Responses of Agricultural Drought in China's Main Grain Production Areas to Climatic Changes Based on EEMD

HUANG Jin; LIU Yibo; ZHANG Fangmin

doi:10.13870/j.cnki.stbcxb.2023.05.041

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Responses of Agricultural Drought in China's Main Grain Production Areas to Climatic Changes Based on EEMD

更新时间：2025-03-12

- Responses of Agricultural Drought in China's Main Grain Production Areas to Climatic Changes Based on EEMD
- Vol. 37, Issue 5, Pages: 337-344(2023)
- 作者机构：
  
  南京信息工程大学应用气象学院,南京,210044
- 作者简介：
- 基金信息：
- DOI：10.13870/j.cnki.stbcxb.2023.05.041
  CLC： P429
- Published：2023
- 稿件说明：
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HUANG Jin, LIU Yibo, ZHANG Fangmin. Responses of Agricultural Drought in China's Main Grain Production Areas to Climatic Changes Based on EEMD[J]. 2023, 37(5): 337-344.
DOI：

HUANG Jin, LIU Yibo, ZHANG Fangmin. Responses of Agricultural Drought in China's Main Grain Production Areas to Climatic Changes Based on EEMD[J]. 2023, 37(5): 337-344. DOI： 10.13870/j.cnki.stbcxb.2023.05.041.

摘要

量化旱情统计数据与气候因子间的响应关系对保障粮食安全有着重要意义。针对我国13个粮食主产省份1980-2019年的农业干旱受灾率

采用集合经验模态分解(EEMD)构建了实际灾情对不同月份气候因子的响应关系

进而探求重要气候因子与大尺度大气-海洋指数(LAOI)的可能联系。结果表明:(1) EEMD从灾情逐年序列分离出中短期波动表征的气候干旱强度(IMF-H)和趋势项表征的干旱脆弱性;(2) IMF-H的峰值差异表明东北3省的干旱强度明显高于其他省份;(3) IMF-H与气候因子的线性关系表明夏季气候异常对灾损贡献最高

特别是7月份的日均日照时间及降水被筛选为10个省份的干旱关键影响因子(KDII);(4)各省份KDII的时序诊断结果表明

2000以来长江北部地区的夏季干旱风险有一定的增强趋势;(5) 在0~12个月时滞下

Nino海温、南方涛动、北太平洋遥相关型等表征ENSO及北半球大气低频振荡的LAOI对研究区KDII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。

Abstract

Quantifying the response relationship of drought statistical data and climatee factors is of great significance for ensuring food security. Aiming the agricultural drought-affected rate in 13 grain producing provinces from 1980 to 2019

the responses of the actual disaster conditions to the climatic factors of different months were constructed by using ensemble empirical mode decomposition (EEMD)

and then the possible relationship between important climatic factors and large-scale atmospheric-ocean indices (LAOI) were explored. The main results were as follows:(1) The climate drought intensity reflected by medium-short term fluctuations and the drought vulnerability reflected by trend item were extracted from the annual disaster series by using EEMD. (2) The peak difference of IMF-H indicated that the drought intensity in the three northeastern provinces were significantly higher than those of other provinces. (3) The linear relationship between IMF-H and climatic factors showed that summer climate anomalies had the highest contribution to disaster damage

especially the average daily sunshine hours and precipitation in July were selected as the key drought-influencing factors (KDII) in 10 provinces. (4) The time-series diagnosis results of KDII in various provinces showed that the risk of summer drought in the northern part of Yangtze River had increased since 2000. (5) At the time-lag of 0 to 12 months

the LAOI characterizing ENSO and atmospheric low-frequency oscillation in the northern hemisphere

such as Nino SST

Southern Oscillation and North Pacific teleconnection

had the significant impacts on the KDII in the study area. This study could provide scientific basis for regional drought monitoring and early warning.

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