基于农业旱情解析我国粮食主产区极端无雨事件的演变特征  

Evolution Characteristics of Extreme Dry Events in China's Main Grain Production Areas Based on Analysis of Agricultural Drought Conditions

作　　者：黄进[1] 柳艺博[1] 张方敏[1] HUANG Jin;LIU Yi-bo;ZHANG Fang-min(School of Applied Meteorology,Nanjing University of Information Science and Technology,Nanjing 210044,China)

机构地区：[1]南京信息工程大学应用气象学院,江苏南京210044

出　　处：《水电能源科学》2023年第10期10-13,18,共5页Water Resources and Power

基　　金：国家自然科学基金项目(42177436)。

摘　　要：基于1980~2019年间我国13个粮食主产省份的农业干旱受灾统计数据及逐日降水资料,采用H-P滤波提取了气候致损强度(CCLI),并构建了其对无雨日指数(DDI)和大尺度大气—海洋指数(LAOI)的响应关系。结果发现CCLI与不同月份DDI的相关分析表明夏旱对灾情贡献更高,特别是7月无雨日总天数被识别为10个省份的首要致旱因子(PDCF);河南、江苏、湖北、内蒙古、吉林、辽宁的PDCF均呈现显著增强趋势,表明了夏季关键月份旱灾风险的加剧;各省份PDCF的波动存在2~3年的主周期;在0~12个月时滞下,北大西洋涛动、太平洋暖池、北极涛动等环流信号对旱情有着显著影响。研究结果可为区域干旱监测及预警提供科学依据。Based on the agricultural drought-affected rate of 13 major grain producing provinces in China from 1980 to 2019 and the daily rainfall data,the climate-caucusing loss intensity(CCLI) were extracted using H-P filtering,and its responses to dry-days indices(DDI) and large-scale atmospheric-ocean indices(LAOI) were explored.The correlation analysis between CCLI of each province and DDI in different months indicated that summer drought had the higher contribution to the disaster situation,especially the total number of dry days in July was identified as the primary drought-causing factors(PDCF) in 10 provinces.The PDCF in Henan,Jiangsu,Hubei,Inner Mongolia,Jilin,and Liaoning all showed a significant strengthening trends,indicating the intensification of drought risk in the key month of summer;The fluctuation of PDCF in each province had a main cycle of 2-3 years;At the time-lag of 0-12 months,circulation signals such as North Atlantic Oscillation,Pacific Warm Pool,and Arctic Oscillation had the significant impacts on the drought situation.This study can provide scientific basis for regional drought monitoring and early warning.

关 键 词：农业干旱受灾率 H-P滤波 无雨日指数 大尺度大气—海洋指数 

分 类 号：P424[天文地球—大气科学及气象学] TV11[水利工程—水文学及水资源]