[1]曲成军,林嘉楠,赵广娜.近50年黑龙江省初霜日变化影响因子及预测模型建立的研究[J].自然灾害学报,2019,28(03):205-213.[doi:10.13577/j.jnd.2019.0323]
 QU Chengjun,LIN Jianan,ZHAO Guangna.Study on influencing factors and prediction model of the first frost date in Heilongjiang Province in recent 50 years[J].,2019,28(03):205-213.[doi:10.13577/j.jnd.2019.0323]
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近50年黑龙江省初霜日变化影响因子及预测模型建立的研究
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《自然灾害学报》[ISSN:/CN:23-1324/X]

卷:
28
期数:
2019年03期
页码:
205-213
栏目:
出版日期:
2019-06-28

文章信息/Info

Title:
Study on influencing factors and prediction model of the first frost date in Heilongjiang Province in recent 50 years
作者:
曲成军1 林嘉楠2 赵广娜1
1. 黑龙江省气象台, 黑龙江 哈尔滨 150030;
2. 宾县气象局, 黑龙江 哈尔滨 150400
Author(s):
QU Chengjun1 LIN Jianan2 ZHAO Guangna1
1. Meteorologica Observatory of Heilongjiang Province, Harbin 150030, China;
2. Meteorological Bureau of Bin County, Harbin 150400, China
关键词:
初霜日变化影响因子预测模型实践检验
Keywords:
first frost datechangeinfluence factorprediction modelpractice test
分类号:
X43
DOI:
10.13577/j.jnd.2019.0323
摘要:
为了达到提前做好初霜日预测的目的,利用实际监测1961-2011a初霜日、终霜日、无霜日数及有关气象因子,其中包括月、季平均气温,月、季降水量等资料。采用趋势分析和统计相关计算、等级的划分等方法,分析了近50年初、终霜日与无霜日、夏季温度年际变化特点。结果表明,20世纪80年代后随着全球气候暖化,初霜日与终霜日大有后延与提前及无霜日数增加的特点和夏季温度升高的趋势。相关分析表明,影响初霜日变化重要因子为前期5月终霜日的反相关变化和无霜日数的正相关变化。并依此关系构建了直角三角形初霜冻发生日的预测模型。又根据直角三角形tgα=y/x将初霜日出现早晚划分成特早、偏早、正常、偏晚、特晚5个级别;并又利用了终霜日和夏季平均温度与无霜日数的相关关系组成了能够预测无霜日数的散布图;经2012-2017a6年预测实践检验全部正确。综上只要通过本地终霜日、无霜日数与初霜日关系就可构建直角三角形初霜冻日的预测模型进行预测以减轻对农业灾害损失目的。
Abstract:
In order to predict the first frost day in advance,the observation data from 1961 to 2011 are used and the interannual variation characteristics of the first frost day, the last frost day, the number of days without frost, and the summer temperature in recent 50 years are analyzed, by using the methods of trend analysis, statistical correlation calculation and classification. The results show that the first frost day is delayed, the last frost day is advanced, the number of frost-free days increases, and the summer temperature rises, with the global warming since the 1980s. It shows that the important influencing factors of the first frost day are associated with the reverse correlation of the last frost day in May and the positive correlation of the number of frost-free days. The prediction model of the first frost date of right triangle is established, and the timing of the first frost day is divided into 5 grades:extra early, early, normal, late and extra late, according to the right triangle tgα=y/x. A scatter plot is constructed to predict the number of frost-free days, by using the correlation between the number of days without frostand the average temperature in summer. The methods are proved correct by the forecast practice test of 2012-2017.It is concluded that the prediction model of the first frost days in right triangle can be established by relationship between the number of the last frost days and the first frost days. Finally, the prediction model is used to reduce the loss of agricultural disaster.

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相似文献/References:

[1]杨新.西安市降水频率变化特征分析[J].自然灾害学报,2011,20(04):060.
 YANG Xin.Characteristic analysis of change in precipitation frequency in Xi’an City[J].,2011,20(03):060.

备注/Memo

备注/Memo:
收稿日期:2018-06-01;改回日期:2018-10-23。
基金项目:科技部公益性行业(气象)科研专项(GYHY201306036)
作者简介:曲成军(1966-),男,高级工程师,博士,主要从事气象科技工作.E-mail:qcj_66@163.com
通讯作者:赵广娜(1981-),女,高级工程师,硕士,主要从事灾害性天气预报研究.E-mail:qxtzgn@sina.com
更新日期/Last Update: 1900-01-01