Ningxia Institute of Meteorological Science,Yinchuan 750002,China;Ningxia Meteorological Service Center,Yinchuan 750002,China)

机构地区：[1]宁夏大学葡萄酒与园艺学院,宁夏银川750021 [2]中国气象局干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 [3]宁夏回族自治区气象防灾减灾重点实验室,宁夏银川750002 [4]宁夏气象台,宁夏银川750002 [5]宁夏回族自治区气象科学研究所,宁夏银川750002 [6]宁夏气象服务中心,宁夏银川750002

出　　处：《干旱气象》2024年第4期649-659,共11页Journal of Arid Meteorology

基　　金：宁夏回族自治区重点研发计划项目(2022BBF02014);宁夏回族自治区重大科技成果转化项目(2022CJE9007);宁夏自然科学基金项目(2023AAC03804);宁夏回族自治区科技创新团队项目(2024CXTD006)共同资助。

摘　　要：为提升贺兰山东麓葡萄园晚霜冻灾害精细化防御能力,利用2020—2023年4—5月贺兰山东麓葡萄园农田小气候站最低气温观测数据,分析葡萄园最低气温变化特征、晚霜冻发生频率和区域分布特征,并基于欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)模式预报产品和宁夏地区格点气温实况,采用径向基函数(Radial Basis Function,RBF)神经网络算法,构建贺兰山东麓葡萄园最低气温和霜冻预报模型。结果表明:贺兰山东麓葡萄园轻霜冻最为普遍,其次是中霜冻,4月是霜冻发生的主要月份,东方裕兴酒庄霜冻出现最频繁,观兰酒庄霜冻最少,红寺堡产区是霜冻易发区。最低气温和霜冻预报检验结果显示,与ECMWF模式相比,RBF模型对贺兰、永宁和红寺堡产区的最低气温预报准确率提高,最高提升幅度达33.8%,平均绝对误差降低0.20~1.50℃。从单站霜冻预报看,RBF模型有明显优势,准确率普遍提升1.0%~14.0%,平均绝对误差降低0.04~0.37℃;从产区平均看,RBF模型对红寺堡产区霜冻预报准确率提高最多,达13.0%。在针对霜冻的实例分析中,RBF模型预报效果更优,特别是对中霜冻预报优势明显,相比ECMWF模式准确率提升25.0%~50.0%,平均绝对误差降低1.80~2.10℃。In order to improve the fine defense ability of late frost disaster in the vineyards in the eastern foothills region of the Helan Mountain,the minimum temperature observation data of the vineyards from April to May during 2020-2023 were used to analyze the variation characteristics of minimum temperature,the occurrence frequency and regional distribution characteristics of late frost in the vineyards.Based on the European Centre for Medium-Range Weather Forecasts(ECMWF)model forecast products and the actual tem⁃perature of grid points in Ningxia,the radial basis function(RBF)neural network algorithm was used to construct the minimum tempera⁃ture and frost prediction model in the vineyards in the eastern foot of the Helan Mountain.The results show that the light frost was the most common in the vineyards in the eastern foothills region of the Helan Mountain,followed by the medium frost.April was the main month for frost occurrence.The frost in D.F.Yuxing winery appeared most frequently,and the frost in Guanlan winery was the least.The verification results of the minimum temperature and frost forecast show that compared with the ECMWF model,the RBF model has improved the accuracy of the minimum temperature forecast in the Helan,Yongning and Hongsipu production areas,with the highest in⁃crease of 33.8%,and the average absolute error reduced by 0.20-1.50°C.For the single station frost forecast,the RBF model has obvi⁃ous advantages,the accuracy rate generally increased by 1.0%-14.0%,and the average absolute error reduced by 0.04-0.37°C.For the average of the production areas,the RBF model has the highest accuracy of frost prediction in the Hongsipu production area,up to 13.0%.In the case analysis of frost,the RBF model has better prediction effect,especially for moderate frost prediction.Compared with the ECMWF model,the accuracy rate increased by 25.0%-50.0%,and the average absolute error reduced by 1.80-2.10°C.

关 键 词：贺兰山东麓 农田小气候站 径向基函数 晚霜冻 

分 类 号：P457.3[天文地球—大气科学及气象学]