江西农业学报2017，Vol.29Issue(6)：94-99,6.DOI:10.19386/j.cnki.jxnyxb.2017.06.21
基于EEMD与Markov Chain的雷暴日动态与趋势预测——以盐城地区为例
Dynamic and Trend Prediction of Thunderstorm Days in Yancheng Area Based on EEMD and Markov Chain
摘要
Abstract
Through adopting the moving t-mutation test,EEMD (Ensemble Empirical Mode Decomposition) and Markov chain statistic model,the author studied the dynamic and trend prediction of annual thunderstorm day number in the past 54 years in Yancheng area,and conducted the significance and error test for the periodicity research results.The results indicated that the annual thunderstorm day number in the past 54 years in Yancheng area revealed a decreasing trend,and the mutation year was 1966.The sequence of annual thunderstorm day number in 54 years could be decomposed into four IMF (Intrinsic Mode Function) components and a trend component.There existed two main frequency scopes:0～0.05 Hz and 0.45 ～ 0.50 Hz,and their corresponding period was 2.22 years and 27 years (their reliability all exceeded 95％).The error percentage between the reconstructed thunderstorm day data by EEMD and the original thunderstorm day data ranged from-0.8％ to 0.8％.The long-period prediction by Markov chain shows that the probability which the number of annual thunderstorm days in the future is 25～ 35 d will be about 45％,and the probability which the number of annual thunderstorm days in the future is over 35 d will be about 32％.关键词
盐城地区/年雷暴日/EEMD/Hilbert变换/马尔科夫链Key words
Yancheng area/Annual thunderstorm day/EEMD/Hilbert transform/Markov chain分类
天文与地球科学引用本文复制引用
陈超,李鹏飞,肖稳安,张春龙,吕东波..基于EEMD与Markov Chain的雷暴日动态与趋势预测——以盐城地区为例[J].江西农业学报,2017,29(6):94-99,6.基金项目
国家自然科学基金资助项目(41175003) （41175003）
江苏高校优势学科建设工程资助项目(PAPD) （PAPD）
黑龙江省气象局青年英才项目. （）
