Climate Risk Assessment of Spring Frost for Grapevine on the Loess Plateau in the Past 40 Years
To assess the climate risks of spring frost on the Loess Plateau,the daily minimum temperature observation data during spring frost period(April 1-May 31)from 1981 to 2020 for 13 meteorological stations on the Loess Plateau grapevine area were collected,and the station ratio,frequency,number of days,intensity and risk were studied by mathematical statistics and spatial analysis methods.The results showed that during the spring frost period of grapevine on the Loess Plateau from 1981 to 2020,the average daily minimum temperature showed a highly significant upward trend with 0.42℃·10y-1 of climate tendency,the lowest daily minimum temperature showed a highly significant downward trend with-0.75℃·10y-1 of climate tendency.The negative climate tendency rates of lowest daily minimum temperature were distributed sporadically and the higher absolute value was in Zuoquan with-0.76℃·10y-1.The station ratio of slight spring frost on the Loess Plateau decreased,while the moderate,severe and comprehensive spring frost increased.The frequency and number of days of slight and moderate spring frost decreased,while the severe spring frost showed increased,and the intensity of severe spring frost showed a significant upward trend;the comprehensive frequency and number of days of spring frost decreased,while the intensity showed a significant upward trend.The frequency,number of days,and intensity of spring frosts increased from southwest to northeast for all spring frost levels.The climatic risk of grapevines on the Loess Plateau decreased in the risk of slight and moderate spring frosts,and increased in the risk of severe and comprehensive spring frosts.The high-risk areas were mainly distributed in Zuoquan,Taigu and other places in the north,and the low-risk areas were mainly distributed in Huyi and Weinan in the south.The results could provide a scientific basis for the prevention and mitigation of grapevine spring frost on the Loess Plateau.
万方数据
维普
