武汉大学樱花花期长度特征及预报方法

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 武汉大学樱花花期长度特征及预报方法 DOI: 10.5846/stxb201909241996 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目（2018YFA0606102） Characteristics and forecast of flowering duration of Cherry Blossoms in Wuhan University Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:武汉大学樱花是武汉的一张"城市名片"，开展樱花花期长度的预报工作，可为旅游部门管理工作和游客安排出行时间提供合理的参考。根据1979-2018年40年武汉大学樱园日本樱花树始花期和落花期的观测资料及同期气象资料的研究分析表明：（1）樱花的始花期和落花期在20世纪80-90年代期间有明显的提前；从20世纪90年代末开始至今，始花期与落花期变化趋势不明显，但变率较大，与全球气候变化停滞期相吻合；40年间花期长度变率很大，整体无明显的增多或减少的趋势。（2）平均始花期为3月14-15日，落花期为3月31日-4月1日，平均花期长度为18d。（3）花期长度与当年始花期日序数、开花期间平均气温、开花期间最高平均气温、最低平均气温和温度日较差平均值均呈负相关，与开花期间总降水量呈正相关。与开花期内平均极大风速值、平均降水量和日照时数等无明显相关性。（4）用1979-2015年共37年资料建立了樱花花期长度的单因子拟合、多因子回归及主成分分析模型，用2016-2018年3年资料进行检验，对武汉大学樱花花期长度进行了预报，取得了较好的试验效果。其中主成分回归模型、降水单因子拟合模型和多因子樱花花期长度回归模型预报效果最好，平均绝对误差在1.5d左右，后期将会把预报模型运用到实际的樱花花期预报工作中。 Abstract:Japanese cherry blossoms of Wuhan University is a city card of Wuhan. It can provide a reasonable reference for the management of tourism department and the arrangement of travel time for tourists to carry out the prediction of the length of cherry blossom period. A 40-year-old (1979-2018) dataset of flowering dates of Japanese cherry blossoms at Wuhan University Campus associated with the meteorological data was used for developing a method of forecasting the flowering duration of cherry blossoms. (1) The first-flowering and falling flowering date of cherry blossoms were obviously advanced in the 1980s-1990s. Since the end of 1990s, the trend of initial flowering and falling flower period is not obvious, but the rate of variation is large, which coincides with the stagnation period of global climate change.In the past 40 years, the change rate of florescence length was very large, but there was no obvious trend of increase or decrease. (2) The average first-flowering date was March 14-15, the falling flowering date was March 31 to April 1, and the average flowering period was 18 days. (3) The length of flowering period was negatively correlated with the first-flowering date, and negatively correlated with the average temperature, the highest average and the lowest average temperature during flowering period. It's also negatively correlated with the average daily temperature difference, and positively correlated with the total precipitation during florescence. There was no significant correlation with the average maximum wind speed, average precipitation and sunshine hours during flowering period. (4) Single factor fitting, multi-factor regression and principal component analysis model of cherry blossom period length were established based on the data from 1979 to 2015, which were tested by the data from 2016 to 2018. These models were used to predict the length of cherry blossom period in Wuhan University and good experimental results were obtained. Among them, principal component regression model, precipitation single factor fitting model, and multi-factor cherry blossom period length regression model are the best, with an average absolute error of about 1.5 days. In the future, the prediction model will be applied to the actual cherry blossom period prediction. 参考文献 相似文献 引证文献