• 论文 •

### 湖南月蒸发量的时空变化特征及其与月平均气温的相关性

1. （1．湖南师范大学 资源与环境科学学院，长沙 410081；2．湖南省气象局，长沙 410007）
• 收稿日期:2015-11-17 出版日期:2016-09-05 发布日期:2016-09-05
• 通讯作者: 贺新光（1973―），男，湖南人，教授，博士，主要研究方向为水文气象、地下水数值模拟预测，（E-mail）xghe@hunnu.edu.cn
• 作者简介:陈阿娇（1991―），女，四川人，硕士研究生，主要从事水文气象研究，（E-mail）ajchen0807@163.com
• 基金资助:
国家自然科学基金项目（41472238）；湖南省教育厅资助科研项目（14A097）

### Spatiotemporal Variability of Monthly Evaporation and Correlation between Monthly Evaporation and Monthly Mean Temperature in Hunan Province

CHEN Ajiao1，HE Xinguang1，CAO Siqin2，ZHANG Xinping1

1. （1．School of Resources and Environmental Science，Hunan Normal University，Changsha 410081，China；2．Hunan Meteorological Administration，Changsha 410007，China）
• Received:2015-11-17 Online:2016-09-05 Published:2016-09-05

Abstract: The spatiotemporal distribution of monthly evaporation and the nonlinear interaction between monthly evaporation and monthly mean temperature in the period 1981-2013 in Hunan Province are analyzed by applying the empirical orthogonal function (EOF) and cross wavelet transform．The EOF decomposition of the monthly evaporation shows that the first three EOF modes can account for 77.9% of total variability．The EOF1 (63.4%) reveals that the main spatiotemporal distribution of monthly evaporation in Hunan province is the type of East-West contrary, which reflects that there exists a certain negative correlation between the monthly evaporation and elevation．The EOF2 (8.5%) is of a frequent positive and negative alternation in phase of the time coefficient, which reflects a more complex spatiotemporal change of the monthly evaporation．The value of EOF3(6.0%) shows a distribution as ‘+、-、+’．Then, the cross wavelet and wavelet coherence between monthly evaporation and monthly mean temperature are computed by respectively selecting Hongjiang, Sangzhi and Xinhuang as the representative station of the first three EOF modes． The results show that at the time scale of 8-16 months, the most significant correlation between monthly evaporation and monthly mean temperature occurs and all their phase angles are zero, which illustrates that the temperature strongly effects on the evaporation and there exists no lag effect at these time scales． But at the time scales of less than 8 months or more than 16 months, the occurrence rate and distribution of strong correlation and phase angles are obviously different along time axis．